Embed Size (px)
Citation preview
The University of Maine The University of Maine
DigitalCommons@UMaine DigitalCommons@UMaine
Electronic Theses and Dissertations Fogler Library
Fall 12-18-2020
Adsorptive Surface Modification of Cellulose Nanocrystals to Adsorptive Surface Modification of Cellulose Nanocrystals to
Stabilize Nutraceuticals Loaded Lipid Carriers for Food Stabilize Nutraceuticals Loaded Lipid Carriers for Food
Application Application
Avinash S. Patel University of Maine, [email protected]
Follow this and additional works at: https://digitalcommons.library.umaine.edu/etd
Part of the Food Chemistry Commons, Food Processing Commons, Other Food Science Commons,
and the Other Nutrition Commons
Recommended Citation Recommended Citation Patel, Avinash S., "Adsorptive Surface Modification of Cellulose Nanocrystals to Stabilize Nutraceuticals Loaded Lipid Carriers for Food Application" (2020). Electronic Theses and Dissertations. 3303. https://digitalcommons.library.umaine.edu/etd/3303
This Open-Access Thesis is brought to you for free and open access by DigitalCommons@UMaine. It has been accepted for inclusion in Electronic Theses and Dissertations by an authorized administrator of DigitalCommons@UMaine. For more information, please contact [email protected].
ADSORPTIVE SURFACE MODIFICATION OF CELLULOSE
NANOCRYSTALS TO STABILIZE NUTRACEUTICALS LOADED LIPID
CARRIERS FOR FOOD APPLICATION
By
Avinash Singh Patel
M.S. Banaras Hindu University, India, 2014
B.S. Mahatma Gandhi Kashi Vidyapith, India, 2012
A DISSERTATION
Submitted in Partial Fulfillment of the
Requirements for the Degree of
Doctor of Philosophy
(in Food and Nutrition Sciences)
The Graduate School
The University of Maine
December 2020
Advisory Committee:
Mary E. Camire, Professor of Food Science & Human Nutrition, Co-Advisor
Robert C. Causey, Professor of Animal and Veterinary Sciences, Co-Advisor
Carl P. Tripp, Professor of Chemistry
Mehdi Tajvidi, Associate Professor of Renewable Nanomaterials
Denise I. Skonberg, Professor of Food Science and Human Nutrition
ii
© 2020 Avinash Singh Patel
All Rights Reserved
iii
ADSORPTIVE SURFACE MODIFICATION OF CELLULOSE NANOCRYSTALS
TO STABILIZE NUTRACEUTICALS LOADED LIPID CARRIERS FOR FOOD
APPLICATION
By Avinash Singh Patel
Dissertation Co-Advisors: Dr. Mary Ellen Camire and Dr. Robert Causey
An Abstract of the Dissertation Presented
in Partial Fulfillment of the Requirements for the
Degree of Doctor Philosophy
(in Food and Nutrition Sciences)
December 2020
Lipid carriers such as emulsions and liposomes have been widely studied as
carriers for different nutraceuticals. However, lipid carriers' physicochemical
instability results in the leakage of loaded nutraceuticals and the low solubility into the
digestion medium, thus reducing the bioaccessibility. Cellulose nanocrystals (CNC) are
nano-sized cellulose derivatives obtained after hydrolysis of cellulosic matrices that
possess potential applications in functional foods and nutraceuticals. However,
hydrophilicity, anionic surface potential, and poor re-dispersibility limit CNC’s
applications. The primary objectives of this research were 1) to modify CNC via
adsorbing polyethylene glycol (PEG) to stabilize liposomes and to study its
physiochemical stability at different in vitro gastrointestinal tract (GIT) conditions, pH
levels (1-11), temperatures (4-100 ºC) and illumination periods (4-72 hours); 2) to
modify CNC via adsorbing lauric acid to stabilize O/W emulsion and to study its
physicochemical stability at different pH (1-11), dilution factors (1-10 times), storage
period (up to 30 days) and GIT conditions. Phycobiliprotein and beta-carotene were
chosen as model nutraceuticals.
iv
In study 1, particle size and microscopic analysis revealed a better physical/kinetic
stability for the liposomes stabilized with PEG-adsorbed CNC than the liposomes
stabilized with unmodified CNC, resulting in significantly (p≤0.05) smaller average
particle size during the initial and mouth phases of the in vitro GIT study, nonetheless
a significant (p≤0.05) increase in the particle size from ~300 nm to ~5500 nm at gastric
phase due to lower pH. Moreover, stabilized liposomes retained the attributes of
phycobiliprotein against pH, illumination, and a temperature of 60 C. In study 2, lauric
acid-adsorbed CNC affirmed the kinetic/physical stability of emulsions throughout the
GIT phases. Results exhibited a maximum of 65% beta-carotene bioaccessibility for
the emulsion stabilized with modified CNC, and 71% for the emulsion stabilized with
unmodified CNC. Moreover, a higher amount of lipid oxidation was recorded for the
emulsion with stabilized modified CNC than the emulsion stabilized with gum Arabic.
Although modified CNC retains the kinetic/physical stability of lipid carriers;
however, it increases lipid carriers' chemical instability and decreases the loaded
nutraceuticals' bioaccessibility. A strategic modification of CNC is needed to ensure
the stability of lipid carriers and increased nutraceuticals bioaccessibility.
iii
DEDICATION
I dedicate this dissertation to my beloved mother, who taught me to believe in myself,
my father, who taught me to believe in hard work and dedication, and my teachers
and friends for providing me knowledge, devotion, and encouragement.
iv
ACKNOWLEDGMENTS
Fervently and modestly, I extol the genuine cooperation, inspiration and affection
offered to me by the Co-Chairman of the advisory committee, Dr. Mary Ellen Camire,
Professor of Food Science & Human Nutrition, in completing the research work in
time, successfully. The present work bears the impression of her concrete suggestions,
guidance, and meticulous attention to detail.
I humbly place on record my respect and gratitude to Dr. Balunkeswar Nayak
(former advisor), previously Associate Professor, School of Food and Agriculture, for
his valuable guidance and cooperation towards completing my research and study. I am
grateful to members of my advisory committee, Dr. Robert Causey, Dr. Carl P. Tripp,
Dr. Mehdi Tajvidi, and Dr. Denise Skonberg, for constant motivation, rendered at all
stages of this endeavor and my study period.
I record my profound thanks to the India Council of Agricultural Research (ICAR),
New Delhi, India, for awarding me with a prestigious Netaji Subhas International
Fellow award (award number: 18(02)/2016-EQR/Edn.) and financial support to
perform my doctoral degree at the University of Maine. I want to thank the USDA
National Institute of Food and Agriculture Hatch project ME-021914, for financial
support of my research work through the Maine Agricultural and Forest Experiment
Station (MAFES).
I owe a deep debt of thankfulness and heartfelt regards to Dr. Abhijit Kar, ICAR-
IARI, New Delhi for his endless inspirational help and Mr. Kuldeep Katiyar, Nicholas
Shoes, Pvt. Ltd., Greater Noida, India for his generous financial supports providing a
v
security bond of $10,000 FD (fix deposit) in favor of the ICAR, India until successful
completion of the degree program.
My sincere thanks to the Intensive English Institute and Office of International
Programme for their kind support in my first year of classes and creating an
overwhelming and friendly environment around the campus making this place feel like
home.
I also record my sincere thanks to Dr. L. Brian Perkins, Katherine Davis-Dentici,
David Labrecque, and Kelly Edwards for their guidance and assistance on
instrumentation and analysis. I would like to thank SuriyaPrakash
Lakshmibalasubrmaniam and my other past and current labmates and friends (Praveen
Sappati, Richa Arya, Adoum Fadaya Arabi, Samuel Akomea Frempong, Zach
Dijkhoff, Holly Leung, Rosanna Woodruff, Islam Hafez and all my SFA family
members, UMaine, for helping me in one or the other manner during my research work.
Mere words of acknowledgment will never express my deepest sense of gratitude
and indebtedness to my father Shri. Umashankar Patel, my brothers (Anurag and
Ashwani) and sisters (Mrs. Shalendri Patel and Mrs. Arati Patel), my family members,
whose much-cherished love, inspiration ever encouraging moral support; selfless
sacrifices enabled me to pursue my studies with unfailing zeal and devotion. To them,
I owe more than I say.
The words are not eloquent enough to express my special feeling for my mother
Smt. Basmati Devi, whose moral support, deep affection, encouragement, ever willing
help and understanding always envisioned me throughout this research work.
Last but not least, none is forgotten, but all of them may not be mentioned.
vi
TABLE OF CONTENTS
DEDICATION ...............................................................................................................v
ACKNOWLEDGMENTS ........................................................................................... vi
CHAPTERS
1. INTRODUCTION .................................................................................................1
1.1. Background ...................................................................................................1
1.2. Objectives .....................................................................................................5
2. LITERATURE REVIEW ......................................................................................7
2.1. Nutraceuticals .................................................................................................8
2.1.1. Phycobiliproteins (PBP) ....................................................................10
2.1.2. Characteristics of PBP .......................................................................11
2.1.3. Stability of PBP .................................................................................12
2.1.4. Carotenoids .......................................................................................14
2.1.5. Stability of carotenoids ......................................................................15
2.2. Lipid carriers .................................................................................................16
2.2.1. Oil-in-water emulsion: preparation and physicochemical stability ...18
2.2.2. Stabilization of O/W emulsion ..........................................................21
2.2.3. Pickering emulsion ............................................................................22
2.2.4. O/W emulsion and modified CNC ....................................................24
2.2.5. Liposomes and stability .....................................................................25
2.3. Cellulose ........................................................................................................27
2.3.1. Cellulose nanomaterials ......................................................................29
2.3.2. Application of cellulose nanomaterials ...............................................30
vii
2.3.3. Cellulose nanocrystals ........................................................................32
3. STERIC STABILIZATION OF PHYCOBILIPROTEIN LOADED LIPOSOMES
WITH POLYETHYLENE GLYCOL ADSORBED CELLULOSE
NANOCRYSTALS AND THEIR IMPACT ON THE GASTROINTESTINAL
TRACT .................................................................................................................35
3.1. Introduction ..................................................................................................35
3.2. Materials and Methods .................................................................................38
3.2.1. Chemicals and reagents.....................................................................38
3.2.2. Purification and characterization of phycobiliprotein.......................39
3.2.3. Quantification of phycobiliprotein ....................................................40
3.2.4. Gel electrophoresis analysis of phycobiliproteins ............................41
3.2.5. Adsorption of PEG with CNC ..........................................................42
3.2.6. Preparation and stabilization of PBP loaded liposomes ...................42
3.2.7. In vitro gastrointestinal tract (GIT) study .........................................43
3.2.8. Determination of particle size and zeta potential ..............................46
3.2.9. Spectrofluorometer analysis of phycobiliprotein ..............................46
3.2.10. FTIR analysis ..................................................................................46
3.2.11. Confocal laser scanning microscopic ..............................................48
3.2.12. Statistical analysis ...........................................................................48
3.3. Results and Discussion ...............................................................................48
3.3.1. Phycobiliproteins in content the extract ............................................48
3.3.2. Gel electrophoresis of purified PBP .................................................49
3.3.3. Adsorption of PEG with CNC ..........................................................50
viii
3.3.4. Effect of PEG’s molecular weight on average particle size and zeta
potential of desulfated cellulose nanocrystals (DCs) ........................51
3.3.5. Effect of gastrointestinal tract (GIT) phase on the quality
characteristics of phycobiliprotein (PBP) loaded liposomes ............54
3.3.5.1. Effect on average particle size ...........................................54
3.3.5.2. Effect on zeta potential ......................................................60
3.3.5.3. Stability of phycobiliprotein ..............................................62
3.4. Conclusion .....................................................................................................63
4. IMPROVED STABILITY OF PHYCOBILIPROTEIN WITHIN LIPOSOME
STABILIZED BY POLYETHYLENE GLYCOL ADSORBED CELLULOSE
NANOCRYSTALS ..............................................................................................64
4.1. Introduction ...................................................................................................64
4.2. Materials and Methods ..................................................................................68
4.2.1. Adsorption of PEG with CNC ..........................................................68
4.2.2. Encapsulation and stabilization of phycobiliproteins .......................69
4.2.3. Encapsulation efficiency of phycobiliproteins ..................................70
4.2.4. Stability analysis of phycobiliproteins ..............................................71
4.2.5. Particle size and zeta potential analysis ............................................72
4.2.6. Microscopic analysis .........................................................................72
4.2.7. Statistical analysis .............................................................................73
4.3. Results and Discussion .................................................................................73
4.3.1. Adsorption of PEG with desulfated CNC .........................................73
4.3.2. Effect of pH on average particle size ................................................74
ix
4.3.3. Effect of pH on zeta potential ...........................................................79
4.3.4. Effect on the coalescence and agglomeration of behavior of liposomes
and cellulose nanocrystals.................................................................81
4.3.5. Effect of pH on the stability of phycobiliproteins ............................83
4.3.6. Effect of temperatures on the stability of phycobiliproteins .............86
4.3.7. Effect of illumination on the stability of the phycobiliproteins ........89
4.4. Conclusion ...................................................................................................90
5. PHYSICOCHEMICAL STABILITY OF O/W PICKERING EMULSION
STABILIZED WITH LAURIC ACID ADSORBED CELLULOSE
NANOCRYSTALS AND THE EFFECT OF DILUTIONS, pH, AND STORAGE
PERIODS .............................................................................................................92
5.1. Introduction ...................................................................................................92
5.2. Materials and Methods ..................................................................................95
5.2.1. Adsorption of lauric acid with CNC .................................................95
5.2.2. Preparation of beta-carotene emulsion and stabilization ..................98
5.2.3. Stability study of emulsions ..............................................................98
5.2.3.1. Effect of dilution ..................................................................99
5.2.3.2. Effect of pH..........................................................................99
5.2.3.3. Effect of storage periods ......................................................99
5.2.4. Particle size and zeta potential analysis ..........................................100
5.2.5. Optical microscopic analysis ..........................................................100
5.2.6. Creaming index ...............................................................................100
5.2.7. TBARS analysis ..............................................................................101
x
5.2.8. Beta-carotene stability ....................................................................103
5.2.9. Mineral analysis ..............................................................................103
5.2.10. Statistical analysis .........................................................................104
5.3. Results and Discussion ..................................................................104
5.3.1. Characterization of lauric acid adsorbed CNC (CL) .......................104
5.3.2. Stability of Pickering emulsion .......................................................106
5.3.2.1. Effect of dilutions on average particle size ........................106
5.3.2.2. Effect of pH on average particle size .................................111
5.3.2.3. Effect of storage on average particle size ..........................113
5.3.2.4. Effect on creaming index ...................................................114
5.3.3. Oxidative stability of emulsions ......................................................119
5.3.4. Beta-carotene stability .....................................................................122
5.4. Conclusion ...................................................................................................124
6. DEVELOPMENT OF O/W PICKERING EMULSION USING LAURIC ACID
ADSORBED CELLULOSE NANOCRYSTALS (CNC): AN IN VITRO
GASTROINTESTINAL TRACT STUDY ..........................................................125
6.1. Introduction .................................................................................................125
6.2. Materials and Methods ................................................................................129
6.2.1. Adsorption of lauric acid with CNC ................................................129
6.2.2. Preparation of emulsions .................................................................130
6.2.3. In vitro gastrointestinal tract (GIT) study ........................................131
xi
6.2.3.1. Initial phase of the in vitro GIT .........................................132
6.2.3.2. Simulated saliva juice (SSJ) phase of the in vitro GIT ......132
6.2.3.3. Simulated gastric juice (SGJ) phase of the in vitro GIT ....132
6.2.3.4. Small-intestinal juice (SIJ) phase of the in vitro GIT ........132
6.2.4. Particle size and zeta potential analysis ..........................................133
6.2.5. Creaming index ...............................................................................133
6.2.6. Confocal laser scanning microscopic analysis ................................134
6.2.7. Determination of lipid digestion ......................................................134
6.2.8. Beta-carotene bioaccessibility .........................................................135
6.2.9. Statistical analysis ...........................................................................136
6.3. Results and Discussion .......................................................................136
6.3.1. Characterization of lauric acid adsorbed CNC (CL) .......................136
6.3.2. Morphology of CNC and CL ...........................................................137
6.3.3. In vitro GIT fate of the Pickering emulsion ....................................138
6.3.3.1. Initial phase ........................................................................138
6.3.3.2. Simulated saliva juice (SSJ) phase ....................................140
6.3.3.3. Simulated gastric juice (SGJ) phase ..................................143
6.3.3.4. Simulated small-intestinal juice (SIJ) phase ......................147
6.3.3.5. Lipid digestion ...................................................................149
xii
6.3.3.6. Bioaccessibility of beta-carotene .......................................150
6.4. Conclusion ...................................................................................................152
7. OVERALL CONCLUSION AND RECOMMENDATIONS ...............................153
REFERENCES ..........................................................................................................155
BIOGRAPHY OF THE AUTHOR ............................................................................184
LIST OF TABLES .......................................................................................................xv
LIST OF FIGURES ................................................................................................... xvi
xiii
LIST OF TABLES
Table 3.1. Chemical composition of simulated gastrointestinal tract (GIT) medium
used in vitro study .......................................................................................45
Table 3.2. Phycobiliprotein contents in Palmaria palmata (Dulse) ............................49
Table 5.1. Mineral contents of cellulose nanocrystals (CNC) ...................................121
xiv
LIST OF FIGURES
Figure 2.1. Hierarchical structure of cellulose from wood to monomeric unit ..........28
Figure 3.1. Size exclusion-based column separation of phycobiliproteins .................40
Figure 3.2. Macroscopic images of purified PBP (A) and freeze-dried PBP (B) .......49
Figure 3.3. SDS-PAGE of phycobiliproteins. Marker is in far left ............................50
Figure 3.4. A schematic of polyethylene glycol adsorption and FTIR spectra ..........51
Figure 3.5. Average particle size and zeta potential of PEG-modified CNC .............52
Figure 3.6. Effect of the gastrointestinal phases on the average particle size ............55
Figure 3.7. Confocal laser scanning microscopic images of stabilized liposomes .....57
Figure 3.8. FTIR spectra of CNC before and after gastric phase of GIT ...................59
Figure 3.9. Effect of gastrointestinal (GIT) phase on zeta-potential ..........................61
Figure 3.10. Stability of PBP during GIT phases ........................................................62
Figure 4.1. FTIR spectra of PEG adsorbed CNC .......................................................74
Figure 4.2. Effect of pH on the average particle size of stabilized liposomes ............76
Figure 4.3. Schematic illustration of liposomes and CNC behavior at lower pH .......78
Figure 4.4. Effect of pH range on the zeta potential value of stabilized liposomes ...80
Figure 4.5. Confocal laser scanning microscopic images of stabilized liposomes .....81
Figure 4.6. Optical microscopic image of samples at different pH ............................82
Figure 4.7. Effect of stressors on the fluorescence intensity of phycobiliproteins .....83
Figure 4.8. Effect stressors on the % loss of fluorescence of phycobiliproteins ........87
Figure 5.1. FTIR spectra lauric acid adsorbed CNC and calibration curve ................97
Figure 5.2. Calibration curve of 1,1,3,3-tetraethoxypropane (TEP) .........................102
Figure 5.3. Calibration curve of beta-carotene .........................................................103
xv
Figure 5.4. FTIR spectra of cellulose nanocrystal and lauric adsorbed CNC ..........105
Figure 5.5. Effect of dilution factors on the average particle size emulsions ...........108
Figure 5.6. Optical microscopic image of the stabilized emulsions .........................109
Figure 5.7. Schematic illustration of the stabilization of emulsions .........................110
Figure 5.8. Macroscopic image of stabilized emulsions ...........................................110
Figure 5.9. Effect of pH on the average particle size of stabilized emulsions ..........112
Figure 5.10. Effect of storage periods on the average particle size of emulsions ......114
Figure 5.11. Creaming index of the stabilized emulsions ..........................................114
Figure 5.12. UV-Vis spectra of the beta-carotene of stabilized emulsions ...............117
Figure 5.13. TBARS value of stabilized emulsions ...................................................120
Figure 5.14. Stability of beta-carotene during storage ...............................................123
Figure 6.1. FTIR spectra of CNC, lauric acid and modified CNC ...........................137
Figure 6.2. TEM images of CNC and modified CNC ..............................................138
Figure 6.3. Effect of GIT phases on average particle size of emulsions ..................139
Figure 6.4. Effect of GIT phases on zeta-potential of stabilized emulsions .............141
Figure 6.5. Confocal laser scanning microscopic images of stabilized emulsions ...142
Figure 6.6. Schematic illustration of fate of emulsions in small intestine ................145
Figure 6.7. Effect of GIT phases on creaming index of stabilized emulsion ...........146
Figure 6.8. Release of free fatty acid during the small intestinal phase ...................150
Figure 6.9. Bioaccessibility of the beta-carotene ......................................................151
1
CHAPTER 1
INTRODUCTION
1.1. Background
In the last few decades, market demands have shifted towards healthy and low-
calorie foods due to increased public health concerns, leading to the design and
development of nutraceutical and functional foods (Nahr et al., 2018; Banerjee et al.,
2019; Bai et al., 2020a). Lipid nanocarriers such as emulsion and liposome-based
delivery systems have been extensively utilized for several years as a carrier for
hydrophilic and hydrophobic nutrients and phytochemical compounds to improve their
stability, solubility, targeted delivery, and controlled release (Cagnasso et al., 2010;
McClements, 2015; Woodle et al., 2018; Ojeda-Serna et al., 2019). However, oil-in-
water (O/W) and liposome-based delivery systems have several drawbacks that include
kinetic or physical instability, oxidation of fatty acids, hydrolysis of the ester of the
bond, leakage of loaded nutraceuticals, and poor solubility in the digestion medium
(Yadav et al., 2011; Feng et al., 2018; Mehrad et al., 2018; Peng et al., 2019). Synthetic
and natural emulsifiers and stabilizers such as Tween®, sodium dodecyl sulfate (SDS),
polyethylene glycol, glycerol, fatty acids, starch, gelatin, carrageenan, protein isolates,
agar chitosan, and lecithin have been investigated to address these limitations of the
lipid-based delivery systems (Carocho et al., 2014; Kono et al., 2018; Shen et al., 2018;
Zalipsky, 2018). Considering increased public health awareness and environmental
sustainability, there has been a progressive effort to design and develop non-toxic, non-
synthetic, biocompatible, low cost, and greener biopolymers for their potential
applications in food and nutraceuticals industries. Due to unique features, cellulose and
2
its nanomaterials have inspired researchers to explore its potential application as fat
replacer (Bai et al., 2020a), emulsifier (Angkuratipakorn et al., 2017), thickener
(Sviderskyi et al., 2018), gum (Jimenez et al., 2020) and food packaging material (Stark
et al., 2016).
Cellulose is the most abundant biopolymer on the planet Earth, is a
polysaccharide, and is a linear structure of anhydro D-glucose units condensed through
a β-1,4 glycosidic bond (Peciulyte et al., 2015). Cellulose is predominantly present in
wood, cotton, hemp, some bacterial pellicles, and other plant-based products as a
principal structural material (Kargarzadeh et al., 2018). Due to its abundance in nature,
researchers have investigated the isolation, purification, and characterization of
cellulose and its derivatives, such as cellulose nanomaterials from different sources
(Chirayil et al., 2016; Prado and Spinace, 2019). Cellulose nanomaterials are
micro/nano-scaled cellulose derivatives obtained after a series of processing methods,
which include grinding, bleaching, homogenization/mechanical crushing, and chemical
hydrolysis (Kargarzadeh et al., 2018). Nano-scaled biopolymers have distinctive
features such as smaller dimension and higher surface area (Brinkmann et al., 2016),
compatibility in nano-formulations, better dispersion and homogeneity, and more
active surfaces such as hydroxyl groups (O-H) for targeted modifications (Cheng et al.,
2015; Natterodt et al., 2017; Kargarzadeh et al., 2018).
Cellulose nanocrystals (CNC), also known as crystalline nanocellulose,
nanocrystalline cellulose, or cellulose nanowhiskers, are rod or needle-shaped
nanoparticles with a dimension of 5-15 nm in width and 150-200 nm in length and up
to 99% of crystallinity (Jordan et al., 2019; Abiaziem et al., 2019). CNC is produced
3
through different techniques such as acid hydrolysis (Kargarzadeh et al., 2018), acid-
alkali hydrolysis (Jordan et al., 2019), enzymatic hydrolysis (Peciulyte et al., 2015),
and metal salt catalyzed hydrolysis (Yahya et al., 2015). Among the CNC production
methods, acid hydrolysis with sulfuric acid is most preferred because it contributes
sulfate ions (-SO3-) to the CNC. Sulfate ions on the surface of the produced CNC help
in maintaining the dispersibility of the CNC particles into an aqueous medium by
creating an electrostatic repulsion. Despite having a nano-scaled dimension and
dispersibility into an aqueous medium, CNC also comprises free surface hydroxyl
groups (O-H) (Natterodt et al., 2017), high charge potential due to sulfate ions
(Prathapan et al., 2016), and non-toxicity (Seabra et al., 2018). These properties of CNC
offer an opportunity to explore potential applications.
Commercially produced CNC possesses a significant amount of sulfate anions (-
OSO4-3), resulting in a zeta potential of approximately −55 mV (Cheng et al., 2015).
CNC with anionic properties and anionic liposomes (zeta potential −25 mV) may
encounter a strong electrostatic repulsion that may limit the adsorption of CNC onto
the surface of liposomes (Navon et al., 2017). Although a few researchers have reported
the adsorption of anionic polymers on the interface of anionic liposomes due to Van
der Waals attraction (Liu et al., 2013; Navon et al., 2017), a reduced zeta potential of
CNC can also assist in adsorption onto the interface of the liposome (Navon et al.,
2017). Moreover, it has been reported that CNC with reduced electric potential has
shown agglomeration and precipitation behavior in an aqueous medium (Cheng et al.,
2015). Besides the instability and precipitation behavior of CNC with low electrical
potential, Cheng et al. (2015) have reported that dried CNC had poor re-dispersibility
4
into an aqueous medium due to irreversible agglomeration of CNC particles caused by
existing surface O-H groups. Therefore, it is necessary to ensure the dispersibility and
the stability of CNC into aqueous medium sustaining its potential applications. Studies
have shown that the adsorption of hydrophilic molecules such as polyethylene glycol
(PEG) maintained the dispersibility of the CNC (Cheng et al., 2015). Hence, we
hypothesized that the adsorption of water-soluble molecules on the surface of CNC
would help to maintain the dispersibility of CNC into the aqueous medium and stabilize
liposome via adsorbing onto the interface, thus maintaining the stability of the liposome
and the loaded nutraceuticals.
On the other hand, CNC in stabilizing O/W emulsions have shown a significant
effect on maintaining the physicochemical stability of emulsion (Rayner et al., 2014;
Hedjazi and Razavi, 2018; Sharif and Zahid, 2018; Aswathanarayan and Vittal, 2019)
by either electrostatic (Prathapan et al., 2016) or steric repulsion mechanism (Zoppe et
al., 2012). Adsorption of CNC onto the interface of oil droplets may not be an easy
target due to the hydrophilic nature of CNC, which has many hydroxyl groups (O-H).
However, several researchers have found that the addition of 0.06% of NaCl to the
aqueous phase facilitated the adsorption of CNC particles onto the interface of oil
droplets due to increased surface pressure (Bergfreund and Fischer, 2019; Bertsch et
al., 2019). The addition of NaCl to the aqueous medium also increased the CNC-CNC
interaction due to the counter-ion effect of sodium ions (Na+) altering the rheological
properties, such as increasing the gel strength of the aqueous phase leading to higher
viscosity. The increased gel strength of the continuous phase restricts the mobility of
the free oil droplets (with no CNC on the interface), resulting in less interaction among
5
oil droplets, and thus a stable emulsion (Aaen et al., 2019). Moreover, a significant
agglomeration and an increased particle size of CNC stabilized O/W emulsion have
been reported due to a gradual dilution of the stabilized emulsion with simulated
digestive juices and the addition of counter ions (Maphosa and Jideani, 2018; Bai et
al., 2020a). Dilution of a CNC stabilized emulsion can lead to a separation of the oil
phase from the aqueous phase due to the following reasons: (a) reduced surface
pressure, thus desorption of polymer from the interface of oil droplet reducing steric or
electrostatic repulsion among droplets, and (b) weaker gel strength of the dispersing
medium, thereby increased droplets interaction thus coalescence/Ostwald ripening
(Wooster, 2006; Maphosa and Jideani, 2018; Yokota et al., 2019). Hence, we
hypothesized that modifying CNC with hydrophobic or amphiphilic molecules
properties can help to create a stable O/W emulsion by maintaining the hydrophilic and
hydrophobic balance between CNC and lipids droplets.
1.2. Objectives
The main objective of this study was to modify the surface of CNC via adsorbing
compatible food-grade polymers such as polyethylene glycol and fatty acids to ensure
the dispersibility of CNC into aqueous medium and its suitability for the stabilization
of liposomes and O/W type emulsion. One hydrophilic (phycobiliprotein) and one
hydrophobic (beta-carotene) compound were chosen as model nutraceuticals. To
ensure the physicochemical stability of the stabilized liposome, O/W emulsion, and
loaded nutraceuticals, the effect of different stressors and static in vitro gastrointestinal
tract (GIT) conditions were performed.
The specific objectives of this study are as follows:
6
1). To create a stable liposome using polyethylene glycol-adsorbed CNC and to study
the stability of the stabilized liposome during static in vitro GIT conditions.
2). To study the effect of different pH, illumination (exposure to light), and temperature
on the behavior of stabilized liposomes and the stabilization capacity for the
encapsulated phycobiliprotein.
3). Create a stable O/W type Pickering emulsion using lauric acid-adsorbed CNC and
to study the physicochemical behavior of the stabilized Pickering emulsion under
different dilution factors, pH, and storage period.
4). To study the physicochemical behavior of the stabilized Pickering emulsion during
static in vitro GIT conditions.
7
CHAPTER 2
LITERATURE REVIEW
According to the World Health Organization (WHO), good health is not just
simply the absence of illness or debility but a complete physical, mental, and social
well-being (Sartorius, 2006). Lifestyle behavior defines the state of human health,
which can be constructive to health, but it can also harm. For example, a balanced and
healthy diet improves our health; however, a diet deficient in essential nutrients or too
high in energy results in malnutrition, decreased immunity, vulnerability to several
preventable diseases, physical and mental discomfort, and compromised overall health
status (Corzo et al., 2020). Due to hectic lifestyles, increased household income,
urbanization, and availability of a variety of food options, a drastic change in regular
diet habits have arisen in the last decade among the majority of the world population.
The consequences of several chronic diseases or conditions, including chronic heart
disease (CVD), obesity, diabetes mellitus, high blood pressure, stroke, and certain types
of cancer, have affected millions of people globally, resulting in the development of
infirmity and premature death (Lynch and Smith, 2005; Silberner, 2018; Corzo et al.,
2020). These chronic diseases or conditions create immense burdens on the health and
economy of developed areas like the United States, European Union, and Australia.
According to the National Center for Chronic Disease Prevention and Health
Promotion (NCCDPHP) of the CDC, 6 in 10 adults in the United States have a chronic
disease, and 4 in 10 have two or more preexisting health conditions, costing around
$3.5 trillion annually (NCCDPHP, 2020). Even though the annual budget for public
health is high, an average of 174 (Type 2 diabetes) and 134 (hypertensive disease)
8
deaths per million population was recorded in 2016 in the United States, which was
higher than the average global deaths of 134 and 121 per million of the population
(Lynch and Smith, 2005; Editor, 2018). In the elderly, the prevalence and seriousness
of chronic diseases are higher as compared to the younger age groups (Ge et al., 2019).
In 2016, the age group of 65 years and older was estimated to be 15% of the U.S.
population, and is further estimated to increase up to 17% by the end of 2020 and 21%
in 2030 (Vespa et al., 2019). According to the United States Census, Maine was the
second oldest state in the country in 2015 and one-fifth of its population was above 65
years old. The median age of “Mainers” was 42.7 years, which was greater than the
national median age of 37.2 years (U.S. Census, 2016). Therefore, with its significantly
larger aged population, Maine residents are more likely to suffer from chronic diseases
and face an increased healthcare burden.
Studies have shown a significant impact of diet and eating habits in modulating
health and preventing chronic diseases (Costa et al., 2017). Diets rich in bioactive
compounds, also known as nutraceuticals, have the potential in controlling and
preventing several pathological mechanisms of chronic diseases and other health issues
(Ortega et al., 2019; Maqsood et al., 2020).
2.1. Nutraceuticals
Significant scientific explorations have led to notable developments of expensive,
highly innovative techniques in pharmaceutical, medical, and surgical procedures. An
emphasis on good health maintenance and the significance of proper diet has
contributed in recent decades to increased interest in alternative medical therapies
(Kuttruff et al., 2014; Hettle et al., 2017; Zhang et al., 2020). Nutraceuticals are
9
substances that might be regarded as foods or part of foods and are responsible for
providing medical or health interests. However, the United States government does not
recognize a definition for these products. While consumer interests involve the
prevention and cure of illnesses, the U.S. Food and Drug Administration restricts
claims for those abilities to drugs, not foods (Burdock et al., 2006). Nutraceutical
products extensively include special foods, isolated nutrients, diets, and dietary
supplements. Foods fortified with nutraceuticals tend to be considered as functional
foods that signify the food products consisting of health benefits that stretch beyond
basic nutrition. Depending on the nation, the federal food authority may allow different
products to claim to improve health status, delay aging, increase life expectancy,
support body structure and function, and prevent chronic illnesses (Pandey et al., 2013;
Santini et al., 2017; Corzo et al., 2020).
Nutraceuticals are grouped based on food sources, mechanisms of action, and
chemical nature. Food sources includes plants, animals, and microbes (Bao et al., 2019;
Corzo et al., 2020). Nutraceuticals are categorized according to their mechanisms of
action as anti-cancerous, anti-inflammatory, osteogenic, antioxidants, anti-cardiac
disease (Medeiros and Wildman, 2018). Other categories of nutraceuticals are based
on chemical nature such as carotenoids, collagen hydrolysate, dietary fiber, fatty acids,
flavonoids, glucosinolates, indoles, phenols, plant steroids, soy protein,
phytoestrogens, and prebiotics (Medeiros and Wildman, 2018; Bao et al., 2019; Corzo
et al., 2020). Further nutraceuticals can be classified as potential or established
nutraceuticals (Pandey et al., 2010; Medeiros and Wildman, 2018).
10
Potential nutraceuticals hold a significant promise for a particular health or
medical advantage. Potential nutraceuticals are only developed after having enough
clinical data; thus, demonstrations are made to convince consumers and regulatory
agencies. However, there are substantial scientific interventions underway to validate
the nutraceuticals in diversified health applications (Sauer and Plauth, 2017; Sharif and
Khalid, 2018).
2.1.1. Phycobiliproteins (PBP)
PBP are regarded as the main light-harvesting chromo-proteins present in some
seaweeds (Lage-Yusty et al., 2013). PBP are classified into four major classes
according to their properties in light absorption as well as the types of bilins:
phycoerythrins, phycocyanins, allophycocyanins, and the phycoerythrocyanins.
Phycoerythrins can further be divided into four classes: R-phycoerythrin (R-PE), B-
phycoerythrin (B-PE), C-phycoerythrin (C-PE), and B-phycoerythrin (B-PE); they are
grouped according to their origin and absorption spectrum. These absorption properties
are determined by various types of bilin prosthetic groups (Pagels et al., 2019; Nikolic
et al., 2020). R-PE has been identified as the most plentiful phycobiliprotein in red
algae and marine unicellular cyanobacteria (Denis et al., 2010). Microalgae are a
diversified category of photosynthetic aquatic microorganisms capable of growing in
an extended range of habitats, pH, and temperatures. Microalgae tend to have
uncomplicated growth requirements and use light, carbon dioxide, and other inorganic
components efficiently (Manirafasha et al., 2016). Recently, microalgae have drawn
researchers’ attention because of their high rate of growth and compound
diversification, capable of accumulating large amounts of bioactive compounds such
11
as proteins, lipids, carbohydrates, carotenoids, and PBP (Eyley et al., 2015; Sadhukhan
et al., 2019; Sappati et al., 2019; Nikolic et al., 2020).
Phycocyanin and phycoerythrin are photosynthetic pigments that are associated
with a blue and red color in most of the red macro/microalgae. They are also found in
cyanobacteria, rhodophytes, and cryptomonads (Falkeborg et al., 2018; Hsieh-Lo, et
al., 2019). These pigments are grouped in the family of PBP, where the main
commercial interest in these compounds stems from their high protein content and
simple extraction techniques. Reports indicate that these proteins are identified to have
health benefits like antioxidant, anti-inflammatory, anti-hypertension and anti-cancer
properties (Lee et al., 2013; Furuta et al., 2016; Manirafasha et al., 2016; Pagels et al.,
2019). PBP is identified as food-grade if the ratio of Amax PBP / A280 is greater or equal
to 0.7, reagent grade when Amax PBP / A280 ranges between 0.7 and 3.9 and analytical
grade when Amax PBP / A280 is greater than or equal to 4.0 (Dumay et al., 2013; Rastogi
et al., 2015).
2.1.2. Characteristics of PBP
Chlorophyll is a pigment responsible for photosynthesis by trapping light energy
present in most plants and algae. It is worth noting that red algae lack chlorophyll b
pigment; hence absorption of light occurs in the blue and red region within the visible
spectrum because of chlorophyll a (Hsieh-Lo, et al., 2019). Compensation of
significant absorption gaps and optimization of light energy gathered is achieved by
assembling supramolecular complexes identified as phycobilisomes within the
thylakoid membrane having an absorption range of 500-600 nm. Each phycobilisome
consists of colored proteins known as PBP. Arrangement of these molecules can be
12
made in an antenna-like shape. The absorbed energy is channeled towards the center of
the photosynthesis II reaction process, attaining an efficiency higher than 95%. PBP,
like phycoerythrin, are regarded as chlorophyll accessory pigments that contain two
primary subunits; α subunit (MW 12-19 kDa), β subunit (MW 14-21 kDa) and γ subunit
(MW 30-40 kDa), where each type consists of 160-180 amino acids (Galland-Irmouli
et al., 2000; Furuta et al., 2016; Hsieh-Lo, et al., 2019). These molecules' color is
mainly provided by the chromophore (prosthetic group) of the PBP, which is a linear
tetrapyrrole group responsible for binding the apoprotein through a thioether bond to
cysteine residues with its absorption spectrum depending upon the attached protein
(Kuddus et al., 2013; Martelli et al., 2014; Hsieh-lo et al., 2019).
2.1.3. Stability of PBP
PBP are soluble in water and produce intense colors. However, their utilization
in foods has been insubstantial because of their low stability (Rastogi et al., 2015).
Notably, these molecules are extremely unstable in the presence of light, low pH, high
temperatures, and as well in the presence of alcohol (Rastogi et al., 2015). pH changes
might lead to disruption in the electrostatic properties and hydrogen bonds that are
associated with protein’s structure, which has the capability of inducing structural
chromophore changes (Kuddus et al., 2013; Martelli et al., 2014; Hsieh-lo et al., 2019).
Lower levels of pH might lead to the denaturation of PBP, which includes the
dissociation of trimers to monomers (Ratogi et al., 2015). Moreover, under light, there
is a high tendency to lose chromophores (PBP fluorescence capacity) (Munier et al.,
2014; Rastogi et al., 2015).
13
Researchers have come up with few strategies to improve pigment stability. The
primary and most straightforward way to enhance PBP’s stability is by utilization of
additives. Various studies have been established to investigate the application of
additives, thus improving their thermal stability (Martelli et al., 2014; Gonzalez-
Ramirez et al., 2014; Braga et al., 2016). Nonetheless, low toxicity additives must be
used due to the use of large amounts of additives that might be necessary. Martelli et
al. (2014) recorded that high glucose concentration increases the thermal stability PBP.
Sugars and salts tend to act as protein stabilizing agents. The addition of sugars leads
to an increase in surface tension in water, and as a result, the thermal stability of
proteins is increased. A study by Braga et al. (2016) found improved thermal stability
of PBP when nanofiber was incorporated into the solution, followed by the addition of
polyethylene oxide and sorbitol as additives. Braga et al. (2016) indicated that the
addition of nanofibers enhanced pigment thermal stability by lowering the system's
enthalpy, thus reducing the denaturing of proteins. Benzoic acid is another additive that
seems to be very interesting in improving PBP stability. Benzoic acid is known to act
as an antimicrobial agent, thus inhibiting bacterial growth as well as antioxidant activity
(Kannaujiya et al., 2016). Crosslinking is a method where two chemical groups present
on the protein surface tend to be covalently bound by the use of biofunctional reagents
either intramolecularly or intermolecularly, thus reinforcing the folded structure (Wu
et al., 2017). Bekasova et al. (2016) reported that when intramolecular crosslinking is
applied between the protein molecule and silver nanoparticles, the stability of
phycoerythrin was increased while the protein aggregation was unchanged.
Phycocyanin stabilized through covalent crosslinking between the subunits (alpha and
14
the beta) by formaldehyde successfully inhibits the dissociation of PBP into its subunits
during treatment in SDS buffer at different temperatures (Sun et al., 2006). However,
the use of formaldehyde in food-grade ingredients is questionable from a regulatory
perspective. Alternatively, a complex formation can be another stabilization method
such that proteins can be linked covalently to a polysaccharide, thus maintaining the
extended tetrapyrrole structure (Hsieh-lo et al., 2019).
PBP products are primarily used in consumer products because of their possible
application as natural food colorants in products like ice cream, chewing gum and
candy (Sekar and Chandramohan, 2008). The application of PBP in food products is
limited since several challenges are encountered in preserving these products for a
longer duration without degradation (Rastogi et al., 2015). However, more studies are
needed to improve PBP stability and thereby increasing the number of products in the
market using PBP pigments as additives (Sekar et al., 2013; Furuta et al., 2016).
2.1.4. Carotenoids
Carotenoids are a group of hydrophobic compounds found in primarily terrestrial
plants such as carrot, tomato, sweet potato, marigold flower, and colored mature leaves
of several plants (Maoka, 2020). The carotenoids are long-chain hydrocarbon (CH)
compounds containing 40 carbon atoms with an alternating double bond. The double
bonds of the carotenoids are collectively known as isoprene units. Carotenoids
comprise a total of eight isoprene units. Structurally, carotenoids are categorized into
two groups: carotenes and xanthophylls. Carotenoids containing only carbon and
hydrogen in its structure are recognized as carotene, while others containing carbon,
hydrogen, and oxygen are xanthophylls (Xiao et al., 2018; Maoka, 2020). Typically,
15
carotenoids play a crucial role in photosynthesis and photoprotection processes in plant
tissues. An essential role of carotenoid pigments included in the diets of humans and
other animals is their potential to serve as precursors of vitamin A. The antioxidant
function of carotenoids is responsible for reducing the risks of cancer, cataracts, and
atherosclerosis (Maoka, 2020). Usually, carotenoids can be categorized based on their
functionality, and whether they are primary or secondary carotenoids. These primary
carotenoids are substances necessary for the photosynthetic process, while secondary
carotenoids are elements that are not directly related to the plant's survival (Xiao et al.,
2018).
2.1.5. Stability of carotenoids
Among various food characteristics, color may be the most significant since it is
often a consumer’s first impression or sensation (Singh, 2006; Viera et al., 2019).
Diverse food colorants have been studied to intensify food's original color. Carotenoids
are responsible for many of the brilliant reds, orange, and yellow coloring in fruits,
vegetables, and flowers (Maoka, 2020). Regrettably, several food processing functions,
particularly ones that include the application of heat, are generally known to degrade
food ingredients, and even change food coloring and its functionality (Boon et al.,
2010). Isomerization and oxidation are the significant reactions responsible for
degradation of carotenoids. Generally, conjugated double bonds in carotenoids are
known to exist in all-trans configuration. The carotenoids in plants exist mostly as
trans-isomers, and trans- to cis-isomerization mainly occurs during food processing
due to their large number of conjugated double bonds (Xiao et al., 2018). Several
factors, such as heat, light, low pH, transition metals and other pro-oxidants, promote
16
the oxidation and isomerization of carotenoids. Moreover, exposure to organic
solvents, irradiation and ozone can also induce oxidative degradation of carotenoids
(Boon et al., 2010).
Carotenoids are relatively stable typically during storage and as well as during
the handling of most fresh and minimally processed fruits and vegetables. The apparent
carotene content slightly tends to be affected by an increase in temperature, such as the
blanching process. Blanching affects cell walls and thus makes carotenoids easier to
extract than from raw plant tissues (Cilla et al., 2018; Mehmood and Zeb, 2020).
Natively, carotenes are considered reasonably stable at a lower temperature; however,
heating at a higher temperature, such as those that occur during sterilization, can
facilitate the induction of trans to cis isomerization reaction processes (Xiao et al.,
2018). Nevertheless, carotenoid isomerization results in a slight decline in biological
activities and the color saturation, while oxidation terminates all operations and color
in carotenoids. The creation of cis isomers provides a slight hypsochromic or blue shift
of 3 to 5 nm, affecting mainly the color of the product. This can decrease the pro-
vitamin A activity of the products (Xiao et al., 2018).
2.2. Lipid carriers
Lipids are prime nutrients widely applied in foods such as confections,
butter/spreads, salad dressings, and ice creams. Physical, biotechnological, chemical,
and biochemical techniques have been invented to modify lipids, thus coping with the
present diversification of market demands within the lipids industry (Damodaran et al.,
2007). Among these diversifications, different practices such as replacement of
saturated fatty acids with alternatives, reduction of trans-fatty acids, and improvement
17
of functionality of the end products have been widely used (Kabeva et al., 2017;
Wilczek et al., 2017; Bai et al., 2020b). Lipid contributes different physicochemical,
tribological and mechanical attributes to end products; these attributes include
glossiness, melting, texture, lubrication, friction, and spreadability (Guichard et al.,
2018; Tan et al., 2019).
Nowadays, the demand for food is not only limited to good sensory, tribological
and satiety value but also more about a balance between these attributes with additional
health implications. Thus, consumers are expecting food with multifunctional or
nutraceutical ingredients besides essential nutrients. Foods with these multifunctional
or nutraceutical ingredients are recognized as a functional food, which provides
additional health benefits besides the nutritional values (Singh et al., 2018; Banerjee et
al., 2019). In a functional food system, nano/micronization of multifunctional or
nutraceutical ingredients with a compatible polymer or carrier/encapsulating materials
is considered an ideal tool to improve its functionality and health benefits (Ko et al.,
2017; Da Silva et al., 2020).
The Definition of the nanomaterials/nanoparticles are commonly described as
"the understanding and monitoring the properties of materials at the nanoscale, which
ranged from 1 to 100 nm” (Khan et al., 2019; Wang et al., 2019). At the nano
dimension, the physicochemical properties such as color, solubility, reactivity, texture
and toxicity of the particle vary, and in turn, so do the functional applications (Hydbring
and Du, 2019; Khan et al., 2019; Wang et al., 2019). On the other hand, microparticles
range from 1 to 1000 µm and have a relatively lesser influence on the physicochemical
properties (Lengyel et al., 2019). The particle size of matrices/ingredients plays a key
18
role in designing and developing desirable functional foods, nutraceuticals, and
medicines. The size-dependent application primarily includes enhanced bioavailability
of bioactive compounds, efficient and targeted delivery, and increased solubility
(McClements, 2015; McClements, 2018; Lengyel et al., 2019).
Lipid’s biocompatibility and versatility traits have extensively led to several nano
and microparticulate preparations in the past two decades. There are many merits
portrayed by lipid nano/microparticles over the polymeric nanoparticles in delivering
drugs and other bioactive compounds, hence they have a widespread application
(Tamjidi et al., 2013). Lipid nano/microparticle’s biocompatibility appears better than
that of the polymeric nanoparticles since they consist of lipids that have a similarity to
their physiological counterparts (McClements, 2018). Lipid particles or lipid carriers
are nano/micro-sized lipids particles or droplets and are an ideal carrier for labile
multifunctional and nutraceutical ingredients. Lipid carriers are categorized into two
groups: solid lipid nanoparticles (SLN) and nano-lipid carriers (NLC) (Beloqui et al.,
2016). Nano-lipid carriers are considered more pertinent in delivering nutraceuticals
than SLN due to higher loading capacity, faster release, and less expulsion capacity of
NLC. The most common types of NLC are nanoemulsion, microemulsion and liposome
(Beloqui et al., 2016; Khosa et al., 2018; Nahr et al., 2018).
2.2.1. Oil-in-water (O/W) emulsion: preparation and physicochemical stability
A wide range of food products that consumers use in daily life is produced from
different immiscible phases, for example, a mixture of oil and water in salad dressing
or mayonnaise. Consequently, the droplets of one liquid phase tend to be dispersed into
the other, creating an emulsion (Gupta et al., 2016). There are two major categories of
19
emulsions: first, oil-in-water (O/W) emulsions, which involves dispersing of oil
droplets into a continuous phase, and second, water-in-oil (W/O) emulsion, which
involves dispersion of water droplets into an ongoing oil phase (Yang et al., 2017). In
our food system, O/W type emulsions are found in milk, salad dressings, mayonnaise,
ice-cream, and yogurt; however, a W/O type emulsion is found in butter, and
margarine. A triple-phase emulsion can also be created by mixing oil-in-water-oil
(O/W/O) or water-oil-water (W/O/W) emulsions. Triple-phase emulsions are generally
used in drug delivery (Tamjidi et al., 2013).
The utilization of O/W emulsion-based delivery systems in functional foods has
been extensively explored (Siro et al., 2008; Sharif and Zahid, 2018) because an O/W
emulsion is an ideal tool for the encapsulation of lipophilic micronutrients, protecting
them against degradation during processing, storage, and consumption. The preparation
of O/W emulsions, which is available commercially, can be done by applying low
energy and high-energy methods. Low-energy approaches require an input energy
density of 103-105 W kg-1; however, high-energy approaches utilize an input energy
density of about 108-1010 W kg-1 (Gupta et al., 2016). Low-energy approaches include
emulsion inversion or phase inversion method and input energy is not induced by any
mechanical means other than the chemical activity of the components. A low-energy
approach allows a narrower size distribution of the resulting emulsion. On the other
hand, a high-energy approach utilizes energy input from mechanical devices such as
microfluidizer, high-pressure homogenizer, or high shear blender. High-energy
approach method results in wider size distribution of the oil droplets. However, due to
higher emulsion production efficiency and scalability, the high-energy method is most
20
commercially applicable (Yang et al., 2012; Liu et al., 2020). High-energy methods
also help in retaining the rheological attributes of emulsions and a higher concentration
of dissolved nutraceuticals; however, the emulsion is diluted gradually, resulting in
thinner emulsions with a lower nutraceutical concentration (Yang et al., 2012; Gupta
et al., Liu et al., 2020). In high-energy methods, two steps are carried out separately by
using a microfluidizer or high-pressure homogenizer. The first step involves a higher-
shear blend to create a coarse emulsion by mixing up water, oil, and emulsifier. The
second step consists of an action where the emulsion is forced through the
microfluidizer (Silva et al., 2012). The micro-fluidization pressure facilitates the
determination of the oil droplet size, emulsifier concentration, and emulsion stability.
Nevertheless, it is worth noting that the system has to be fed with sufficient emulsifiers
that should be rapidly adsorbing to the oil droplet surfaces and stabilizing them against
the aggregation (Al-Bukhaitia et al., 2018).
Since the O/W emulsion system consists of an oil-water interface, it is associated
with positive free energy and is thus regarded as thermodynamically unstable. On this
account, oil droplets tend to break down over time; therefore, reducing the contact area
between both phases. This reduced contact results in separation of the oil phase from
the aqueous phase over time (Vignati et al., 2003; Marquez et al., 2018). Additionally,
oxidation of fatty acids and hydrolysis of the ester bond of the triglycerides results in
the leakage of loaded nutraceuticals and poor solubility in the digestion media, thus
reducing the bioaccessibility of loaded/dissolved nutraceuticals (McClements, 2015;
Da Silva et al., 2020; Hu et al., 2020). An emulsion’s physiochemical instability is
usually identified as a kinetically unstable system when there is a continuous
21
breakdown over a period because of the destabilization of chemical stability and other
physical mechanisms like gravitational separation, coalescence, and flocculation (Silva
et al., 2012; Berton-Carabin, and Schroen, 2015). Gravitational separation occurs
because of contrasting relative densities between the dispersed and the continuous
phases leading to creaming or sedimentation. The other physical mechanisms involve
droplet aggregation like flocculation or coalescence and appear to be minimally
encountered in nanoemulsions since the droplet particles are relatively small
(Dickinson, 2012; Whitby et al., 2011). Colloidal interactivity relates to droplets’ size
and is due to attractive interactions (hydrophobic and van der Waals) and the repulsive
interactions (electrostatic and stearic) between adjacent droplets (Dickson, 2012).
2.2.2. Stabilization of O/W emulsion
Several synthetic and natural polymers can be used to create an interfacial
hindrance among oil droplets/particles, which can create a thermodynamically stable
emulsion, and the polymers are known as emulsifiers. Emulsifiers are required to
adsorb on the interface of the oil droplet to generate strong repulsive forces, thus
preventing the droplets from coalescing. These repulsive forces can be either
electrostatic or steric (Bai et al., 2020a). Various emulsifiers, such as protein isolates,
starch, gum arabic, PEG, Tween-80®, glucan, and maltodextrin, have commonly been
applied in the food industry for the formation and stabilization of emulsions (Silva et
al., 2012; Da Silva et al., 2020). In the past few decades, consumers have been much
more informed about food consumption-related matters and how healthy lifestyles can
be enhanced. Thus, market demands shift towards healthy and low-calorie foods
because of increased public health concerns have captured researchers’ attention in
22
designing and developing nutraceuticals and functional foods (Siro et al., 2008; Sharif
and Zahid, 2018). Without a doubt, consumers opt for products that are natively
obtained from their natural sources instead of synthetic products (Roman et al., 2017;
Saleh et al., 2019).
2.2.3. Pickering emulsion
Considerable investigations have been carried out on the development of
nutraceuticals and functional foods through Pickering emulsions and liposome
technology (Siro et al., 2008; Sharif and Zahid, 2018). In the present, much interest has
been directed towards utilizing particle-based stabilizers to create and stabilize
emulsions. Nevertheless, over a century ago, there was a realization of emulsion
stabilization using the small solid particles through the Pickering stabilization process
(Pickering, 1907). These colloidal particles used in Pickering emulsions demand
balanced interfacial wettability, hence presenting affinity for both phases.
Consequently, droplets coated with particles tend to exhibit more stability to droplet
coalescence than ones coated with molecular-based emulsifiers due to the higher steric
repulsion and irreversible adsorption (Vignati et al., 2003). The electrical charge
density of these particles depends on the method of preparation, such as acid hydrolysis
or application of post-treatment, which increases the electrical density (Rayner et al.,
2014).
Pickering emulsions can be economically suitable for commercial applications.
In general, O/W Pickering emulsions have soundly been applied in various food-related
emulsion systems like antibacterial emulsions, coloring and flavoring agents, and
delivery of nutraceuticals (Silva et al., 2012; Berton-Carabin, and Schroen, 2015; Khan
23
et al., 2018). Flavors and coloring compounds used in food consist of esters, aldehydes,
and ketones acting as functional groups that expose them to oxidative and photolytic
degradation. Prevention of such harmful impacts can be done by the encapsulation
process of emulsions within these ingredients to enhance the shelf life (Berton-Carabin,
and Schroen, 2015). With widespread adoption and application of emulsions in the
food, nutraceutical, pharmaceuticals and packaging industries, the sustainability of the
emulsification process and its physicochemical suitability for the targeted product, is
one of the most important aspect to be addressed (Calabrese et al., 2018; Sarkar and
Dickinson, 2020).
There is an increased interest in investigating particle-based stabilizers in the
production of Pickering emulsions and modulate their digestion (Dai et al., 2018; Fu et
al., 2019). Research has been done to examine the impacts of naturally derived particle
stabilizers, cellulose nanocrystals (CNC), to establish a wide range of applications in
food emulsion (Bai et al., 2020a; Bai et al., 2020b). Researchers have investigated the
stabilization capacity of CNC for the O/W type emulsions and reported a significant
stabilization activity (Bai et al., 2018; Wu et al., 2020). However, the critical element
in applications of CNC-stabilized Pickering emulsions involves storage instability. The
phase separation of droplet coalescence (gravitational separation) can be of great
importance in systems containing large oil droplets and smaller colloid particles (Bai
et al., 2020a). Exceptionally, the O/W emulsions containing CNC can also lead to a
separation of the oil phase when diluted. This can be due to the following reasons: (a)
desorption of the polymer from the oil droplet interface reducing steric or electrostatic
repulsion among droplets, (b) weaker gel strength of the aqueous medium, thereby
24
increasing droplets’ interaction, thus coalescence/Ostwald ripening, and (c) reduced
surface pressure on the oil droplets due to decreased salt concentration hence
depletion/desorption of adsorbed polymers (Wooster, 2006; Maphosa and Jideani,
2018; Bai et al., 2020a).
2.2.4. O/W emulsion and modified CNC
As stated earlier that, bio-based derived nanomaterials are in the process of being
investigated for their applications in foods to advance quality and as well to facilitate
the functionality due to the abundant primary and secondary hydroxyls. The presence
of these hydroxyls on the surface can easily be modified with other polymers to create
the desired surface property. Surface modification can also produce other cellulose
derivatives or else through grafting to various substances (Tao et al., 2020). Different
studies have also indicated that the modification of CNC formed a stable O/W
emulsion. The amphiphilic nature is considered as the main driving force for the
stabilization of emulsion using the modified CNC. The amphiphilic behavior leads to
suggestions that all CNC surfaces consist of dual traits- the hydrophilic and the
lipophilic. (Cagnasso et al., 2010; Li and Woodle, 2018). Surface modifications of the
CNC mainly focus on achieving enhanced emulsion stability, where such studies have
been focusing on the surface hydroxyl unit modifications (Cagnasso et al., 2010; Li et
al., 2020). CNC is known to be an easily- modified substance to produce several
derivatives and impart physiochemical characteristics like stiffness, transparency,
lower density, and induction of tunable surface chemistry (Saidane et al., 2016;
Natterodt et al., 2017). These developments include the application of modified CNC
as a drug carrier, composites, and emulsifier/stabilizer for the Pickering emulsifiers. In
25
essence, the discovery of new and practical approaches in producing stable Pickering
emulsions using the unmodified CNC in emulsion systems containing low oil
concentration remains the main challenge due to the hydrophilic nature of unmodified
CNC (Cheng et al., 2015). CNC exhibit an abundance state of functional moieties like
the aldehyde and the active hydroxyl units, thus, ensuring that they can be modified to
enable control over their properties, physical and chemical is essential. Modified CNC
can achieve the anisotropy since they can comfortably take advantage of these aldehyde
units attached in the ends of the molecules, thus facilitating the selective modification
of the CNC (Saidane et al., 2016). Researchers' interest has significantly been directed
towards selective modification of CNC to prepare functional CNC with unique features
(Heise et al., 2019; Tao et al., 2020). However, the chemical modification process'
sustainability is a big concern; moreover, it is also a complex process, which requires
a variety of non-food grade chemicals and reagents.
2.2.5. Liposomes and stability
Liposomes are spherical vesicles that form with the hydration of surfactants like
phospholipids after being mixed with water under low shear forces. Ideally, the
liposome technique is used to encapsulate and stabilize hydrophilic compounds
(Kopechek et al., 2008; Aditya et al., 2017). Typically, it consists of a bilayer of
phospholipids that are self-assembled due to attractive forces associated with the long
hydrophobic chains of the fatty acids (Bally et al., 2010). The liposomes prepared
through the phospholipid method possess the zwitterionic property (Yadav et al., 2011).
Despite consisting of positively charged choline groups, liposomes prepared with
26
phospholipids show moderate anionic surface property due to the presence of
phosphate group (Yoshikawa et al., 2016).
Liposomes enhance the stability of the hydrophilic nutraceuticals during oral
delivery; thus, the increased bioaccessibility and bioavailability in the body is achieved
(Couvreur et al., 2001; Eloy et al., 2014). Although liposomes possess few
physiochemical limitations such as 1) progressive coalescence due to the presence of
Van-der-Waals attractions leading to the formation of giant liposomes; thus, leakage of
the loaded compound (Tan et al., 2016; Haider et al., 2017); and 2) chemical and
enzymatic hydrolysis of phospholipid ester of fatty acids of liposome bilayers (Peng et
al., 2018; Peng et al., 2019). Developments are made to ensure that physiochemical
stability of liposome using polyethylene glycol (PEG), chitosan, and other synthetic
and natural polymers (Panja et al., 2019; Sopyan and Gozali, 2020). Previous studies
report that a significant improvement in the physicochemical stability of liposomes
during storage prepared with chemically modified phospholipids with PEG and
cholesterol (Kono et al., 2018; Shen et al., 2018; Zalipsky, 2018). The chemical
modification increases the puncture resistance behavior of the phospholipid bilayers by
providing a stronger lipophilic-lipophilic interaction between tail groups of fatty acids
and the lipophobic-lipophobic interaction between the inner head group (Yadav et al.,
2011; Sopyan et al., 2020). Since the chemical modification of phospholipids limits the
application of the liposome system in food due to being extremely expensive, chemical
residue from the modification process and feasibility. Thus, researchers have made an
effort to explore some alternative greener, cheap and feasible additives to ensure the
stability of the liposomes. In recent studies conducted by Lee et al. (2020) have
27
investigated the effect of fortification of stigmasterol (a sterol) on the stability of
phospholipid bilayer, found enhanced physicochemical stability of the liposomes, thus
enhanced stability of the loaded vitamin C. In another conducted by Panja et al. (2019)
reported the enhanced stability of liposome stabilized with casein protein. Utilization
of a hydrophilic colloid particle can be a good choice as a stabilizing material since it
can easily be adsorbed onto the interface of the liposome due to Van-der-Waals of
attraction (Liu et al., 2013).
2.3. Cellulose
Cellulose is the most abundant polymer found on the planet Earth, is the most
significant structural component in plants (Kargarzadeh et al., 2018). Cellulose is found
in the cell walls of plants, bacterial pellicles, and even in algae. Cellulose is responsible
for the rigidity, firmness, and shape of the cells (García et al., 2016). Cellulose was
discovered in 1838 by Anselme Payen, a French chemist. Payen isolated cellulose from
plant matter and discovered its chemical structure and formula. Cellulose is a
homopolysaccharide consists of D-glucose units linked through β-(1 → 4) glycosidic
bonds forming linear structures. Cellulose is a complex organic compound chemically
identified with the formula (C6H10O5)n thus, classified as polysaccharides, which are
linearly aligned into chains and closely packed, causing rigidity. Below is the equation
that describes the formation of cellulose (García et al., 2016):
n(C6 H12 O6 ) → (C6 H10 O5)n + nH2O
(Glucose) (Cellulose)
28
Figure 2.1 illustrates the hierarchical structure of cellulose from wood to its
monomeric unit. In their native state, cellulose parallel chains that are closely packed
with multiple hydrogen bonds, giving rise to long fibers, also known as microfibrils.
Microfibrils have a width of 4 -10 nm and tend not to dissolve in water and are
relatively inert. The microfibrils are characterized by crystalline (highly ordered) and
amorphous regions (less ordered) (Kargarzadeh et al., 2018). The estimated degree of
polymerization of naturally existing cellulose is approximately 10000 to 15000
Fig. 2.1. Hierarchical structure of cellulose from wood to a monomeric unit.
repeating units of two anhydroglucose rings, so the molecules have a high molecular
weight (Moon et al., 2011; Kargarzadeh et al., 2018). Macrofibrils can be formed by
further aggregation of microfibrils with the lignin and hemicelluloses present in plant
tissue. Due to a high degree of cellulose bonding, microfibrils and macrofibrils produce
tall, high tensile strength structures that are generally insoluble in several solvents
29
(Moon et al., 2011; Kargarzadeh et al., 2018). The cellulose content in both softwoods
and hardwoods is approximately 42% (Rowell et al., 2012).
2.3.1. Cellulose nanomaterials
Cellulose nanomaterials are structures, platelet-like particles, or fibers that are
modified substances manufactured at nanoscales (Moon et al., 2011; Kargarzadeh et
al., 2018). The primary objective for developing these materials is to produce unusual
functionalities such as conductivity and increased chemical reactivity compared to
similar material not at the nanoscale level (Kargarzadeh et al., 2018; Kasiri and Fathi,
2018). Typically, these nano substances provide some unique advantages such as a
larger surface area to volume ratio, compatibility with nanoformulations, homogeneity,
better dispersion property, and hydroxyl groups (O-H) as a functional group
(Brinkmann et al., 2016). Cellulose nanomaterials naturally occur with unique
structural properties, mechanical and also the optical traits. The surface chemistry of
cellulose nanomaterials plays an essential role in determining particle interactions with
the environment, dispersion control in solvents, and agglomeration (Brinkmann et al.,
2016). Primarily, Cellulose nanomaterials can be grouped into two; the nanoobjects
and nanostructures. Cellulose nanoobjects consist of cellulose nanocrystals (CNC) and
cellulose nanofibers (CNFs) (Grishkewich et al., 2017).
There are two major approaches for fragmentation of cellulose source material
during its refinement process into nano-sized structures: mechanical shear and acid
hydrolysis (Kargarzadeh et al., 2018). The mechanical refinement process involves the
application of high shear to tear off the cellulose source material apart. This technique
produces the cellulose nanofibrils (CNF) or microfibrillated cellulose (MFC)
30
structures. On the other hand, production of cellulose nanocrystals (CNC) is done by
several methods such as acid hydrolysis (Kargarzadeh et al., 2018), acid-alkali
hydrolysis (Jordan et al., 2019) enzymatic hydrolysis (Hayashi et al., 2005; Peciulyte
et al., 2015), and the metal salt catalyzed hydrolysis process (Kamireddy et al., 2013;
Yahya et al., 2015). The hydrolysis conditions are primarily the determinant of CNC
surface chemistry, charge, and as well the aspect ratio, which is a ratio of sizes in
different dimensions of CNC (Brinkmann et al., 2016).
2.3.2. Application of Cellulose nanomaterials
Cellulose nanomaterials have potential applications in different areas of food,
biomedical, packaging, textile, construction industry due to its aforesaid unique
physicochemical properties (Habibi et al., 2010; Grishkewich et al., 2017; Tang et al.,
2017; Amalraj et al., 2019). Food science researchers have investigated the application
of cellulose nanomaterials as a fat replacer, thickener, food package, and food gel
(Amalraj et al., 2019; Bai et al., 2020b; Dai et al., 2020). Cellulose nanomaterials also
have shown the characteristic of dietary fibers in the rat (Yan et al., 2018).
Microorganisms present in the digestive system’s large intestine can partly degrade
cellulose to produce organic acids and gasses (Flint et al., 2012). Thus, as dietary fiber
cellulose possesses an ability to absorb moisture inside the intestinal tract, thus easy
defecation and prevention of constipation (Ekvall, 2017; Lever et al., 2019).
Technology has led to a new application of cellulose nanomaterials in foods
ranged from coatings directly on fruit surfaces to applying as an emulsifier/stabilizer
for lipid droplets and fat reducer (Hedjazi and Razavi, 2018; Aswathanarayan and
Vittal, 2019). Recent reviews demonstrate an advantage of Cellulose nanomaterials
31
when applied to fruit pre-harvest to curb skin cracking caused by excess rain, extending
the shelf-life, and preserving the nutrients and nutraceuticals (Hubbe et al., 2017; Jung
et al., 2020). The reduced environmental toxicities of cellulose nanomaterials,
particularly the CNF, may in the future favor food applications (Hedjazi and Razavi,
2018; Aswathanarayan and Vittal, 2019).
Cellulose nanomaterials also have a significant impact on biomedical
applications, mainly when used as a binder, due to their biocompatibility, low levels of
cytotoxicity, tissue-friendliness, wound healing aspects, antimicrobial effects, and
biodegradability (Amalraj et al., 2018; Kargarzadeh et al., 2018). In addition, cellulose
nanomaterials have the property of potential binding to tissues through the presence of
O-H groups and negative interfacial charges that promote the cellulose nanomaterial’s
electrostatic adsorption onto the tissue. Cellulose nanomaterial’s medical applications
are widely studied concerning the delivery of drugs, tissue healing, tissue repair, and
tissue replacement cases, and medical implants (Hosseinidoust et al., 2015). Cellulose
nanomaterials have primarily been used in the dressing of the wounds due to its anti-
infection characteristic and the ability to increase tensile properties associated with the
tissue scaffolds. Adding CNC to collagen-based composite raises the levels of its
biocompatibility and stabilizes its mechanical functionality. Moreover, a study
demonstrated that the addition of CNC to poly [D, L-lactic-co-glycolic acid] (PLGA)
produced a more robust composite, enhancing thermal, mechanical stability and
facilitated cytocompatibility, spreadability, fibroblast adhesion, and proliferation as
compared to neat poly [D, L-lactic-co-glycolic acid] (Mo et al., 2015). CNF is also
applicable in the biomedical field by using them for filaments (threads) formation.
32
Coating the CNF filaments with stem cells can produce sutures that positively influence
post-surgery inflammation and wound healing. Hakkarainen et al. (2016) conducted a
clinical study investigating CNF’s application in the dressing of wounds, particularly
for severely burned patients. There was a successful grafting within the skin donor sites
consequent to cellulose dehydration. Cellulose nanomaterials have also been effective
in bone generation.
The study has shown that the modification of surface charge on the CNC can be
useful in delivering small interfering RNA, which tend to have therapeutic effects.
RNA in their naked form cannot be delivered to the disease cell and can degrade
quickly; therefore, it is advisable to employ a nanocarrier such as CNC since CNC is
non-toxic, biodegradable, easily available, and a nano-biopolymer (Kargarzadeh et al.,
2018) that facilitates the therapeutic actions through binding RNA (Kim et al., 2020).
A study by Plackett et al. (2014) also reports that CNF and CNC could readily bind
with water-soluble drugs when applied in drug delivery functions.
2.3.3. Cellulose nanocrystals (CNC)
CNC is also identified as crystalline nanocellulose or cellulose nanowhisker
(Kargarzadeh et al., 2018), which is a tiny needle or rod-like structure produced from
cellulose. Due to CNC’s unique features, researchers have recommended it for potential
use in foods, nutraceuticals, drugs, and other applications (Cherhal et al., 2016; Hedjazi
& Razavi, 2018; Bai et al., 2020a; Bai et al., 2020b). CNC derived from wood pulp
have a diameter of 5-15 nm with a length of 150-200 nm (Grishkewich et al., 2017;
Tang et al., 2017). CNC accounts for up to 99% of the crystallinity in its structure
compared to other cellulose nanomaterials that account for a maximum of 70%
33
(Abiaziem et al., 2019). CNC is a nano dimension structure with surface hydroxyl
groups (O-H) (Natterodt et al., 2017). CNC has excellent dispersibility in aqueous
media (Cheng et al., 2015), contains a high charge potential due to sulfate ions (-SO3-)
(Prathapan et al., 2016), and is a non-toxic biopolymer (Natterodt et al., 2017;
Kargarzadeh et al., 2018). These characteristics establish CNC as a better platform for
developing functional foods (Bai et al., 2018; Dai et al., 2020).
CNC has been considerably utilized in stabilizing O/W emulsion and has shown
significant (p≤0.05) effect in retaining physical and morphological attributes of the
lipid droplets (Angkuratipakorn et al., 2017; Bai et al., 2018, Bai et al., 2020b; Dai et
al., 2020). The stabilization of lipid droplets via CNC is due to the electrical screening
behavior of added salt (NaCl). NaCl in the CNC stabilized emulsion improves the rate
of adsorption of CNC on oil droplets' interface due to increased surface pressure
(Bergfreund & Fischer, 2019; Bertsch et al., 2019). It has been reported that the
addition of salt to the O/W Pickering emulsion also increases the CNC-CNC
interactions resulting in increased gel strength of the aqueous phase, which limits the
motion and interfacial interaction of the oil droplets, thus stable emulsion (Bai et al.,
2018). However, the stability of these emulsion types can be compromised when
diluted or the addition of opposite ions (Wooster, 2006; Maphosa and Jideani, 2018).
Dilution leads to a segregative separation of oil phase due to the following reasons: (a)
detachment of the polymer from the oil droplet interface, reducing the steric or
electrostatic repulsion; (b) weaker gel strength of the aqueous medium, thus increased
droplets interaction consequently coalescence/Ostwald ripening and (c) reduced
surface pressure on the oil droplets due to decreased salt concentration resulting in
34
detachment of adsorbed polymer (Wooster, 2006; Maphosa and Jideani, 2018; Bai et
al., 2019a).
CNC modified with hydrophobic or amphiphilic molecules have significantly
improved the physical stability of the O/W emulsion (Saidane et al., 2016; Natterodt et
al., 2017; Li et al., 2020; Tao et al., 2020). The modified CNC helped in creating a
structure that is stable to dilution, ionic stress, and pH due to its compatible
hydrophobic-hydrophobic interaction between oil and CNC interface (Saidane et al.,
2016; Tang et al., 2018; Le et al., 2020). However, the modification process's
sustainability and utilization of several non-food grade chemicals and reagents are a
major concern and may preclude their use in food.
35
CHAPTER 3
STERIC STABILIZATION OF PHYCOBILIPROTEIN LOADED
LIPOSOMES THROUGH POLYETHYLENE GLYCOL ADSORBED
CELLULOSE NANOCRYSTALS AND THEIR IMPACT ON THE
GASTROINTESTINAL TRACT
3.1. Introduction
Recent advances in the nutraceutical, cosmeceutical and pharmaceutical sciences
support the concept that bioactive phytochemicals extracted from plants and seaweeds
can help in the reduction of some of the human chronic diseases (Kuć, 2007;
Manirafasha et al., 2016).
Phycobiliproteins (PBP) are common light-harvesting protein found in brown/red
seaweeds, including dulse and several other marine algae and have potential effects in
reducing human diseases such as anti-inflammatory, hepatoprotective, anti-aging and
angiotensin (Riss et al., 2007; Furuta et al., 2016). However, PBP is embedded into the
cell wall of the seaweed forming a conjugate complex with a broad range of
polysaccharides. Due to lack of site-specific enzymes, this protein-polysaccharide
conjugate complex limits PBP extractability and digestibility into the human
gastrointestinal tract (GIT) and consequently hinders its applications (Mæhre et al.,
2016). Further, the stability of PBP is greatly affected by light, pH, oxidative stress,
irradiation, and temperature (Munier et al., 2014). For example, Rastogi et al. (2015)
reported that the concentration of PBP extracted from marine cyanobacterium
Phormidium sp. decreased significantly when the extract was exposed to above 40 °C,
at a pH below 4.0 & above 8.0, and oxidative stress above 0.8%. Few other studies
36
have investigated the stabilization of extracted PBP with different encapsulating
materials, such as pH-regulated multilayered polyelectrolytes and sol-gel glass
mediated encapsulation (Chen et al., 1996; Li et al., 2012). However, there is a limited
study on the fate and stability of PBP through various pH in human GIT. The stomach
stage of GIT system has a most noticeable effect on the quality attributes on the
bioactive food compounds due to its very low pH (2.0 to 3.0), however, the mouth and
small intestine phases of the GIT have less significant effects (McClements, 2015; Xiao
et al. .2017; Winuprasith et al., 2018). To protect the bioactive compounds from lower
pH of the GIT and safely deliver into the small intestine and subsequent absorption into
epithelial cell, oil-in-water (O/W) based delivery systems have been often tested using
liposomes (Dhakane et al., 2017; Woodle et al., 2018; Zaborova et al., 2018).
Liposome-based delivery systems for hydrophilic and hydrophobic compounds
improve the solubility and controlled release (Cagnasso et al., 2010; McClements,
2015; Woodle et al., 2018). However, preparation temperature, particle size, and
method of preparation cause changes in the arrangement of the phospholipid bilayer
within the liposomes. This affects the loosely packed head groups in the inner layer,
and tightly packed alkyl chains in the outer layer of the bilayer and leads to physical
instability, such as agglomeration or fusion of the liposomes (Kamatsu et al., 2001;
Yadav et al., 2011). Similarly, pH, ionic strength and oxidative effects can hydrolyze
the ester linkage between fatty acids & phosphocholine glycerol, cause peroxidation of
long-chain fatty acids and consequently lead to the formation of acetaldehyde (Yadav
et al., 2011; Guldiken et al., 2018). To reduce these effects, a suitable coating material
could be identified and used for encapsulation. A few studies have been investigated to
37
understand the physicochemical interaction between cellulose nanomaterials with
liposomes (Kresse et al., 2016; Navon et al., 2017; Lombardo and Thielemans, 2018).
Few researchers have investigated cellulose nanomaterials as a stabilizer for an oil-
based delivery system (Angkuratipakorn et al., 2017; Guo et al., 2017; Kasiri and Fathi,
2018; Li et al., 2018). Studies reported that the cellulose nanomaterials stabilize
Pickering emulsion and retain the desired quality attributes. Further, Winuprasith et al.
(2018) investigated the effect of different ratios of CNF (0.1 – 0.7 %) on the stability
and digestibility of Pickering emulsion under in vitro simulated GIT conditions and
reported that the increase in the concentration of CNFs increased the stability of the
emulsion, which reversibly limited the digestibility. Findings concluded that the CNFs
could stabilize the oil droplet due to its bulky molecular chain-like structure and large
average particle size (>100 nm diameter to several µm in length) while limiting the
lipase activity by keeping them away from lipid droplets. (Winuprasith et al., 2018).
Since CNC is tiny, rod-like particles with dimensions of approximately 5 nanometers
(nm) in diameter and 150-200 nm in length (Cheng et al., 2015), it can be a better
stabilizer for O/W based delivery system. However, the dispersibility of cellulose
nanomaterials into the aqueous medium is limited due to its irreversible agglomeration
through surface hydrogen bonding. Adsorption of polyethylene glycol (PEG) via
hydrogen bonding onto the surface of CNC could be a suitable way to reduce
irreversible agglomerations (Yang et al., 2013; Cheng et al., 2015) through coating the
free surface hydroxyl groups (O-H).
Understanding the surface and colloidal properties of CNC and phycobiliprotein,
we hypothesize that the cellulose nanocrystals can be adsorbed with polyethylene
38
glycol to stabilize phycobiliprotein for better delivery of the compounds in the human
gastrointestinal tract. The objectives of this study were (i) to stabilize cellulose
nanocrystals (CNC) by adsorption of different molecular weight of polyethylene glycol
(PEG) and (ii) to understand the physicochemical behavior of phycobiliprotein loaded
liposome stabilized through PEG adsorbed CNC during simulated gastrointestinal tract
condition (GIT). Subsequent characterization includes particle size, zeta potential,
stability PEG adsorbed CNC, the stability of PBPs loaded liposome, hydrolysis of the
liposome, and release of PBP.
3.2. Materials and Methods
3.2.1. Chemicals and reagents
Dulse (Palmaria palmata) was purchased from Maine Sea Farm, Franklin, Maine,
United States. Sulfuric acid hydrolyzed cellulose nanocrystals (CNC: contained up to
2% sulfate ion (O-SO3-), 11.5-12.5% solid, 5-20 nm wide and 150-200 nm long) was
procured from the Process Development Center, University of Maine. PEG with
different molecular weights, 400-4000 g/mol, xylanase (≥2500 units/g), α-amylase
(Aspergillus oryzae) pepsin from porcine gastric mucosa (~2500 units/mg), lipase type
II from porcine pancreas, mucin-type III from the porcine stomach, bile extracts
porcine, uric acid ≥99% crystalline, phospholipid (soy lecithin), cellulose membrane
dialysis tube (43 mm in diameter), maxi dialysis tube (3 mL capacity) with molecular
cut-off 12-14 kDa, HDPE 20 μm porosity bed supports column with a dimension of 2.5
x 170 cm (volume capacity 230 mL) and Sephadex G-100 were purchased from Sigma-
Aldrich, USA. Phospholipid containing 17-24% phosphatidylinositol, 6% phosphatidic
39
acid, 18% phosphatidylethanolamine and 35% phosphatidylcholine and other
analytical grades chemical & reagents were purchased from Fisher Scientific Products,
USA.
3.2.2. Purification and characterization of phycobiliproteins
The extraction of PBP was performed following the procedure of Dumey et al.
(2013) with some modifications. Briefly, 20 g of dried dulse was placed into 500 mL
of acetate buffer (50 mM @ 5.0 pH) and 0.33 g of xylanase enzyme (16.5g/kg of the
sample, ≥2500 units/g) was added. The reaction mixture was stirred at 200 rpm for 3
hours at the incubation temperature of 40°C. After hydrolysis, the reaction mixture was
centrifuged 21,800x g for 20 minutes at 4 °C using a super speed centrifuge (Beckman
Coulter Avanti J-E Floor, CA, USA). The supernatant was collected and subsequently
dialyzed against distilled water for 12 hours at 4 °C using a 12-14 KDa dialysis tube
with intermittent replacement of distilled water to remove the soluble salts, minerals,
and carbohydrates. Dialyzed samples were further purified using size exclusion column
containing Sephadex G-100 as a stationary bed medium (Fig. 3.1). Purified fraction
was freeze-dried (SP Scientific 2000 Virtis 35EL, Freeze Dryer, USA) at -40 °C under
a vacuum of 250 millitorrs for three days in the absence of light and the dried PBP was
stored in a deep freezer (-20 °C) for further experimental investigations.
40
Fig. 3.1. Size exclusion-based column separation of phycobiliproteins.
3.2.3. Quantification of phycobiliproteins
Total PBP in the purified extract was analyzed following the method of Rastogi
et al. (2015). In brief, 200 µL of purified PBP was loaded in multi plate reader UV-Vis
spectrophotometer (BioTek Eon, Vermont, U.S.A) and the absorbance was measured
over 250–750 nm range. The equations of Bennett and Bogorad (1973) were used to
calculate the amount of PBP:
𝑃𝐶 (𝑚𝑔 𝑚𝐿−1) = [𝐴615 − 0.474 (𝐴652)]/5.34
𝐴𝑃𝐶 (𝑚𝑔 𝑚𝐿−1) = [𝐴652 − 0.208 (𝐴615)]/5.09
𝑃𝐸 (𝑚𝑔 𝑚𝐿−1) = [𝐴562 − 2.41 (𝑃𝐶) − 0.849 (𝐴𝑃𝐶)]/9.62
41
𝑃𝐵𝑃 (𝑚𝑔 𝑚𝐿−1) = 𝑃𝐶 + 𝐴𝑃𝐶 + 𝑃𝐸
where PC is phycocyanin, APC is allophycocyanin, PE is phycoerythrin, A is the
absorbance at a given wavelength.
3.2.4. Gel electrophoresis analysis of phycobiliproteins
The extracted PBP was analyzed for its molecular analysis using sodium
dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Sample was
prepared according to the method of Lasekan and Nayak (2016). PBP was diluted with
Laemmli buffer (1:1) containing 5% of 2-mercaptoethanol. Diluted PBP was
immediately heated at 100 ºC for 5 minutes. After cooling at room temperature for 20
minutes 7.5 µL sample was loaded into 12% precast gel cassette (Mini-Protean TGX
Precast Gel, Bio-Rad, Hercules, CA., USA). The electrophoretic separation was then
performed at 170 V into Mini-Protean Tetra Tank (Bio-Rad, Hercules, CA., USA).
After 10 minutes of the electrophoresis period, the gel cassette was removed from the
tank and the cassette was gently removed from the gel. The obtained gel was then
washed with distilled water gently followed by staining into 50 mL of GelCode Blue
Stain Reagent (Pierce Biotechnology Inc, Rockford, IL, USA). Macroscopic visuals of
the separated protein bands were recorded, and the molecular weights of each band
were compared with the marker named Precision Plus Protein Dual Color Standard
(Lasekan and Nayak, 2016).
42
3.2.5. Adsorption of PEG with CNC
The CNC produced through sulfuric acid hydrolysis contained ~2% of sulfate
ions (OSO3-). Studies show that more active sites on the surface of CNC can be created
through the desulfation of sulfate ions (Yang et al., 2013 and Cheng et al., 2015). CNC
was desulfated to remove the sulfonates from the CNC surface using 0.85 mM NaOH.
Desulfated CNC (coded as DCs) were dialyzed against distilled water for two days and
then freeze-dried (SP Scientific 2000 Virtis 35EL, Freeze Dryer, USA) for further PEG
adsorption. PEG adsorption onto the desulfated CNC was performed following the
procedure of Cheng et al. (2015) with slight modification. Briefly, freeze-dried
desulfated CNC (3 g) was placed into a 250 mL Erlenmeyer flask and distilled water
was added to make a concentration of 3% DCs. The mixture was stirred at 1200 rpm
for 5 minutes followed by ultrasonication at 500 watts for 5 minutes using ultrasonic
dismembrator (Fisherbrand, Ultrasonic Liquide Processor, USA). Then, 3.33 g of PEG
was added into the flask with continuous stirring at 200 rpm for 3 hours at room
temperature. The reaction was subsequently dialyzed for three days against distilled
water through a 12-14 KDa molecular weight cutoff dialysis tube. Dialyzed sample was
then freeze-dried (SP Scientific 2000 Virtis 35EL, Freeze Dryer, USA) and coded as
desulfated PEG adsorbed CNC (DPCs).
3.2.6. Preparation and stabilization of phycobiliproteins loaded liposomes
The PBP was extracted and purified using the method optimized by Dumay et
al. (2013). Purified PBP was freeze-dried using a freeze dryer (SP Scientific 2000 Virtis
35EL, Freeze Dryer, USA) and stored in a deep freezer. The liposomes were prepared
43
according to the method described by Gao et al., (2013) with slight adjustment. In brief,
600 mg of purified soy lecithin was dissolved into 200 mL of ethyl acetate and
chloroform (60:40) solution. The solution was subsequently passed through a 0.22 µm
filter paper to remove undissolved lecithin or any foreign particles, followed by rotary
evaporation and thin layer formation in the round bottom flask. The flask with a thin
layer of lecithin was placed under a vacuum dryer at room temperature overnight to
remove any traces of solvent. To encapsulate the purified PBP, the thin layer was
further rehydrated with PBP solution (300 mg/50 mL) followed by the addition of 100
mL of phosphate buffer saline (7.4 pH). The resulting multilamellar liposomes were
sonicated for 1.2 minutes at 40% amplitude (at the interval of 15 seconds ON and 5
seconds OFF-pulse time) using an ultrasonic dismembrator (Fisherbrand, Ultrasonic
Liquid Processor, USA) to obtain unilamellar vesicle (SUV) liposomes. This liposome
was coded as phycobiliprotein loaded liposome (PL). Loaded liposome was
subsequently stabilized by the addition of 100 mL suspension/solution (1% w/v) of
desulfated cellulose nanocrystals (DCs), or polyethylene glycol (PEG-400-4000 g/mol)
or polyethylene glycol adsorbed onto cellulose nanocrystals (DCs-2000 or DCs-4000).
These stabilized liposomes are coded as PLDCs, PLP-2000, PLP-4000, PLDCs-2000
and PLDCs-4000. Stabilized liposomes were dialyzed in the absence of illumination
over 48 hours at 4 ℃ using 50 kDa cellulose dialysis tubing against distilled water to
remove the excess PBP.
3.2.7. In vitro gastrointestinal tract (GIT) study
The stability of liposome and PBP during GIT study was investigated following an in
vitro GIT model proposed by Winuprasith et al. (2018) with slight adjustments. The
44
simulated digestion media were prepared for the in vitro study are given in Table 3.1.
Briefly, 100 mL volumetric flask (quantity 24) was washed properly with distilled
water, dried under vacuum and wrapped with an aluminum sheet to avoid light
degradation of PBP during the study. Initially, 40 mL of PBP loaded stabilized
liposomes was preheated in a shaking water bath (JULABO, SW22, Julabo Inc., USA)
at 37 °C for 2 minutes with a shaking speed of 100 rpm and was considered as initial
sample of the GIT study. After minutes, 20 mL aliquot was transferred into the next
flask for further GIT phase (mouth phase - SSJ) study. SSJ (20 mL) added to the
reaction mixture previously, was incubated at 37 °C and adjusted to a pH of 6.8 using
0.5M NaOH/HCl solution. The reaction was allowed to occur for 5 minutes with
continuous stirring at 100 rpm at 37 °C. The gastric phase investigation was performed
by transferring 20 mL of SSJ phase sample into the next 100 mL volumetric flask.
Twenty mL of gastric juice (SGJ) was added into a flask and pH was maintained at 2.0
using 0.5M HCl. The mixture was then incubated for 2 hours at 37 °C with continuous
stirring at 100 rpm. After completion of the SGJ phase, pH was neutralized using 0.5
M NaOH solution. The small-intestinal (SIJ) phase was performed by transferring 20
mL aliquot of the SGJ phase sample into the next 100 mL volumetric flask and adding
1.5 mL SIJ (CaCl2+NaCl solution) followed by 3.5 mL of bile salt and 2.5 mL of lipase
solution. The reaction mixture was maintained at pH 7.0 and incubated at 37 °C with
stirring at 100 rpm for 2 hours of the reaction period.
The sample fractions of each GIT phases were collected separately and stored
under refrigeration condition until qualitative and quantitative characterizations.
However, particle size and the zeta-potential study were performed immediately.
45
Table 3.1. Compositions of chemicals for preparation of simulated gastrointestinal
tract (GIT) medium for in vitro study.
Chemical
name Quantity Vol. (mL) pH
Initial Na2HPO4
NaH2PO4
10.11 g
1.70 g 500 6.8 ± 0.2
Simulated saliva
juice (SSJ):
Mouth phase
KCl
KSCN
NaH2PO4
NaSO4
NaCl
NaHCO3
Urea
Uric acid
Mucin
α-amylase
4.48 g
1.00 g
4.44 g
2.87 g
8.77 g
8.47 g
1.00 g
75 mg
25 mg
290 mg
500 6.8 ± 0.2
Simulated gastric
juice (SGJ):
Stomach phase
HCl
NaCl
Pepsin
3.5 mL
1.00 g
1.60 g
500 2.0 ± 0.2
Simulated
intestinal juice
(SIJ): Small
intestine phase
CaCl2
NaCl
1.39 g
10.95 g 50
7.0 ± 0.2 Bile salt 250 mg 50
Lipase 80 mg 50
Note: All prepared chemicals and reagents were prepared freshly and incubated at 37
°C prior in vitro study.
46
3.2.8. Determination of particle size and zeta potential
The samples collected from different GIT phases were further diluted using a
phosphate buffer (6.8 pH) to standardize for CNC-loaded PBP concentration. Particle
size and ζ-potential were performed on a zeta-sizer (Zetasizer Malvern 3000 HSA).
Means and standard deviations of ten automatic replications (by instrument) of each
sample (triplicate of each sample) were recorded. Similarly, the particle size and ζ-
potential of fresh DPCs sample were performed by dispersing 0.2 g of sample into 10
mL of distilled water by stirring at 100 rpm for 5 minutes.
3.2.9. Spectrofluorometer analysis of phycobiliproteins
Effects of the GIT phase on the stability of PBP, particularly fluorescence
intensity was recorded using a spectrofluorometer (Jobin Yvon Fluorolog-3-21). 5 mL
of samples from the GIT phases were mixed with 500 µL of a 100 mM Tween-20
solution and were vortexed for the 2 minutes followed by centrifugation at 4,550x g for
10 minutes on a rotor centrifuge (Beckman Coulter Avanti J-E Floor, CA, USA). The
fluorescence intensity of the collected supernatant was measured using a
spectrofluorometer (Jobin Yvon Fluorolog-3-21). Excitation and emission spectra of
545 nm 575 nm of the PBP were used to record the fluorescence intensity (Lage-Yusty,
et al., 2013; Caracciolo, 2015).
3.2.10. FTIR analysis
Infrared spectroscopic analysis of the samples was recorded on an FTIR
spectrometer (ABB FTLA 2000). The samples (fresh and GIT) were placed onto the
top of a crystal diamond and spectra were recorded between the wavelengths of interest
47
ranging from 400 to 4000 cm-1. The results were recorded in percent transmittance
(%T). Obtained FTIR %T was then converted to the absorbance following the equation
developed by Toft et al. (1993).
𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 = 2 − 𝑙𝑜𝑔 (%𝑇)
The adsorption of PEG onto the desulfated CNC surface was confirmed by exposing
freeze-dried desulfated CNC and DPCs samples through this analysis. Similarly, PBP
loaded liposome, liposomes stabilized by desulfated CNC and DPCs samples were
directly exposed for FTIR analysis. An additional FTIR analysis was performed to
understand the desorption behavior of PEG from the surface of CNC under the SGJ
phase. The samples collected from the SGJ phase were dialyzed through a 3 mL maxi
dialysis tube for 24 hours to remove the desorbed PEG, followed by freeze-drying (SP
Scientific 2000 Virtis 35EL, Freeze Dryer, USA). However, to study the liposomes
digestion during the GIT phase, only SIJ phase samples were exposed for FTIR analysis
(to find a trend in the total digestion throughout the GIT phase). To extract undigested
liposomes and free fatty acids, 5 mL of samples collected from the SIJ phase were
mixed with 2 mL of ethyl acetate: chloroform solution (60:40). Samples were vortexed
for 2 min and allowed for phase separation. After a clear phase separation of the upper
ethyl acetate, the chloroform layer was collected gently with a 5 mL syringe. The lower
portion was again subjected to the same solvent separation process. Collected upper
layer samples were pooled and evaporated under vacuum and investigated for FTIR
characterization.
48
3.2.11. Confocal laser scanning microscopy
The stability and coalescence behavior of stabilized liposomes under the GIT
phase was performed on a Leica TCS SP laser scanning confocal microscope (LSCM).
50 µL of samples were loaded on a microscope slide and gently covered with a
coverslip. A fluorescence characteristic of PBP (phycoerythrin) excitation at 545 nm
and emission at 575 nm was used. A 100X magnification lens was used to acquire
LSCM results with a specimen scanning depth of 1.5 µm.
3.2.12. Statistical analysis
The experiments for the particle size, zeta potential, and PBP release were
performed in triplicate. One-way ANOVA was applied to determine the significant
effect at the level of p≤0.05, while the Tukey’s honestly significant difference (HSD)
post hoc test was performed to identify the significant differences between the means
of the characteristic parameters at different GIT phases.
3.3. Results and Discussion
3.3.1. Phycobiliproteins content in the extract
The macroscopic image of the purified PBP is given in Fig. 3.2. PBP in the extract
accounted for 1.36 mg/mL for the extract without enzymatic hydrolysis; however,
14.99 mg/mL was obtained for the extract assisted with xylanases enzymatic
hydrolysis. The major PBP in the extract was phycoerythrin (PE) followed by
allophycocyanin (APC) and phycocyanin (PC) (Table 3.2).
49
Table 3.2. PBP contents (mg/mL) of Palmaria palmata (Dulse)
PE PC APC Total PBP
Fresh 0.74±0.07 0.30±0.02 0.32±0.02 1.36
Hydrolyzed 9.55±0.35 2.19±0.07 3.25±0.15 14.99
Note: Results are the mean ± standard deviation of triplicate for each sample (n=3). PE:
phycoerythrin, PC: phycocyanin and APC: allophycocyanin.
Fig. 3.2. Macroscopic images of purified PBP (A) and freeze-dried PBP (B).
3.3.2. Gel electrophoresis of purified phycobiliproteins
SDS-PAGE analysis of extracted PBP from the dulse revealed that there three
bands, which comprised at 16-18 kDa of alpha and beta subunit of phycoerythrin and
at 34 kDa of the gamma subunit of phycoerythrin. Furuta et al. (2016) reported that the
molecular weight of the phycoerythrin extracted from the dulse molecular weight
around 20 kDa (Fig. 3.3).
A B
50
Fig 3.3. SDS-PAGE of phycobiliproteins. Molecular weight marker is in far left.
3.3.3. Adsorption of PEG with CNC
A schematic diagram of adsorption of polyethylene glycol (PEG) onto the
desulfated CNC (DCs) surface with an O-H bond is given in Fig. 3.4a. From the FTIR
spectra in the range of 2800 to 2900 cm-1, the C-H stretching of the alkane group of
PEG showed the most noticeable differences between DCs and PEG adsorbed DCs
(DPCs). DPCs with a higher molecular weight of PEG had higher C-H stretching
vibration, which could be due to the long-chain length of the higher molecular weight
of PEG. Similar to the C-H stretching vibration of the alkane group, characteristic peaks
of PEG adsorption were C-H scissoring and bending vibration of alkane between 1290
to 1440 cm-1, C-O stretching vibration of an alcohol group at 1245 cm-1, C-O-C peak
of ether group between 1190 to 987 cm-1 and a characteristic peak of PEG crystallinity
at 834 cm-1 (Sun, Zhang, & Chu, 2008). These characteristics peak of the PEG in the
DPCs sample confirmed the successful adsorption of PEG on the surface of DCs (Fig.
3.4b).
51
Fig. 3.4. Schematic of polyethylene glycol adsorption (a) and FTIR spectra (b).
Note: Desulfated CNC (DCs) Polyethylene glycol (PEG) of different molecular
weight viz., 400, 600, 1000, 1500 and 4000 g/mol, PED adsorbed desulfated CNC
(DPCs)
3.3.4. Effect of PEG’s molecular weight on average particle size and zeta potential
of desulfated cellulose nanocrystals (DCs)
The particle sizes of DCs and PEG adsorbed DCs (DPCs) samples were analyzed
to understand the effect of different molecular weights of PEG adsorption on the
stability of DCs in an aqueous medium. An average particle size (APS) and zeta
potential of DCs and DPCs are given in Fig. 3.5. Purchased CNC contained an initial
average particle size of 150-200 nm; however, DCs displayed an average particle size
of 6922.3 nm. The results implied that the desulfation might reduce the electrostatic
repulsion among CNC by removing the negatively charged sulfate ions (Yang et al.,
2013). The desulfation may lead to the formation of CNC intermolecular O-H bridge
causing CNC to agglomerate (Habibi, Lucia, & Rojas, 2010 and Cheng et al., 2015).
Adsorption of PEG had an effect on the re-dispersion of DCs as well. The average
a b
52
Fig. 3.5. The average particle size of PEG-modified CNC
Note: Desulfated CNC (DCs) and PEG (molecular weight 400, 600, 1000, 1500 and
4000 g/mol) adsorbed DCs (DPCs) (a). Zeta potential (b). DCs*10 represents the
particle size (nm) is 10 times higher for DCs sample. Different letters above columns
indicate significant differences (Tukey’s HSD, p≤0.05).
a
bb c c,d c
0
100
200
300
400
500
600
700
800
DCs*10 DPCs-400 DPCs-600 DPCs-1000 DPCs-1500 DPCs-4000
Part
icle
siz
e (n
m)
Sample type
aa
a
b b
c
-30
-25
-20
-15
-10
-5
0DCs DPCs-400 DPCs-600 DPCs-1000 DPCs-1500 DPCs-4000
Zet
a p
ote
nti
al
(mV
)
Sample type
a
b
53
particle size of DPCs samples was much lower (≤ 244.64 nm) than the DCs (6922.3
nm). From our observation, the adsorption of PEG on the surface of DCs might
interfere with intermolecular attraction among DCs (Yadav et al., 2011; Guo, Xie, &
Luo, 2013). This adsorption of PEG onto DC’s may create a steric hindrance causing
significant redispersion of desulfated CNC (Cheng et al., 2015). It was also observed
that the adsorption of polyethylene glycol at the higher MW decrease in the average
particle size ranging from 244.64 nm to 198.53 nm. This trend could be due to the
longer chain length of higher MW PEG, which may result in more surface steric
hindrances and subsequently limit the formation of O-H bond during the drying process
(Cheng et al., 2015). Desulfated CNC had a total surface charge of -21.74 mV, which
implies that the surface charge was adequate to create a temporary electrostatic
stabilization (Clogston and Patri, 2011).
However, results from the particle size depicted that the particles were not
stable. It is assumed that the agglomeration might be due to the higher forces of
attractions between surface O-H groups as compared to electrostatic repulsive force
(Yadav et al., 2011 and Guo et al., 2013). Adsorption of lower MW PEG (400 and 600
g/mol) resulted in an insignificant (p>0.05) change in the zeta potential value.
However, desulfated CNC adsorbed with higher MW of PEG (1000, 1500 and 4000
g/mol) decreased the zeta potential value slightly, which might be attributed to the
surface coating of desulfated CNC by a long chain of higher MW of polyethylene
glycol (Chibowski & Paszkiewicz, 1999). Despite the slight decrease in zeta potential
from -21.74 to -15.44 mV with an increase in the MW of PEG, stabilization of CNC
54
was noticed. The stability of CNC implied that the particles were stabilized through
steric hindrance rather than electrostatic stabilization in the aqueous medium.
3.3.5. Effect of gastrointestinal tract (GIT) phases on quality characteristics of
phycobiliprotein (PBP) loaded liposomes
Liposomes are commonly used in pharmaceutical, cosmeceutical and
nutraceutical industries as loading materials/carriers for hydrophilic and hydrophobic
bioactive compounds. However, its physical and chemical stability under different
environmental conditions is a concern. Various studies have been conducted so far to
stabilize the liposomes (Parise et al., 2015; Mahmud, Piwoni, Filiczak, Janicka, &
Gubernator, 2016; Jang et al., 2018 and Raja et al., 2018). PBPs loaded small
unilamellar vesicle liposome contains an average particle size of 319±78.61 nm and
average zeta potential of -31±8.82 mV. To understand the physicochemical stability of
liposomes, we investigated the agglomeration behavior and enzymatic digestibility of
PBP loaded liposome under the GIT phase, the effect of the GIT phase on the particle
size, zeta potential, and liposomes digestion and release behavior of PBP’s were
investigated and illustrated in the following sub-headings.
3.3.5.1. Effect on average particle size
The average particle size (APS) of the samples was investigated under different
GIT phases. PBP loaded liposomes stabilized with Desulfated CNC and DPCs into
phosphate buffer (pH 6.8) was considered as an initial phase. From Fig. 3.6, it was
observed that the sample stabilized with desulfated CNC had a much higher value of
the average particle size (5392.6 nm) as compared to the samples stabilized with
55
Fig. 3.6. Effect of the GIT phases on the average particle size of samples.
Note: Desulfated CNC (DCs), PEG adsorbed DCs (DPCs). DCs*10 = values are ten
times higher for DCs sample under however, SGJ*10 and SIJ*10 represent the values
are ten times higher for all samples in gastric (SGJ) and intestinal phase (SIJ). The
upper-case letters denote the significant difference (p ≤0.05) among sample types;
however, small letters denote significant differences (p≤0.05) among gastrointestinal
phases.
different DPCs (DPCs 400 – 4000: 308.72 to 207.33 nm). Two possible reasons were
presumed for these findings: first, it could be due to the poor re-dispersible and
agglomeration of desulfated CNC as described in section 3.2, and second, the
coalescence of liposomes due to the absence of steric hindrance among intermolecular
of liposomes (Yadav et al., 2011). The confocal laser scanning microscopy (CLSM)
images of the initial samples (Fig. 3.7) showed that liposomes were stabilized by
different DPCs, which supports the earlier statement that the DPCs may create the steric
hindrance among liposomes and thereby stabilize liposomes. The effect of simulated
saliva juice (SSJ) phase onto the average particle size of samples was insignificant (p
Aa
Ab
Ab Ab Ab
Ba
Ba Ba
Bb
Ab
Ba
Ba Ba
BbBb
Ba
Ca Ca
Cb
Cc
BaCa Ca
Cb
Cc
Ba Ca Ca
Cb
Cc
0
100
200
300
400
500
600
700
800
PEG-DCs Initial SSJ SGJ*10 SIJ*10
Part
icle
siz
e (n
m)
Treatments
DCs*10 DPCs-400 DPCs-600DPCs-1000 DPCs-1500 DPCs-4000
56
> 0.05), except the sample stabilized through desulfated CNC. It was noticed that the
average particle size of the desulfated CNC stabilized sample increased from 5392.6 to
6042.5 nm after exposure to SSJ phase (Fig. 3.6). It was inferred that as time passed,
due to no stabilization effect (DCs was precipitated), the continuous coalescence of
liposomes occurred with the progression of the GIT phase that causes an increase in
the average particle size. The confocal microscopic images also confirmed an increase
in the liposome’s particle size (Fig. 3.7), which may be due to a continuous coalescence
of liposomes by the Van-der-Waals forces of attraction (Yadav et al., 2011 and Guo et
al., 2013). The confocal microscopic images of the samples stabilized through DPCs
showed good stability of liposomes under the saliva phase (SSJ) of the GIT. It was
presumed that the stability of liposomes might be due to the steric behavior of DPCs,
preventing the coalescence of liposomes (Yadav et al., 2011). It was observed that the
average particle size of the sample increased up to 10 times higher than its SSJ phase
except the sample stabilized through DCs (Fig. 3.6). The average particle size of
desulfated CNC sample was increased slightly from 6042.5 to 6193.5 nm, which may
be due to the further coalescence of liposomes during the gastric phase of GIT.
However, the average particle size of DPCs samples increased to a maximum value of
5526 nm for DPCs-400 followed by 5487 nm (DPCs-600), 4308 nm (DPCs-1000),
4182 nm (DPCs-1500) and 3718 nm (DPCs-4000). These findings could have
happened due to the following reasons. Firstly, the instability of O-H bond between
desulfated CNC and polyethylene glycol at lower pH (Habibi et al., 2010; Way et al.,
2012 and Yang et al., 2013) causing desorption of polyethylene glycol followed by
57
Fig. 3.7. Confocal laser scanning microscopic images of stabilized liposomes.
Note: Images are the effect of gastrointestinal tract (GIT) phase on the physical stability
of stabilized liposomes, where desulfated CNC is DCs, PEG (400-4000 g/mol)
adsorbed DCs is DPCs. Scale bars for the size of the liposomes are 1.0 µm. SSJ –
simulated saliva juice, SGJ – simulated gastric juice, SIJ – simulated small-intestinal
juice.
58
agglomeration of desulfated CNC. Secondly, the coalescence of liposomes is due to its
physical instability (Yadav et al., 2011).
Besides, the confocal microscopic images also support the findings for an
increase in average particle size (Fig. 3.7). The FTIR analysis of the gastric juice (SGJ)
samples confirmed the desorption of PEG from the surface of the desulfated CNC. As
it can be seen from Fig. 3.8 (FTIR spectra) the characteristics peak of the PEG (C-H
stretching vibration alkane between 2800 to 2900 cm-1; C-H scissoring and bending of
alkanes between 1290 to 1440 cm-1, C-O stretching of an alcohol group at 1245 of, C-
O-C peak of ether group between 1120 to 1010 cm-1 and a characteristic peak of
crystallinity at 834 cm-1) of higher molecular weight of polyethylene glycols have
disappeared. It was observed that the average particle size of lower molecular weight
of polyethylene glycol’s samples (DPCs-400 and DPCs-600) increased more
significantly (p≤0.05) than the DPCs-1000, DPCs-1500, and DPCs-4000, which was
confirmed due to the anti-coalescence effect of longer chain length of higher MW PEG
remaining in solution (Fig. 3.7). The results were in agreement with the finding of
Allen, Hansen, Martin, Redemann, and Yau- Young (1991), who observed that the
liposomes stabilized under the higher molecular weight of polyethylene glycol from
1900 to 5000 g/mol were more stable than the liposomes stabilized under the lower
molecular weight of polyethylene glycol 120 to 750 g/mol. A similar observation of
the long chain of polyethylene glycol due to the entangling effect on the stability of
liposomes was also reported by Hashizaki et al. (2003).
59
Fig. 3.8. FTIR spectra of CNC before and after the gastric phase of gastrointestinal
tract.
Note: PEG (molecular weights 400, 600, 1000, 1500 and 4000 g/mol) adsorbed
desulfated CNC (DPCs) before (a) and after gastric (SGJ) phase (b). Highlighted
spectra depict the adsorption of PEG adsorbed with DCs.
After exposing the samples into the next GIT phase, the small-intestine phase
(SIJ), the average particle size of the samples significantly increased with respect to
SGJ phase results. It was hypothesized that the increase might be due to a reduction in
the number of lower particle size liposomes via lipase hydrolysis (Cheng et al., 2017;
Winuprasith et al., 2018). Similar to the SGJ phase, the desulfated CNC stabilized
sample had larger average particle size compared to DPCs stabilized samples. Confocal
microscopic images showed the cause of the increase in overall particle size with
respect to the SGJ phase. It can be seen from Fig. 3.7 that the desulfated CNC samples
have bigger liposomes that may have significantly contributed to the larger particle
size. However, DPCs samples with a higher molecular weight of polyethylene glycol
a b
60
even after desorption showed better stabilization of liposomes as compared to the DPCs
with lower MW of PEG, thus the average particle size compared to desulfated CNC.
3.3.5.2. Effect on zeta potential
The effect of an electrostatic behavior of the samples throughout the GIT phases
was recorded in the form of average zeta potential (AZP) (Fig. 3.9). It was also
confirmed that the desulfated CNC sample showed coalescence of liposomes even at
the initial phase (Fig. 3.7), which may have resulted in an increase in the size of the
liposomes and subsequently lowering the surface area and zeta potential (Sahu et al.,
2020). Saliva phase of GIT had a slight effect on the average zeta potential value of the
samples (Fig. 3.9), which could be due to the cationic (K+, P+, and Na+) and anionic
(mucin) compounds of saliva fluid (Pfeiffe et al., 2014 and Menchicchi et al., 2015)
influencing the anionic behavior of liposomes and desulfated CNC (Wang & Wang,
2008). A decrease in the zeta potential of vitamin D3 loaded emulsion due to
electrostatic screening effect caused by counter ions of the simulated saliva juice and
mucin after exposure in the mouth phase of GIT was reported by Winuprasith et al.
(2018). From Fig. 3.9, it was observed that the average zeta potential of the samples
increased after exposure to gastric juice (pH 2.0). An overall increase in the average
zeta potential that might be due to a strong anionic characteristic of phospholipid at a
lower pH (Pfeiffe et al., 2014). In contrast to the effect of GIT on the average particle
size. An increase in the molecular weight of polyethylene glycol had an increase in the
average zeta potential value. DPCs-400 and DPCs-600 displayed much lower average
particle size value, ranging from -38.2 to -40.64 mV compared to DPCs-1000 (-48.4
mV), DPCs-1500 (-53.63 mV) and DPCs-4000 (-64.38 mV). Following the
61
Fig. 3.9. Effect of gastrointestinal (GIT) phase on zeta-potential of samples.
Note: PBPs is phycobiiprotein, DCs is desulfated CNC, DPCs is PEG (molecular
weight 400, 600, 1000, 1500 and 4000 g/mol), SSJ is simulated saliva juice, SGJ is
simulated gastric juice, SIJ is simulated small-intestinal juice. The upper-case letters
denote the significant difference (p ≤ 0.05) among sample types; however, small letters
denote the significant differences (p≤ 0.05) among gastrointestinal phases.
antagonistic effect of SGJ phase on the average particle size (higher molecular weight
of PEG resulted in a decrease in particle size), it was inferred that lower average particle
size might have resulted in a higher surface charge. DPCs-4000 had the most significant
increase in the average zeta potential value (p≤0.05), which could be due to the
entangling effect of long-chain length of PEG-4000 that sterically hindered the
coalescence of liposomes after desorption fromdesulfated CNC (Fig. 3.7) (Allen et al.,
1991; Hashizaki et al., 2003). The desorption effect of the gastric phase (SGJ) also
exposed the desulfated CNC surface charge that might have contributed to increases in
the zeta potential (Cheng et al., 2015). The electrostatic behavior of samples under the
simulated intestinal phase (SIJ) displayed similar effects as resulted in the SGJ phase.
Aa
BaBa
Ba
Ba
Aa
BbBb
Cb
Bb
Aa
BbBb
Cb
Bb
Aa
BbBb
Dc
Cc
Aa
BbBb
Ed
Cc
Ab
BbBb
Fe
Dd
-70
-60
-50
-40
-30
-20
-10
0
PEG-DCs Initial SSJ SGJ SIJZ
eta p
ote
nti
al
(mV
)
Simulated GIT phase
DCs DPCs-400 DPCs-600
DPCs-1000 DPCs-1500 DPCs-4000
62
3.3.5.3. Stability of phycobiliproteins
The fluorescence intensity of the encapsulated PBP is given in Fig. 3.10. Results from
the figure depict the significant effect of the GIT phases on the fluorescence intensity
of the PBP. The most noticeable results were observed at the gastric phase, where the
liposomes stabilized with modified CNC (DPCs) had higher intensity as compared to
the liposomes with unmodified CNC (DCs). It was also noticed that the liposomes
stabilized by the modified CNC with higher molecular weights of PEG (DPCs-4000)
had higher fluorescence intensity, which was assumed due the physical stability of the
liposomes. The physically stable liposomes may have avoided the formation of giant
liposomes, thus less leakage of the loaded PBP and degradation, hence higher the
fluorescence intensity.
Fig. 3.10. Stability of PBP during gastrointestinal tract phases.
Note: Fluorescence intensity of PBP during gastrointestinal (GIT) phase. SSJ - saliva
juice, SGJ - gastric juice, SIJ - small-intestinal juice. De-sulfated CNC (DCs) and PEG
(400-4000 g/mol) adsorbed DCs (DPCs).
5
10
15
20
25
30
35
40
45
Initial SSJ SGJ SIJ
Flu
ore
scen
ce i
nte
snsi
ty (
CP
S)
Sample types
DCs
DPCs-400
DPCs-600
DPCs-1000
DPCs-1500
DPCs-4000
63
3.4. Conclusion
The simulated gastrointestinal tract (GIT) phase significantly affected the
stability of phycobiliprotein (PBP)-loaded liposomes stabilized through polyethylene
glycol (PEG) adsorbed cellulose nanocrystals (CNC). Before the GIT experiments, an
effort was made to re-disperse the freeze-dried desulfated cellulose nanocrystals (DCs)
into the aqueous medium through adsorption of different MW of PEG viz., 400, 600,
1000, 1500 and 4000 (coded as DPCs). The effect of the same GIT phase on the
characteristics of liposomes stabilized through desulfated CNC displayed an effective
coalescence of liposomes. Lower pH of the gastric phase caused effective desorption
of PEG from the surface of desulfated CNC, which resulted in precipitation of
desulfated CNC, thereby causing coalescence of liposomes. In summary, we concluded
that the adsorption of PEG on the desulfated CNC surface was appropriate to stabilize
PBP loaded liposomes initially and in the saliva environment. However, the desorbed
gastric condition led to an effective coalescence of PBPs loaded liposomes. It was
inferred from the investigation that further modification of CNC is needed for the
stabilization of phycobiliprotein during encapsulation.
64
CHAPTER 4
IMPROVED STABILITY OF PHYCOBILIPROTEIN WITHIN LIPOSOMES
STABILIZED BY POLYETHYLENE GLYCOL ADSORBED CELLULOSE
NANOCRYSTALS
4.1. Introduction
Phycobiliproteins (PBPs) are a class of proteins found in different macroalgae
(seaweed) microalgae and cyanobacteria. These proteins are colored and fluorescence,
and are subcategorized into three major groups of phycoerythrin, phycocyanin and
allophycocyanin. PBP's have been commercially distinguished as pharmaceuticals and
nutraceuticals for their potential application as anti-cancer, anti-cardiac, anti-aging,
anti-inflammation, neuroprotective and hepatoprotective agents in the food industry
(Riss et al., 2007; Futura et al., 2016; Lee et al., 2017). In seaweed, PBP is embedded
in the cell walls and bound to polysaccharides. Due to the conjugation with
polysaccharides, the extraction of PBP from seaweed is difficult. Moreover, the lack of
enzymes in the human digestion system for the specific type of polysaccharides in
seaweed, microalgae, and cyanobacteria also limits their digestibility, thereby limiting
the bioavailability of PBP (Dumey et al., 2013; Maehre et al., 2016; Martin).
Furthermore, the physicochemical stability of PBPs is strongly influenced by
several stress factors such as temperature, illumination, oxidative stress and
acidic/basic conditions (Munier et al., 2014; Rastogi et al., 2015). Studies show that
PBP's are unstable when exposed to temperatures above 40 °C, pH below 4.0 and above
8.0, resulting in the loss of 50 to 60% of phycobiliprotein (Rastogi et al., 2015).
Research also shows that exposure to the illumination, even at refrigeration at 4 °C for
65
a day, can significantly reduce the PBP content by 60%. On the other hand, exposure
to oxidative stress has comparatively less effect on PBP content, reducing to the amount
from 25 to 60% depending upon types of PBP (Liu et al., 2019; Munier et al., 2014). A
few studies have been conducted on encapsulating the PBP for control release and
targeted delivery (Chen et al., 1996; Hu et al., 2008; Manconia et al., 2009; Castangia
et al., 2016; Suzery et al., 2017). However, no studies have been reported regarding the
stabilization of PBP under the effects of different food processing and storage
parameters such as temperature, pH, illumination and oxidative stress. Li et al. (2012)
reported improved stability by incorporating the PBP within a polyelectrolyte
multilayered microcapsule. The study concluded that the microcapsule, however, a
further increase or decrease in the pH adversely affected the stability and encapsulation
efficacy. Yan et al. (2014) microencapsulated (1–3 mm capsule size) phycoerythrin
within alginate and chitosan as a carrier material using an extrusion process. Results
showed that a combination of alginate and chitosan (2.5 and 2.0%) significantly
retained the phycoerythrin content of up to 93% at 50 °C and up to 88% under
illumination for 40 days in storage. The ability to obtain good stability through the
effective distribution and dispersion of encapsulated bioactive compounds into
different food matrices, targeted delivery and control release into the human digestion
has resulted in major attention (Espitia et al., 2019; Guo et al., 2019)
Due to advancements in the science and technology of nanoencapsulation, this has
become a promising area of research to enhance the encapsulation efficiency, targeted
delivery and control release of encapsulated compounds (Aditya et al., 2017; Bai et al.,
2019b; Bao et al., 2019; Fu et al., 2019). Various nanoencapsulation techniques such
66
as molecular complex, ionic gelation, multiple emulsion, multiple layered emulsion,
biopolymer complex colloid systems and solid fat particle have been tested
(McClements, 2015; Dhakane et al., 2017). These encapsulation techniques have
several disadvantages, such as leakage of loaded materials, instability during ionic
reflux, agglomeration and precipitation at lower pH, limited loading capacity, less
bioavailability and production and handling cost.
Liposome encapsulation system, which provides higher loading capacity, superior
bioavailability and less production cost, offers a multifaceted application for
encapsulation of bioactive and unstable compounds (Couvreur et al., 2001;
McClements, 2015; Eloy et al., 2014). However, liposomes have a few
physicochemical limitations of 1) progressive coalescence due to the Van-der-Waals
attraction, which leads to the formation of giant liposomes, thereby leading to the
leakage of the loaded compound (Taylor et al., 2003; Laye et al., 2008; Haider et al.,
2017; Tan et al., 2016) and 2) hydrolysis of liposome structure, that depends upon the
composition of the phospholipid used in liposome preparation (Rasti et al., 2012;
Vafabakhsh et al., 2013; Peng et al., 2018; Peng et al., 2019). Stabilization of liposome
using polyethylene glycol (PEG), chitosan and other polymers either covalently or
noncovalently bound to the liposome have been reported, as they greatly improve the
physicochemical stability of the liposome during storage (Laye et al., 2008; Tan et al.,
2016; Kono et al., 2018; Shen et al., 2018; Zalipsky, 2018).
Nano biopolymers for the liposomes in encapsulation technology have attracted
many researcher's attention. Among them, cellulose nanocrystals (CNC) have been
investigated for the stabilization of drug-loaded liposomes due to its unique properties
67
such as their dimension (150–200 nm long and 5–15 nm wide) and non-toxicity
(Roman et al., 2009). As mentioned in chapter 3, it was found that the adsorption of
polyethylene glycol (PEG) on the surface of desulfated CNC (zeta potential −25 mV)
helped in the stabilization of phycobiliprotein loaded liposome at neutral pH.
Commercially produced CNC via sulfuric acid hydrolysis has a significant amount of
sulfate anions with a zeta potential of approximately −55 mV (Cheng et al., 2015).
Anionic property of the CNC and liposomes, anionic at neutral pH, creates a strong
electrostatic repulsion limiting the adsorption of CNC on the surface of liposomes
(Navon et al., 2017). Although a few researchers have reported the adsorption of similar
charged polymers and liposomes (Seki and Tirrell, 1984 and Liu et al., 2013), a reduced
electrostatic repulsion can also assist the adsorption of CNC on the surface of liposome
(Navon et al., 2017).
As reported in chapter 3, it was noticed that a reduced electric property of the
CNC-liposome system can cause the agglomeration or precipitation to the CNC and
then liposome. Therefore, a modification to the CNC was suggested. In addition to
surface modification, understanding of the effects of different environmental stressors
such as temperature, pH and illumination on the stability of liposome and the loaded
compound is critical. Thus, the present study was designed to investigate the effect of
pH viz., 1, 3, 5, 7, 9 and 11; temperature 4, 20, 40, 60, 80 and 100 °C and exposure to
illumination (4, 8, 14, 24, 48 and 72 h) on the stability of the PBP, and the physical
stability of liposome stabilized with polyethylene glycol adsorbed cellulose
nanocrystals. It was hypothesized that the high surface area and hydrophilic surface
properties of CNC could stabilize the PBP loaded liposome by creating steric
68
hindrance, preventing the leakage of the PBP. This study includes analysis of average
particle size, zeta potential, confocal laser scanning microscopic imaging of liposome
(to measure their physical stability), and the optical microscopic imaging of PEG
adsorbed cellulose nanocrystals (to measure dispersibility and agglomeration
behavior). Moreover, the release behavior of PBP from the liposome, total retained and
percent loss of loaded PBP during exposure to different stressors are measured.
4.2. Materials and Methods
Fresh dulse (Palmaria palmata) for the extraction of phycobiliprotein was
procured from Maine Fresh Sea Farms, Maine, USA. Cellulose nanocrystals
suspension (11.5-12.5% of total solid) with a dimension of 5-20 nm wide and 150-200
nm long was purchased from the Process Development Center of the University of
Maine. Polyethylene glycol of molecular weights viz., 1000, 2000, 4000 and 6000
g/mol, purified soy lecithin (>99%) containing 17-24% phosphatidylinositol, 6%
phosphatidic acid, 18% phosphatidylethanolamine and 35% phosphatidylcholine were
purchased from Fisher Scientific Products, USA. Cellulose dialysis tube MWCO 12-
14 kDa and 50 kDa, Sephadex G-100, HDPE column (2.5 x 170 cm) with a 20 μm
porosity bed support was purchased from Sigma-Aldrich, USA.
4.2.1. Adsorption of PEG with CNC
Polyethylene glycol of molecular weight 2000 and 4000 g/mol were adsorbed
onto desulfated cellulose nanocrystals (DCs) following the previous method described
in Chapter 3. Briefly, 3 percent of CNC suspension was placed into a 250 mL
Erlenmeyer flask and 3.33 g of PEG was added. The mixture was stirred at 200 rpm at
room temperature for 3 hours. The mixture was subsequently dialyzed for three days
69
against distilled water using a 14 KDa MW cutoff dialysis tube. Dialyzed CNC
containing adsorbed PEG of molecular weights 2000 and 4000 g/mole were freeze-
dried using a freeze dryer (SP Scientific 2000 Virtis 35EL, Freeze Dryer, USA) and are
coded as DCs-2000 and DCs-4000, respectively. CNC without PEG was labeled as
DCs. The zeta potential and size were measured using a Malvern 3000 Zetasizer HSA
and infrared spectra were recorded on an ABB FTLA 2000 FTIR as mentioned in
Chapter 3.
4.2.2. Encapsulation and stabilization of phycobiliproteins
The PBP was extracted and purified using the method optimized by Dumay et
al. (2013). Purified PBP was freeze-dried using a freeze dryer (SP Scientific 2000 Virtis
35EL, Freeze Dryer, USA) and stored in a deep freezer. The liposomes were prepared
according to the method described in chapter 3. In brief, 600 mg of purified soy lecithin
was dissolved into 200 mL of ethyl acetate and chloroform (60:40) solution. The
solution was subsequently passed through a 0.22 µm filter paper to remove undissolved
lecithin or any foreign particles, followed by rotary evaporation and thin layer
formation in the round bottom flask. The flask with a thin layer of lecithin was placed
under a vacuum dryer at room temperature overnight to remove any traces of solvent.
To encapsulate the purified PBP, the thin layer was further rehydrated with PBP
solution (300 mg/50 mL) followed by the addition of 100 mL of saline phosphate buffer
(7.4 pH). The resulting multilamellar liposomes were sonicated for 1.2 minutes at 40%
amplitude (at the interval of 15 seconds ON and 5 seconds OFF-pulse time) using an
ultrasonic dismembrator (Fisherbrand, Ultrasonic Liquid Processor, USA) to obtain
unilamellar vesicle (SUV) liposomes. This liposome was coded as phycobiliprotein
70
loaded liposome (PL). Loaded liposome was subsequently stabilized by the addition of
100 mL suspension/solution (1% w/v) of desulfated cellulose nanocrystals (DCs), or
polyethylene glycol (PEG-2000 or PEG-4000) or polyethylene glycol adsorbed onto
cellulose nanocrystals (DCs-2000 or DCs-4000). These stabilized liposomes are coded
as PLDCs, PLP-2000, PLP-4000, PLDCs-2000 and PLDCs-4000. Stabilized liposomes
were dialyzed in the absence of illumination over 48 hours at 4 ℃ using 50 kDa
cellulose dialysis tubing against distilled water to remove the excess PBP.
4.2.3. Encapsulation efficiency of phycobiliproteins
The encapsulation efficiency was determined by the addition of 500 µL of a 100
mM Tween-20 solution into 5 mL of the liposome dispersion followed by
centrifugation at 4,500x g for 10 minutes. The fluorescence spectrum of the supernatant
was measured on a spectrofluorometer (Jobin Yvon Fluorolog-3-21) using excitation
at 545 nm and emission at 575 nm (Lage-Yusty et al., 2013; Caracciolo, 2015). The
measured fluorescence was due to PBP encapsulated (within liposome) and PBP
adsorbed on the surface of the liposome (probably due to the protein corona mechanism
between the outer surface of the liposome and PBP) (Riviere et al., 2013). An estimate
of the fluorescence from the adsorbed PBP was determined by adsorption of PBP on
empty liposomes prepared using the same phospholipid layer rehydration method (see
chapter 3). Briefly, the dried phospholipid layer was rehydrated with 10 mL of
phosphate buffer followed by sonication. Additionally, the 5 mL of PBP solution (300
mg/50 mL) was added to the liposome dispersion. The mixture was allowed 3 hours at
4 ºC to adsorb the PBP on the outer surface of liposome with a gentle stirring speed of
100 rpm (Palchetti et al., 2016). Subsequently, the mixture was dialyzed against
71
distilled water over 48 hours at 4 ℃ using 50 kDa cellulose dialysis tubing to remove
the non-adsorbed PBP. 5 mL of PBP adsorbed liposome was then dissolved with 500
µL Tween-20 solutions (100 mM) followed by centrifugation at 4,500x g for 10
minutes. The fluorescence intensity of the supernatant was considered as the adsorbed
PBP. The following equation was used to determine the encapsulation efficiency.
𝐸𝑛𝑐𝑎𝑝𝑠𝑢𝑙𝑎𝑡𝑖𝑜𝑛 𝑒𝑓𝑓𝑖𝑐𝑖𝑒𝑛𝑐𝑦 (%) = 𝐴
𝐵 × 100
Where A is the fluorescence intensity of PBP within liposome and B is the fluorescence
intensity of total added PBP.
4.2.4. Stability analysis of phycobiliproteins
The stability of the encapsulated PBP was determined by exposing the liposomes
to different stressors such as pH, temperature and illumination, as described by Munier
et al. (2014) and Rastogi et al. (2015). For each experiment, a 100 mL of stabilized
PBP loaded liposome suspension was placed into 250 mL bottles (DURAN® PURE
bottles) and properly covered with aluminum foil.
A 100 mM solution of HCl and NaOH was used to maintain the pH of stabilized
liposome samples using phosphate buffer solution at 1, 3, 5, 7, 9 and 11. Treated
samples were placed into the refrigeration chamber at 4 ℃ for 60 minutes. The stability
toward temperature was determined by exposing the samples to different treatment
temperatures of 4, 20, 40, 60, 80 and 100 ℃ for 60 minutes at pH 7.0. The stability of
PBP toward illumination was evaluated in a 1.0-meter square cardboard box covered
with a black polyethylene sheet. The box was placed in a cooling chamber (4 to 7 ℃)
and a 3.5 W bulb (16.1 µmol m-2 s-1) was placed inside the top portion of the box.
72
Samples in 250 mL transparent bottles were placed into the center of the preinstalled
carton box and the illumination test was conducted for different time intervals of 4, 8,
14, 24, 48 and 72 hrs. The fluorescence spectra of the PBP samples were recorded on
a spectrofluorometer and the total loss of PBP was calculated using the following
equation:
𝐿𝑜𝑠𝑠 𝑜𝑓 𝑃𝐵𝑃 (%) = 100 − (𝐷
𝐸× 100)
where D is the fluorescence intensity of retained PBP during the process and E is the
initial fluorescence intensity of entrapped PBP.
4.2.5. Particle size and zeta potential analysis
Average liposome size and zeta potential of the samples were performed using
a Malvern Zetasizer 3000 HSA. Our preliminary investigation and observation on the
effects of temperature (4 – 100 °C) and illumination intensity (16.1 µmol m-2 s-1) did
not show any significant effect on the liposome size and zeta potential (preliminary
observation). However, adjusting pH did affect the average liposome size and zeta
potential. A 10 mL sample was taken into 25 mL of the test tube and different pH viz.,
1, 3, 5, 7, 9 and 11 was maintained for 60 minutes at 4 ℃. Afterward, samples were
immediately analyzed for average liposome size. A similar procedure was followed
separately for the investigation of the effect of pH on zeta potential.
4.2.6. Microscopic analysis
A 5 mL aliquot of each sample was taken into a 25 mL dark, amber-colored
Pyrex test tube and a pH of 1.0 was maintained using 0.1M HCl solution. After 60
minutes at pH 1.0, 50 µL of the sample was loaded on a separate glass slide and covered
73
with a thin glass coverslip and images were recorded on a laser scanning confocal
microscopy (Leica TCS SP instrument). An excitation and emission spectra of 545 and
575 nm was used for scanning using a 100X magnification lens.
An optical microscope (AmScope Polarized Light Microscope) was used to
measure the agglomeration behavior of desulfated CNC (DCs) adsorbed with
polyethylene glycol (DCs-2000 and DCs-4000) at different pH. A 10 mL sample of the
f PLDCs or PLDCs-2000 or DCs-4000 was placed into 25 mL test tubes. Subsequently,
the pH was adjusted using 100 mM solutions of HCl and NaOH. After 60 minutes of
storage at 4 ℃, 100 µL of the suspensions were placed onto glass slides and covered
with coverslips. Images were processed using a 20X magnification lens.
4.2.7. Statistical analysis
Data were collected in triplicate for the average liposome size, zeta potential,
and fluorescence intensities. The data were analyzed using SAS software version 9.4.
One-way ANOVA was used to determine the significant effect at the level of p≤0.05,
while the Tukey’s (HSD) post-hoc test was performed to identify the significant
differences among the means values.
4.3. Results and Discussion
4.3.1. Adsorption of polyethylene glycol with desulfated CNC
FTIR analysis revealed the successful adsorption of polyethylene glycol (PEG)
on the DCs (Fig. 4.1). Characteristic peak of the alkane group of PEG was recognized
between 2800-2900 cm-1, (stretching of C-H group) and between 1290-1440 cm-1
(scissoring and bending of C-H group). The peak at 1245 cm-1 was identified as the
74
stretching vibration C-O of alcohol group and between 1190 to 987 cm-1 as C-O-C
vibration of ether group. A characteristic peak of the crystallinity of PEG was
confirmed at 834 cm-1 (Sun, Zhang, & Chu, 2008).
Fig. 4.1. FTIR spectra of modified CNC.
Note: Highlighted peaks confirm the adsorption of polyethylene glycol (2000 and
4000) with desulfated cellulose nanocrystals (DCs).
4.3.2. Effect of pH on average particle size
The average size of the stabilized phycobiliprotein loaded liposome samples at
different pH is shown in Fig. 4.2. At neutral pH (7.0±0.05) the PL sample had an initial
average liposome size of 177±3 nm. A gradual decrease in the pH from 7.0 to 5.0, 3.0
and 1.0 resulted in a significant (p≤0.05) increase in the particle size of 424±3 nm,
1141±202 nm and 1306±80 nm, respectively. Stability of PBP loaded liposome at pH
75
7.0 may have been due to an anionic surface property of the of a phosphate group (zeta
potential: -34±3 mV) of a phospholipid, shows that charge stabilization does not lead
to the coalescing of the liposomes (see the section 4.3.3.). However, a decrease in the
pH to 3 led to protonation (H+) of an anionic phosphate group (PO4-3 to PO4) of the
liposome, causing a reduced zeta potential and hence to the coalescence of the
liposomes into larger aggregates (Aoki et al., 2015 and Chiang, Lyu, Wen, and Lo,
2018). Conversely, an increase in the pH of the liposome dispersion medium up to pH
9.0 had no significant effect (p>0.05) on the coalescence of the liposomes as the zeta
potential did not change. However, a further increase in the pH up to 11.0 led to a slight
increase (p≤0.05) in the average size from 177±3 nm to 200± 4 nm.
Control experiments were performed using liposomes containing adsorbed PEG
2000 and 4000 g/mol (PLP-2000 and PLP-4000) and compared to those liposomes
stabilized with CNC that contain the same adsorbed PEG (PLDCs-2000 and PLDCs-
4000). The average particle size PLP-2000 and PLP-4000 increased from 161±3 and
197±2 nm to 938±113 and 1024±45 nm, respectively, with a decrease in the pH from
7.0 to 1.0 (Fig. 4.2). In contrast, an increase in the pH from 7.0 to 11.0 resulted in a
minor increase in the particle size to 193±2 and 221±3 nm for PLP-2000 and PLP-
4000, respectively. Again, the coalescence at a pH of 1.0 is the result of lower zeta
potential and hence lower electrostatic stabilization of the system. No significant
(p>0.05) difference between the average particle size of the stabilized liposome with
polyethylene glycol 2000 and 4000 (2000 g/mol) was obtained at neutral pH (7.0±0.05)
(Fig. 4.2). The freeze-dried desulfated CNC (DCs) and desulfated CNC adsorbed with
polyethylene glycol 2000 and 4000 g/mol (DCs-2000 and DCs-4000)
76
Fig. 4.2. Effect of pH range on the average particle size of stabilized liposomes.
Note: Phycobiliprotein loaded liposomes (PL), PBP loaded liposome stabilized with
polyethylene glycol (PLP-2000 and PLP-4000), PBP loaded liposome stabilized with
desulfated cellulose nanocrystals (PLDCs) and desulfated cellulose nanocrystals
adsorbed with polyethylene glycol (PLDCs-2000 and PLDCs-4000). Capital letters
denote significant differences (p≤0.05) among samples and small letters denote
significant differences (p≤0.05) among pH. Error bars represent the standard deviation
of three independent experiments.
(without liposome) had an average particle size of 7304±639, 200±23 & 198±14 nm
and zeta potential value of -22±3, -16±1 & -15±3 mV at pH 7. A considerably larger
average particle size of 7304±639 for the desulfated CNC as compared to DCs-2000
and DCs-4000 (200±23 & 198±14 nm) was due to the irreversible agglomeration of a
surface hydroxyl group (O-H) of the CNC during the freeze-drying process (Cheng et
al., 2015). However, adsorption of polyethylene glycol on the surface of the desulfated
CNC led to steric stabilization of the CNC at a size of about 200 nm. (Cheng et al.,
2015). Both desulfated CNC and desulfated CNC containing adsorbed PEG (DCs-2000
Aa
Aa Aa
Ba
CaCa
Aa
Aa Aa
Ba
Cb
Cb
Ab Ab Ab
Bb
Cc
Cc
Ac Ac Ac
Bc
Cd CdAcAc
Ac
Bc
Cd Cd
Ad Ad Ad
Bd
Ce Ce
0
1500
3000
4500
6000
7500
9000
PL PLP-2000 PLP-4000 PLDCs PLDCs-2000 PLDCs-4000
Aver
age
part
icle
siz
e (n
m)
Sample types
pH 1.0 pH 3.0
pH 5.0 pH 7.0
pH 9.0 pH 11.0
77
and DCs-4000) were employed as a steric stabilizer for the PBP loaded liposome and
the effect of different pH was studied after 60 minutes after adjusting the pH. At pH
7.0, the liposomes containing adsorbed desulfated CNC (PLDCs) had approximately
thirty times higher average particle size (5505±1120) as compared to the PBP loaded
liposome (PL) and PBP loaded liposome stabilized with polyethylene glycol (PLP-
2000 and PLP-4000) (Fig. 4.2). This is attributed to the higher initial particle size
(7304±639 nm) of the freeze-dried desulfated CNC (DCs). Furthermore, a decrease in
the pH down to 1.0 led to an increase in the average particle size of the PLDCs from
5505±1120 nm to 7975±1273 nm and a charge reversal in zeta potential from -37±5 to
+15±2. The average particle size of the PBP loaded liposome stabilized by desulfated
CNC adsorbed with polyethylene glycol (PLDCs-2000 and PLDCs-4000) was
189.43±3.14 and 206.97±2.36 at pH 7.0. Results showed that the average particle size
of PLDCs-2000 and PLDCs-4000 samples were significantly different compared to the
particle size of the PBP loaded liposome (PL), PLP-2000 and PLP-4000. It was
observed that the average particle size of the PLDCs-2000 and PLDCs-4000 samples
increased significantly up to 2192.67±284.83 & 1959.50±201.73 nm at pH 5.0 and
3186.34±634.97 and 2728.10±618.63 nm at pH 3.0, followed by 6464.33±211.65 and
6698.55±317.53 nm at pH 1.0. It was assumed that the increase in the average particle
size might be due to the desorption of polyethylene glycol from the surface of
desulfated CNC at lower pH (see in chapter 3), that may have led to the agglomeration
of desulfated CNC (Fig 4.3). This may also have caused the coalescence of PBP loaded
liposome, thereby significant increase in the particle size. The following mechanisms
were hypothesized for the agglomeration and coalescence of the samples. First the
78
Fig. 4.3. Schematic illustration of behavior of liposomes and CNC at lower pH.
Note: desulfated cellulose nanocrystals (DCs) as an effect of lower pH ( ) and their
agglomeration. (A) Stabilized PBP loaded liposome, (B) molecular structure of
liposome (phosphatidylcholine) showing anionic phosphate group and cationic choline
group, (C) protonation (H+) of a phosphate group (PO4-) of the liposome, (D,E)
Agglomeration of liposome and DCs together due to entangling effect caused by the
addition of cationic liposome with anionic DCs due to ionic interaction, (E) protonation
(H+) of anionic surface group of DCs (SO4-) and agglomeration, (F) Protonation of an
anionic group of the desulfated CNC resulting in agglomeration and precipitation of
DCs.
protonation (H+) of phosphate (PO4-) group of the liposome (Aoki et al., 2015 and Kono
et al., 2018); second, the ionic interaction of protonated liposome (cationic at lower
pH) with slight anionic desulfated cellulose nanocrystals (DCs) resulting entangling
effect (Navon, Radavidson, Putaux, Jean, & Heux, 2017); third, the successive
agglomeration of desulfated CNC at lower pH due to protonation of its residual sulfate
group (SO-3) (Eyley et al., 2015) (Fig. 4.3).
79
4.3.3. Effect of pH on Zeta potential
The average zeta potential value of the samples is given in Fig. 4.4. PL contained a zeta
potential value of -33±3 mV at pH 7.0. With a decrease in the pH from pH 7.0 to pH
5.0, the zeta potential value decreased to -12±2 mV. Further, a decrease in the pH down
to 3.0 and 1.0, resulted in the zeta potential turning positive with values of +8±2.74 to
+18±3 mV. The positive zeta potential values were due to the positive choline group
of the liposomes and the protonation (H+) of PO4-3 group of the liposome (Fan, Chen,
Huang, Zhang, & Lin, 2017) (Fig. 3). An increase in the average particle size of the
samples may also have led to less surface area, reducing the charge density on the
surface, and leading to aggregation. (Yadav et al., 2011). The trend in zeta potential
with pH agrees with Peng et al. (2018), who reported that the zeta potential value of
liposome prepared using Sunlipon-75 (a type of phospholipids) decreased down to zero
when the pH was reduced to 3.0 and afterword gradually changed into positive values
at pH 2.0. Furthermore, no significant change in the zeta potential values of the PBP
loaded liposome (PL) was observed when the pH was increased to 9.0 and 11.0 and
this is in agreement with Peng et al. (2018). A similar trend in zeta potential with pH
for PL was obtained for PBP loaded liposome with polyethylene glycol 2000 and 4000
g/mol (PLP-2000 and PLP-4000). Results also displayed that the zeta potential value
of PLP-2000 and PLP-4000 were slightly lower compared to PBP loaded liposome
(PL) at pH 7.0, 9.0 and 11.0 (Fig. 4.4). Studies show that the polyethylene glycol
molecules can lower the zeta potentials value through the surface coating of the
colloidal system (Cheng et al., 2015).
80
Fig. 4.4. Effect of pH range on the zeta potential value of stabilized liposomes.
Note: PBP loaded liposome (PL), PBP loaded liposome stabilized with polyethylene
glycol (PLP-2000 and PLP-4000), PBP loaded liposome stabilized with desulfated
cellulose nanocrystals (PLDCs) and desulfated cellulose nanocrystals adsorbed with
polyethylene glycol (PLDCs-2000 and PLDCs-4000). Capital letters denote significant
differences (p≤0.05) among samples and small letters denote significant differences
(p≤0.05) among pH. Error bars represent the standard deviation of three independent
experiments.
The zeta potential values of PBP loaded liposome (PL), PL-2000 and PLP-4000
at pH 7.0 and above (9.0 and 11.0); were slightly lower than obtained for PBP loaded
liposome with desulfated CNC (PLDCs), PLDCs-2000 and PLDCs-4000 (Fig. 4.4).
This difference could be due to the contribution from the lower average zeta potential
of desulfated CNC (-22±3 mV). Furthermore, higher zeta potential values were
recorded at pH of 5.0 and 3.0 for the PLDCs, PLDCs-2000 and PLDCs-4000 (-11±3
and -2±0.7, -19±0.4 and -3±0.3 and -18±2 and -4±0.7 mV, respectively) compared to
PLP-2000 and PLP-4000. Again, these higher values may be due to the contribution
from the lower isoelectric point of the cellulose nanocrystals (around 2.5) (Eyley et al.,
81
2015). Further decrease in the pH to 1.0 resulted in a positive zeta potential values of
+15±3, +16±3 and +14±1 mV, respectively, which may be due to neutralization of the
anionic group of the CNC below its isoelectric point (Eyley et al., 2015; Bai et al.,
2019a).
4.3.4. Effect on the coalescence and agglomeration of behavior of liposomes and
cellulose nanocrystals
To confirm the increase in the average particle size and decrease in the zeta
potential value, we conducted the confocal laser scanning microscopic analysis of PBP
loaded liposome followed by optical microscopic observation of desulfated CNC with
polyethylene glycol. Fig. 4.5 shows the confocal image of PBP loaded liposomes with
different types of stabilizers at pH 7.0 and 1.0. The images show that the liposome
particles were unevenly dispersed into the aqueous medium for all of the samples;
however, a decrease in the pH led to effective coalescence. This coalescence behavior
Fig. 4.5. Confocal laser scanning microscopic images of stabilized liposomes.
Note: Agglomeration behavior phycobiliprotein loaded liposomes. pH 7.0 - first row
and pH 1.0 - second row. The scale bar is 2 µm. PBP loaded liposome (PL), PBP loaded
liposome stabilized with polyethylene glycol (PLP-2000 and PLP-4000), PBP loaded
liposome stabilized with desulfated cellulose nanocrystals (PLDCs) and desulfated
cellulose nanocrystals adsorbed with polyethylene glycol (PLDCs-2000 and PLDCs-
4000).
82
of the liposome supports our hypothesis that an increase in the average particle size of
the samples was due to the coalescence of liposomes at lower pH (Fig. 4.3). Optical
microscopic images of the desulfated CNC (DCs) and polyethylene glycol (2000 &
4000 g/mol) adsorbed desulfated CNC with phycobiliprotein loaded liposomes are
given in Fig. 4.6. It was observed that the desulfated CNC (DCs) with phycobiliprotein
loaded liposome clustered at all pH values. However, PLDCs-2000 and PLDCs-4000
(Fig. 4.6) showed no observable cluster at the pH condition of 7.0, 9.0 and 11.0 and
some tiny clusters of approximately 10 µm at pH 5.0. Further, a decrease in the pH
from 5.0 to 3.0 showed a group of clusters of about 20 to 30 to 50 µm in diameter;
however, further, decrease in pH to 1.0 showed a complete agglomeration of desulfated
CNC resulting a cluster of similar to optical microscopic images of PLDCs (Fig. 4.6).
The agglomeration of PLDCs-2000 and PLDCs-4000 was hypothesized to be due to
the desorption of polyethylene glycol at lower and higher pH levels (chapter 3).
Fig. 4.6. Optical microscopic image of stabilized liposomes samples at different pH.
Note: Polyethylene glycol adsorbed desulfated CNC (PLDCs-2000 and PLDCs-4000).
Scale bar 10 µm.
83
4.3.5. Effect of pH on the stability of phycobiliproteins
Fluorescence intensity values (centipoise - CPS) of the PBP for the samples
viz., PBPs, PL, PLP-2000, PLP-4000, PLDCs, PLDCs-2000 and PLDCs-4000 are
shown in Fig. 4.7. There is a substantial decrease in the fluorescence intensity for the
PBP in solution (PBPs) with a gradual decrease in the pH from 7.0 to 1.0, resulting in
a significant (p≤0.05) loss of 91±2%. In contrast, raising the pH from 7.0 to 11.0 had
comparatively less effect on the fluorescence intensity resulting in a total loss of 32±2%
(Fig. 4.8). A similar effect of the pH on the fluorescence intensity of the PBP extracted
from Phormidium rubidium was observed by Rastogi et al. (2015). They found a total
loss of 30.19 and 99.58% after an exposure period of 60 minutes at pH 4.0 and pH 2.0.
Considering the effect of basic pH environment on the stability of extracted PBP,
Fig. 4.7. Effect of stressors viz., pH (a), temperature (b) and illumination (c) on the
fluorescence intensity of PBP.
84
Note: Values are given in CPS are 1000 times higher of the given values. Error bars
represent the standard deviation of three independent experiments. PBP loaded
liposome (PL), PBP loaded liposome stabilized with polyethylene glycol (PLP-2000
and PLP-4000), PBP loaded liposome stabilized with desulfated cellulose nanocrystals
(PLDCs) and desulfated cellulose nanocrystals adsorbed with polyethylene glycol
(PLDCs-2000 and PLDCs-4000). Error bars represent the standard deviation of three
independent experiments.
85
Munier et al. (2014) found a total loss of up to 97% of the fluorescence intensity of the
PBP at pH 12.0, which was considerably higher compared to the value of 32% obtained
in this study at pH 11.0. The loss of fluorescence intensity of PBP was attributed to the
dissociation or denaturation of the subunits of PBP into monomeric units such as α-, β-
and γ- etc., of the PBP (Liu et al., 2009). An extreme change in the pH of the PBP’s
environment alters the chromophore structure by disturbing its electrostatic property
and O-H bond of protein structure (Szalontai, Gombos, Csizmadia, & Lutz, 1987).
These properties vary with the sources of PBP and types of monomeric subunits (Liu
et al., 2009; Munier et al., 2014 and Rastogi et al., 2015).
For the samples containing PBP in liposomes (PL, PLP-2000, PLP-4000,
PLDCs, PLDCs-2000, and PLDCs-4000), a slight decrease in the pH from 7.0 to 5.0
had no significant (p>0.05) effect on the fluorescence intensity (Fig. 4.7). Liposome
bilayers have good stability at pH above 5.0 and show slight chemical shifts of polar
head-groups of the phospholipid and mild protonation of phosphoric groups
(Sułkowski et al., 2005 and Ding et al 2009).
A further decrease in the pH from 7.0 to 1.0 reduced the fluorescence intensity
of the PBP significantly (p≤0.5) (Fig. 7), accounting for a total loss of 28±2.1, 9±3.8,
13±2.12, 25±1.7, 19±0.7 and 17±0.3% for PL, PLP-2000, PLP-4000, PLDCs, PLDCs-
2000, and PLDCs-4000, respectively (Fig. 4.8). These losses may be due to
destabilization of the liposome’s bilayer at lower pH that increased the permeability of
the bilayer resulting more release of the PBP and causing the loss of the fluorescence
intensity (Ding et al., 2009; Yadav et al., 2011 and Fan et al., 2017). Results showed
that the PLP-2000 and PLP-4000 retained approximately 15% more fluorescence
86
intensity as compared to the PL and PLDCs and approximately 7% more than PLDCs-
2000 and PLDCs-4000. As illustrated in Figure 3, a lower pH caused the agglomeration
of the CNC, resulting in less steric hindrance for the protonated liposomes. This might
have caused the coalescence of liposomes and loose liposome bilayers, resulting in the
release of PBP.
4.3.6. Effect of temperatures on the stability of phycobiliproteins
The temperature had the most noticeable effect on the fluorescence intensity of
the PBP in solution (PBPs), which decreased drastically with a gradual increase in the
exposure temperatures from 4 ℃ to 20, 40 and 60 ℃ (Fig. 4.7). This resulted in a total
loss of 8.4±2.9, 39.5±2.6 and 70.7±1.4, respectively (Fig. 4.8). Further increase in the
temperature above 60 ℃, resulted in a complete loss of the fluorescence intensity.
Munier et al. (2014) and Rastogi et al. (2015) reported a similar trend for the loss of
fluorescence intensity of the PBP isolated from Porphyridium cruentum and
Phormidium rubidium. Our results demonstrate the extreme instability of PBP above
40 ℃. PBP has a distinguishing characteristic of fluorescence due to its linear
tetrapyrrole bilin chromophores attached to a protein molecule (Glazer and Cohen-
Bazire, 197; Sidler, 1994). Likewise, the deleterious effect of the lower pH of 3.0 and
1.0 on fluorescence intensity of the PBP, higher temperature also might have damaged
the double covalent bond between tetrapyrrole bilin chromophores and protein
conjugates, causing the loss of the fluorescence intensity (Glazer et al., 1994).
Considering the stability of the fluorescence intensity for the PL, PLP-2000,
PLP-4000, PLDCs, PLDCs-2000 and PLDCs-4000, no significant (p>0.05) loss was
observed at the exposure temperature of 20 ℃ as compared to those stored at 4 ℃ (Fig.
87
Fig. 4.8. Effect of stressors viz., pH (a), temperature (b) and illumination (c) on the %
loss of the fluorescence intensity of PBP.
-20
0
20
40
60
80
100
1 3 5 7 9 11
Flu
ore
scen
ce in
ten
sity
(%
lo
ss)
pH levels
PBPs PL
PLP-2000 PLP-4000
PLDCs PLDCs-2000
PLDCs-4000
-20
0
20
40
60
80
100
120
4 ℃ 20 ℃ 40 ℃ 60 ℃ 80 ℃ 100 ℃
Flu
ore
scen
ce i
nte
nsi
ty (
% l
oss
)
Temperature (ºC)
PBPs PL
PLP-2000 PLP-4000
PLDCs PLDCs-2000
PLDCs-4000
a
b
88
Note: Error bars represent the standard deviation of three independent experiments.
PBP loaded liposome (PL), PBP loaded liposome stabilized with polyethylene glycol
(PLP-2000 and PLP-4000), PBP loaded liposome stabilized with desulfated cellulose
nanocrystals (PLDCs) and desulfated cellulose nanocrystals adsorbed with
polyethylene glycol (PLDCs-2000 and PLDCs-4000). Error bars represent the standard
deviation of three independent experiments.
4.7 and Fig. 4.8). Further increase in the temperature from 20 ℃ to 40 ℃, PL, PLP-
2000, PLP-4000 and PLDCs samples showed lower fluorescence intensity recorded a
total loss of up to 35% as compared to the PLDCs-2000 and PLDCs-4000, which
retained approximately 20% more fluorescence intensity. It was presumed that the PEG
adsorbed desulfated CNC (DCs-2000 and DCs-4000) might have provided the steric
stability to the liposomes by coating the surface resulting in less motile phospholipid
bilayers thereby less leakage and denaturation of the PBP. Further, increase in the
temperature from 40 ℃ to 60 ℃, the total loss difference between the samples with
(PLDCs-2000 and PLDCs-4000) and without (PL, PLP-2000, PLP-4000 and PLDCs)
-20
0
20
40
60
80
100
4 8 14 24 48 72
Flu
ore
scen
ce i
nte
nsi
ty (
% l
oss
)
Time (hours)
PBPs PL
PLP-2000 PLP-4000
PLDCs PLDCs-2000
PLDCs-4000
c
89
PEG adsorbed desulfated CNC decreased from 20% to approximately 7%. A complete
loss of the fluorescence intensity was recorded when temperature increased from 60 to
80 ℃. A similar effect on the activity of flavorsome loaded within liposome was
reported by Vafabakhsh et al. (2013) at different temperatures, who found a complete
loss of the fluorescence activity when exposed at 85℃.
4.3.7. Effects of illumination on the stability of phycobiliproteins
Illumination had the least significant effect on the fluorescence intensity of the
PBP as compared to the effect of pH and temperature, resulting in an insignificant
(p>0.05) loss over 4 hours of storage period. (Fig. 4.7). Further increase in the storage
period from 4 to 8 hours significantly (p≤0.05) reduced the fluorescence intensity for
the PBP in solution (PBPs), PL, PLP-2000, PLP-4000, and PLDCs, resulting in a total
loss of 13±1.1, 14±2.1, 13±3.9, 11±2.7 and 16±2.7% There was an insignificant
difference among the total loss for PLP-2000, PLP-4000, and PLDCs, which inferred
that PEG-2000 and PEG-4000 did not show any preserving activity against
illumination for the PBP despite ensuring the physicochemical stability of the
liposome. Because the liposome’s bilayers are transparent, illumination could have
easily penetrated the bilayer over time, effecting the fluorescence intensity of the PBP.
Further progression in the storage period from 8 to 14 hours, a gradual decrease in the
fluorescence intensity for the PBP in solution (PBPs), PL, PLP-2000, PLP-4000 and
PLDCs was recorded, resulting in a total loss of 29±0.7, 23±1. 3, 24±2.5, 22±0.9 and
31±3.6%, respectively. In contrast to the effect of illumination on PLP-2000, PLP-
4000, and PLDCs, PLDCs-2000 and PLDCs-4000 significantly remained the
fluorescence intensity resulting in zero loss over the storage period of 14 hours (Fig.
90
4.8). Throughout a total storage period of 72 hours, PLDCs-2000 and PLDCs-4000
displayed promising stabilizing activity for the fluorescence intensity of PBP in
liposome against illumination, accounted only a total loss of 32±4.4 and 34±1.0%,
respectively. This shows that the DCs-2000 and DCs-4000 had a significant stabilizing
activity for the fluorescence intensity of PBP against illumination, which may be due
to the partial UV-visible shielding activity of cellulose nanocrystals (Sirviö, Visanko,
Heiskanen, & Liimatainen, 2016). However, a total loss of 84±1.3, 78±2.8, 74±2.9,
74±1.7 and 75±2.3% were recorded for the PBP in solution (PBPs), PL, PLP-2000,
PLP-4000, and PLDCs. At illumination intensity of 33.57 μmol m−2 s−1 Munier et al.
(2014) reported a total loss of fluorescence intensity of PBP of up to 70% after a storage
period of 24 hours at 4 ℃. In agreement with our results, Rossano et al. (2003) has
reported that the exposure of illumination causes instability of R-phycoerythrin, a type
of PBP due to the loss of tetrapyrrole bilin chromophores.
4.4. Conclusion
An effective re-dispersion of desulfated cellulose nanocrystals into the aqueous
medium was achieved through adsorption of polyethylene glycol (2000 and 4000
g/mol). FTIR analysis confirmed the adsorption of PEG on the surface of the desulfated
CNC. Desulfated CNC adsorbed with polyethylene glycol was used as a stabilizing
material for the PBP loaded liposome. Results displayed that the DCs-2000 and DCs-
4000 retained 20% more fluorescence intensity at 40 ℃ as compared to PBP in solution
(PBPs), PL, PLP-2000, PLP-4000 and PLDCs. However, at the higher temperature of
above 80 ℃, DCs-2000 and DCs-4000 had an insignificant (p>0.05) effect on the
stability of fluorescence intensity, resulting in a complete loss by heat. Similarly, DCs-
91
2000 and DCs-4000 retained the fluorescence intensity of PBP up to 65% against
illumination after a storage period of 72 hours; however, the total fluorescence intensity
of up to 25% was retained for PL, PLP-2000, PLP-4000, PLDCs and 15% for the PBP
in solution (PBPs). pH affected the average particle size and zeta potential values of
the samples along with fluorescence intensity, resulted in a significant (p≤0.05)
increase in the average particle size due to agglomeration of PEG adsorbed desulfated
CNC and coalescence of liposomes. Lower pH of below 5.0 also caused the charge
reversal of liposomes resulting in positive zeta potential. Confocal laser scanning
microscopic and optical microscopic analysis confirmed the coalescence of PBP loaded
liposome and the agglomeration of PEG adsorbed DCs at pH 1.0. The study concluded
that the encapsulated PBP had a good stability below 60 °C, above pH of 5.0 and
against illumination. However, further modification of DCs is needed to enhance its
stabilization at a lower pH for delivering sensitive bioactive compounds.
92
CHAPTER 5
PHYSICOCHEMICAL STABILITY OF O/W PICKERING EMULSION
STABILIZED WITH LAURIC ACID ADSORBED CELLULOSE
NANOCRYSTALS AS AFFECTED BY DILUTION, pH AND STORAGE
PERIOD
5.1. Introduction
Pickering emulsion is a well-known type of emulsion system in which a physically
unstable dispersal phase is stabilized by solid colloid sized particles (Ramsden, 1904
and Pickering, 1907). In the past, a variety of colloidal particles and polymers have
been utilized to ensure the physicochemical stability and dispersity of the oil in water
(O/W) type emulsion, which includes synthetic polymers, surfactants and nano metals
(Midmore, 1998; Ashby and Binks, 2000; Tikekar et al., 2013; Sharma et al., 2015;
Shah et al., 2016). However, an increased sustainability concern and the demand of
food-grade stabilizing materials have pulled the researcher’s interest towards natural
polymers and colloidal particles such as solid lipids (Dieng et al., 2019a; Dieng et al.,
2019b), proteins (Dhakane et al., 2017 and Dai et al., 2018) and polysaccharides (Shao
et al., 2018; Ye et al., 2018; Fu et al., 2019). Furthermore, the effort to replace
commercial synthetic stabilizing materials has led researchers to explore for more
sustainable and novel sources, including cellulose nanocrystals, also known as
crystalline cellulose or cellulose nanowhiskers (Abiaziem et al., 2019), cellulose
nanofibers (Winuprasith et al., 2018) and TEMPO-oxidized cellulose (Goi et al., 2019).
Cellulose nanocrystals (CNC) possess several unique features such as nano-sized
dimension (150-200 nm long and 5-15 nm wide) (Cheng et al., 2015), non-toxic
93
(Seabra et al., 2018), dispersible in aqueous medium but insoluble (Cheng et al., 2015),
cheaply produced from wood and other underutilized bioresources (Trache et al., 2017;
Grishkewich et al., 2017), and contains a large number of surface O-H groups (Tang et
al., 2017).
CNC is produced via different methods such as acid hydrolysis (includes H2SO4,
HCl, HNO3, Citric acid, H3PO4 etc.), alkali hydrolysis (NaOH) and oxidation (Sharma
et al., 2019). However, several studies have reported that the CNC produced through
sulfuric acid hydrolysis has shown better emulsion stabilizing activity due to its high
electrical property contributed by surface sulfate groups (Cheng et al., 2015; Bai et al.,
2019a; Zhang et al., 2019). CNC helps to create a stable Pickering emulsion through
providing 1) a strong electrostatic repulsion and 2) steric hindrance (Bai et al., 2019a;
Zhang et al., 2019). Higher the sulfate groups (-SO3-) on the surface of CNC, more
stable the Pickering emulsion is, due to stronger electrostatic repulsion created among
the oil droplets (Zhang et al., 2019). Moreover, CNC adsorbed on interfaces of the oil
droplets create steric hindrance (Cherhal et al., 2016; Bai et al., 2018). Bergfreund &
Fischer (2019) and Bertsch et al. (2019) have reported that the efficacy of the CNC can
be improved by adding salt that can improve the rate of adsorption of CNC on the
interface of oil droplets due to increased surface pressure. Bai et al. (2019a) found that
addition of salt to the O/W Pickering emulsion can affect the electrostatic interactions
property of CNC such as (i) altered adsorption of CNC to the interface, (ii) altered
packing density of CNC at the interface and (iii) altered CNC-CNC interactions in the
aqueous phase. An increased CNC-CNC interaction can enhance the stability of an
emulsion by altering rheological properties, e.g., increasing gel strength of aqueous
94
phase that limits the motion of the oil droplets into a continuous phase, thereby less
interaction among oil droplets thus stable emulsion. However, it has been reported that
the stability of these types of emulsion may significantly be affected by dilution and
addition of opposite ions (Wooster, 2006; Maphosa and Jideani, 2018). Dilution can
lead to a segregative phase separation to the stable Pickering emulsion due to the
following reasons: (a) desorption of the polymer from the oil droplet interface tumbling
steric or electrostatic repulsion among droplets, (b) weaker gel strength of aqueous
medium, thereby increased droplets interaction thus coalescence/Ostwald ripening and
(c) reduced surface pressure on the oil droplets due to decreased salt concentration
desorption of adsorbed polymers (Wooster, 2006; Maphosa and Jideani, 2018; Bai et
al., 2019a).
It has been reported that the CNC with hydrophobic or amphiphilic surface property
can be an effective way to create stable Pickering emulsion (Zoppe et al., 2012;
Girouard et al., 2016; Saidane et al., 2016). Chemically modified CNC shows good
stability against dilution and ionic stress due to its stronger hydrophobic-hydrophobic
interaction between oil and CNC interface as compared to emulsion stabilized through
unmodified CNC. However, the chemical modification process is complex and requires
a large number of organic chemicals and other reagents, which may not be a food-grade
and sustainable. In this work, a hypothesis was made, modifying the surface of CNC
through adsorption of an amphiphilic molecule such as fatty acid to create a
hydrophobic surface, which can provide a better lipophilic-lipophobic balance between
oil droplets and CNC, creating a stable Pickering emulsion.
95
Thus, a stable beta-carotene O/W Pickering emulsion was created using different
concentrations (0.5, 1.0, 1.5 and 2.0%) of lauric acid adsorbed CNC (CL) and neat
CNC separately. Effect of different dilution factors (1-10x), pH (1-11) and storage
period (1-30 days) on the physicochemical stability of the Pickering emulsion was
analyzed. Following quality attributes, including average particle size, zeta potential,
optical microscopic image, creaming index (CI), lipid oxidation (TBARS assay), and
beta-carotene stability, were recorded during the experiment.
5.2. Materials and Methods
Sulfuric acid-hydrolyzed CNC (11.5 to 12.5%) with a dimension of 150-200 nm
long and 5-20 nm wide was purchased from the Process Development Center (PDC) of
the University of Maine. Canola oil (Great value, Walmart, Bangor, Maine) was
purchased from the local supermarket of Bangor, Maine. Lauric acid flake (>99%
pure), 2-thiobarbituric acid (TBA), trichloroacetic acid (TCA), butylated
hydroxytoluene (BHT), 1,1,3,3-tetraethoxypropane (TEP) and other analytical grade
solvents were purchased from Acros Organics/Fisher Scientific, USA. Beta-carotene
(standard grade) was purchased from Sigma Aldrich, USA.
5.2.1. Adsorption of lauric acid with CNC
A 20 g quantity of lauric acid powder was dissolved in 400 mL of ethanol;
subsequently, a 100 g of CNC (11.5 to 12.5%) was added to the solution. Mixture was
then stirred at 500 rpm until the CNC was distributed homogeneously, then the mixture
was consistently stirred for 24 hours at 100 rpm at room temperature. The adsorption
took place in an airtight one-liter bottle to prevent the evaporation of the solvent.
Mixture was then centrifuged at 21,800x g for 10 minutes at room temperature using a
96
super speed centrifuge (Beckman Coulter Avanti J-E Floor, CA, USA). The pellet was
collected and washed repeatedly with ethanol. The pellet was later vacuum dried at 60
°C overnight and stored into a Ziploc bag at room temperature for further use. Later the
adsorption of lauric acid was confirmed by FTIR (ABB, FTLA 2000) analysis and the
average particle size and zeta potential were measured using zeta-sizer (Zetasizer
Malvern 3000 HAS). The amount of the adsorbed lauric acid was quantified, preparing
a blend of the nine different concentrations of lauric acid (10, 20, 30, 50, 75, 100, 150,
200 and 250 mg/500 mg of dried CNC). FTIR % transmittance was recorded, and the
% transmittance value was converted to the absorbance (Fig. 5.1) following the
equation developed by Toft et al. (1993):
𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 = 2 − 𝑙𝑜𝑔 (%𝑇)
Obtained absorbance values were plotted to a calibration curve to calculate the
amount of lauric acid adsorbed (Fig. 5.1).
97
Fig. 5.1. FTIR spectra of the lauric acid mixed CNC (a) and calibration curve of lauric
acids with different concentrations (b).
Note: Different concentrations of lauric acid (10-250 mg) mixed with CNC (500 mg)
to plot a calibration curve to quantify the amount of adsorbed lauric acids on the surface
of CNC.
98
5.2.2. Preparation of beta-carotene O/W emulsion and stabilization
Different concentration of lauric acid adsorbed CNC (CL) dispersion (0.5, 1.0,
1.5 and 2.0%) was prepared by re-dispersing dried CL into distilled water stirring at
400 rpm for one hour and coded as CL-0.5, CL-1.0, CL-1.5 and CL-2.0, respectively.
Since the adsorption of lauric acid decreased the pH of the disperse solution to 4.1±0.2,
pH was neutralized to 7.0 using 0.1 N NaCl. Similarly, a dispersion of neat CNC (never
dried CNC without lauric acid) of the same concentrations (0.5, 1.0, 1.5 and 2.0%) were
prepared by dilution with distilled water and coded as C-0.5, C-1.0, C-1.5, and C-2.0.
10 mL of beta-carotene dissolved canola oil (1 mg/100 mL) was added to the 90 mL of
CL and CNC dispersed solution (a continuous medium) and a coarse emulsion was
prepared using an Ultra-Turrax (IKA S 18 N - 19 G Dispersing Element) for 2 minutes
at 10,000 rpm. In addition to the emulsion prepared into neat CNC dispersed continuous
medium, a 0.06 g of NaCl was added to facilitate the stabilization activity of CNC as
described by Bai et al. (2018). A fine emulsion was prepared by sonicating the coarse
emulsion for 5 minutes at 4-6 ℃ using an ultrasonic dismembrator (500W, 20 kHz,
Fisherbrand™ Model 505, USA) facilitated with a ¾ inch titanium alloy microtip
probe. A 40 percent amplitude of the sonication at the interval of 15 seconds ON and 5
seconds OFF-pulse time was used during the process (Mehmood et al., 2017).
5.2.3. Stability study of emulsions
Physicochemical stability of the beta-carotene O/W emulsion stabilized with CL
and CNC was investigated, exposing the emulsion to different stressing factors such as
dilution, pH and storage period to predict the approximate stability of emulsion during
food processing and consumption.
99
5.2.3.1. Effect of dilutions
Processed foods encounter different dilutions or addition of different solvent
mediums during processing and consumption. An emulsion system must be stable
when added to a different food matrix and subjected to the digestion process. To
understand the effect of dilution on the stability of created Pickering emulsions, a series
of dilution viz., initial (1x), 1:1 (2x), 1:3 (4x), 1:5 (6x), 1:7 times (8x) and 1:9 (10x)
with distilled water was performed. In brief, a dilution level of 6x was prepared by
mixing 1 mL of emulsion with 5 mL of distilled water. Diluted emulsion samples were
kept in the dark at room temperature for 4 hours and the characterization was performed
subsequently. For each type of attribute analysis, fresh samples were prepared, and the
effect of dilution was investigated in triplicate with simultaneous duplication of the
process.
5.2.3.2. Effect of pH
Since pH is the major factor causing the electrostatic screening of the
electrostatically stable emulsion system, the stabilized emulsion was exposed to
different pH of 1, 3, 5, 7, 9 and 11, respectively. A 10 mL of the emulsion was placed
into an amber-colored Erlenmeyer flask and the respective pH was maintained using
0.1 N HCl and 0.1 N NaOH. The samples were stored in the dark at room temperature
for 2 hours of reaction period and subsequently, samples were analyzed.
5.2.3.3. Effect of storage periods
A 100 mL of prepared emulsions were placed into 250 mL amber-colored
Erlenmeyer flask and stored in the dark at room temperature (Tikekar et al., 2013). The
100
quality attributes of the stabilized emulsion such as average particle size, creaming
index, TBARS assay and beta-carotene were recorded after 0, 1, 2, 3, 5, 10, 15, 20 and
30 days of storage period.
5.2.4. Particle size and zeta potential analysis
Average particle size and zeta potential of the stabilized emulsion were
performed on dynamic light scattering zeta-sizer (Zetasizer Malvern 3000 HSA) as
described by Zhang et al. (2019). The samples were diluted with distilled water to
prevent the multiple scattering effects during analysis. The refractive index for the
canola oil was fixed at 1.465 (Przybylski, 2001) and 1.330 for water (Zhang et al.,
2019).
5.2.5. Optical microscopic analysis
Optical microscopic images of the stabilized emulsion were performed on
AmScope Polarized Light Microscope. A 100 µL of emulsion samples from each
experiment were placed on a glass slide and images were acquired simultaneously at
20x magnification of the lens (Zhang et al., 2019).
5.2.6. Creaming index
Creaming index of the samples was recorded following the method suggested
by Varka et al. (2010) with some modifications. Instead of measuring the height of the
separated oil phase and the continuous phase, the amount of the beta-carotene was
measured between both phases using a multi-plate reader UV-Vis spectrophotometer
(BioTek Eon, Vermont, U.S.A) at 452 nm. In brief, 1 mL of sample was withdrawn
from the separated phase and the continuous phase separately and dissolved into 10 mL
101
of n-hexane by vortexing for 1 minute. The solution was stored at 4 ℃ until a clear
layer of the aqueous phase and n-hexane appeared. A 200 µl of fraction from the top
layer was placed into 96 well microplates and absorbance was recorded at 452 nm. The
percent creaming index was calculated using the following equation:
𝐴𝑏𝑠𝑡𝑜𝑝
𝐴𝑏𝑠𝑡𝑜𝑡𝑎𝑙× 100
𝐴𝑏𝑠𝑡𝑜𝑡𝑎𝑙 = 𝐴𝑏𝑠𝑡𝑜𝑝 + 𝐴𝑏𝑠𝑐𝑜𝑛𝑡𝑖𝑛𝑢𝑜𝑢𝑠 𝑝ℎ𝑎𝑠𝑒
Where Abstop is the absorbance of beta-carotene in the separated oil phase.
Additionally, the UV-Vis spectra of the beta-carotene present of the Pickering
emulsion was analyzed, withdrawing 1 mL of emulsion from the center of the
experimental vessel and 10 mL of n-hexane was added. Mixture was vortexed for 1
minute then stored at 4℃ until a clear layer of the aqueous phase and n-hexane
appeared. A 200 µl of fraction from the top layer was placed into 96 well microplates
and spectral scanning was performed between 330 nm to 550 nm.
5.2.7. TBARS analysis
Thiobarbituric acid reactive substances assay (TBARS) analysis of the
Pickering emulsion stored at ambient temperature in the dark was recorded over 30
days of storage periods. Malondialdehyde present in the emulsion was measured using
the TBARS assay following the method of Alamed et al. (2006). One liter of TBA
reagent was prepared by dissolving 3.75 g of TBA, 150 g of TCA and 2% BHT into
ethanol, then into 750 mL of 0.25 M HCl solution. 0.5 mL of emulsion sample was
taken into the screw cap glass test tube and 9.5 mL of TBA reagent was added. The test
tube was placed into a preheated water bath at 90 ℃ for 15 minutes, followed by
102
immediate cooling by placing it into the refrigerator for 10 minutes. The reaction
medium was then centrifuged at 3,480x g for 15 minutes at room temperature using a
centrifuge model Beckman Coulter Avanti J-E Floor, CA, USA. 200 µL of the
supernatant was withdrawn and placed into 96 well microplates, and absorbance was
recorded at 532 nm. A calibration curve of the different concentrations of TEP was
used as a standard to quantify the TBARS values (Fig. 5.2). TBARS analysis of the
control emulsion sample was prepared following the protocol of Bai et al. (2019b). A
10 mL of beta-carotene dissolved canola oil (1 mg/100 mL) was added to the 90 mL of
1% solution of Gum Arabic. A fine emulsion was prepared following the stapes
discussed in sub-section 2.2.
Fig. 5.2. Calibration curve of the different concentrations of 1,1,3,3-
tetraethoxypropane (TEP) standard.
y = 0.0682x + 0.4473
R² = 0.9989
0
0.5
1
1.5
2
2.5
3
3.5
4
0 10 20 30 40 50
Ab
sorb
an
ce
TEP (µmol)
103
5.2.8. Beta-carotene stability
Beta-carotene stability during the storage period of up to 30 days was recorded
at room temperature under dark conditions. Quantification was performed, taking 5 mL
of an emulsion into 20 mL of n-hexane and vortexing for 1 minute and stored at 4 ℃
until a clear layer of the water and n-hexane was formed. A 200 µl of fraction from the
yellow portion was placed into 96 well microplates and absorbance was recorded at
452 nm. A standard curve of the beta-carotene was plotted to calculate the amount of
beta-carotene (Fig. 5.3).
Fig. 5.3. Calibration curve of the different amounts of beta-carotene standard.
5.2.9. Mineral analysis
The mineral content of the CNC sample was analyzed after getting the spike in
lipid oxidation of emulsion stabilized with CNC as compared to reference emulsion (no
y = 0.1441x + 0.3191
R² = 0.9975
0
0.5
1
1.5
2
2.5
3
3.5
0 5 10 15 20
Ab
sorb
an
ce
Beta-carotene (mg)
104
CNC rather a gum arabic). Assuming that it may be due to the presence of some
transition metals in the CNC causing increased lipid oxidation, the elemental analysis
was performed on an Inductively Coupled Plasma Mass Spectrometry (ICP-MS) device
(Finnigan Element2, Thermo Fisher, Waltham, MA). A 10 g of neat CNC was dried
overnight at 80 °C to remove the moisture content. Dried CNC was exposed to a high
temperature of 400 ℃ for 5 hrs. The resulting ash was dissolved into 20 mL of 1%
nitric acid solution and the sample was loaded on an autosampler (CETAC ASX-100).
Distilled water and ICP-MS lab blank were also analyzed for the mineral content to
account for possible contamination during sample preparation.
5.2.10. Statistical analysis
Each experiment was conducted in triplicate. A Tukey’s (HSD) post hoc test
was performed on SAS® Studio (Version 9.4, University edition) to identify the
significant differences among the mean values. Analysis of Variance (ANOVA) was
used to determine the significant effect among treatments at the level of p≤0.05.
5.3. Results and Discussion
5.3.1. Characterization of lauric acid adsorbed CNC (CL)
The adsorption of the lauric acid on the CNC was confirmed by FTIR analysis
(Fig. 5.4). A strong characteristic IR peak for the CL between 2800 to 2960 cm-1 is due
to the stretching vibration of C-H group of lauric acid. However, peak at 1694 cm-1 is
due to the stretching vibration of C=O (Shifu et al., 1989). After ten repeated washes,
the presence of these characteristic peaks validates the successful adsorption of the
lauric acid. A calibration curve was used to quantify the amount of adsorbed lauric acid
105
on the surface of CNC (Fig. 5.1), which recorded 78.62 mg of lauric acid per 500 mg
of dried CNC. The average particle size and analysis and zeta potential value for the
CL were found be 224±11 nm and -54±5 mV; however, it was 176±7 nm and -52±3
mV for neat CNC (fresh CNC).
Fig. 5.4. FTIR spectra of cellulose nanocrystal and lauric adsorbed CNC.
Note: Cellulose nanocrystal (CNC), lauric acid (LA) and lauric acid adsorbed CNC
(CL). Highlighted peaks confirm the adsorption of lauric acid on CNC.
106
5.3.2. Stability of Pickering emulsion
5.3.2.1. Effect of dilutions on average particle size
The average particle size of the Pickering emulsions was recorded against
different dilution factors, pH and storage period. Since the food matrix passes through
different stages such as processing conditions, serving styles, and digestion, it is vital
assuring the key attributes of the foods are maintained. A complex food system such as
Pickering emulsion, which is a physicochemically stable emulsion system; must retain
its quality during processing, storage, serving as well as during initial and stomach
phases of the digestion system (Wooster, 2006; Maphosa and Jideani, 2018; Bai et al.,
2019b). To understand the physicochemical stability of the Pickering emulsion,
dilution was considered as one of the major factors. Dilution is a widespread practice
during serving the food; for example, dilution of concentrated beverages can result in
phase separation of the lipid phase. Moreover, secretion of digestive juices can weaken
gel strength of the viscous foods and can also result in a phase separation of oil phase
from the aqueous phase (Winuprasith et al., 2018; Bai et al., 2020b).
Results from particle size analysis revealed that the neat CNC of all the different
concentrations had an average particle size of 2.23±0.14, 2.18±0.27, 2.16±0.08 and
2.21±0.11 µm for the C-0.5, C-1.0, C-1.5 and C-2.0, respectively. However, emulsion
stabilized with CNC adsorbed lauric acid (CL) had significantly lower (p≤0.05)
average particle size of 1.53±0.17, 1.33±0.05 and 1.23±0.09 µm (CL-1.0, CL-1.5 and
CL-2.0) except for the CL-0.5 (3.41±0.26 µm) as compared to the emulsion stabilized
with neat CNC. It was assumed that the larger average particle size for the emulsion
with neat CNC was due to the following two possible reasons: i) increased packing
107
density of CNC at the oil droplet interface due to increased surface pressure in the
presence of NaCl, leading to increased particle diameter and ii) NaCl can increase
CNC-CNC interactions in the aqueous phase due to presence of Na+ cations resulting
in bulkier and aggregated CNC particles (Bergfreund & Fischer, 2019; Bertsch et al.,
2019; Bai et al., 2019a). In contrast to the emulsion stabilized with neat CNC, smaller
average particle size for the emulsion with CL may be due to a thinner packing density
of CL at oil droplets interface triggered by hydrophobic-hydrophobic interaction rather
NaCl induced interaction and adsorption of CNC (Zoppe et al., 2012; Girouard et al.,
2016; Saidane et al., 2016). Results are shown in Figure 5.5, indicated that a serial
dilution had a significant effect (p≤0.05) on the average particle size of the C-0.5 C-
1.0, C-1.5 and C-2.0, resulted in a gradual increase in the average particle size from
4.11±0.39 to 10.36±0.08, 2.66±0.2 to 10.27±0.06, 2.38±0.11 to 8.22±0.28, 2.21±0.07
to 7.02±0.34 µm. It was also observed that the higher dilution factors of eight (8x) and
ten (10x) resulted in a significantly (p≤0.05) smaller average particle size as compared
to the dilution factor of six (6x). It has been reported that a dilution of a Pickering
emulsion can lead to a segregative phase separation due to the following reasons: (a)
desorption of the polymer from the oil droplet interface reducing steric or electrostatic
repulsion among droplets, (b) weaker gel strength of aqueous medium thereby
increased droplets interaction thus coalescence/Ostwald ripening and (c) reduced
surface pressure on the oil droplets due to decreased salt concentration desorption of
adsorbed polymers (Wooster, 2006; Maphosa and Jideani, 2018; Bai et al., 2019a). Bai
et al. (2019b) recorded a significant increase in the droplet size of the NaCl-CNC
stabilized O/W emulsion during the in vitro gastrointestinal study, which may be due
108
Fig. 5.5. Effect of the dilution factors on the average particle size of emulsions.
Note: Unmodified CNC or neat CNC (C), lauric acid adsorbed CNC (CL), C-0.5 is the
emulsion stabilized with 0.5% of unmodified CNC. Similarly, given numbers are the
different concentrations viz., 0.5, 1.0, 1.5 and 2.0% of CNC and CL (solid basis). The
upper-case letters denote significant differences (p ≤0.05) among sample types;
however, small letters denote significant differences (p≤0.05) among dilutions (1x, 2x,
4x 6x 8x, and 10x), where “x” represents the number of dilutions.
to the addition of a large amount of the simulated digestive juices (~60 mL/20 mL of
2% O/W emulsion) leading to the dilution of stabilized emulsion. In contrary to the
effect of the dilution on C-0.5 C-1.0, C-1.5 and C-2.0, it was found that the dilution has
less or no effect on the average particle size of the emulsion stabilized with CL (CL-
1.0, CL-1.5 and CL-2.0) except for the CL-0.5. It was hypothesized that the lower
concentration of CL, i.e., for the CL-0.5, might not have covered the interface of oil
droplets resulting in simultaneous coalescence and Ostwald ripening, thus larger
average particle size. Finding inferred that the lauric acid adsorbed on the CNC
facilitated the partial hydrophobicity to the CNC, resulting in a stable emulsion. Fig.
Aa AaAa
Aa
Ea
FaGa Ga
AbAb
Cb
Aa
Eb
Fb
Ga Ga
Ac
Bc
Cc
Db Db
Fc
GbFa
Ad Ad
Cd
Dc
Eb
Aa
Ga Ea
Ae
Be
Ce
Dd
Eb
Aa
Ga Ga
Af
Bf
Cf
De
Ec
Fd
Ga Ga
0
2
4
6
8
10
C-0.5 C-1.0 C-1.5 C-2.0 CL-0.5 CL-1.0 CL-1.5 CL-2.0
Pari
cle
size
(µ
m)
Sample types
1x
2x
4x
6x
8x
10x
109
Fig. 5.6. Optical microscopic image of the stabilized emulsion.
Note: 1x is no dilution and 10x is ten times diluted emulsion. 0.5, 1.0, 1.5 and 2.0 are
the concentration of CNC (C) and lauric acid adsorbed CNC (CL). Scale bar is 10 µm.
5.6 displays the optical microscopic images of the emulsion before (1x) and after ten
dilutions (10x). It was noticed that the dilution led the coalescence/Ostwald ripening of
oil droplets. This further support the findings of the effect of dilution on the increased
average particle size of the O/W emulsion stabilized with NaCl-CNC. As described
earlier, the dilution can disrupt the gel packing/network of a NaCl-CNC Pickering
emulsion and can trigger the coalescence/Ostwald ripening of the oil droplets (Fig.
5.7). However, dilution may not have a similar effect for the emulsion stabilized with
110
Fig. 5.7. Schematic illustration (not to scale) of the stabilization of emulsion.
Note: Emulsion stabilized with unmodified CNC + NaCl (a) and lauric acid adsorbed
CNC (b). An effect of dilution on the stability of emulsion stabilized with NaCl-CNC
(a). Dilution breaks the CNC gel packing/network causing the coalescence/Ostwald
ripening of the oil droplets.
Fig. 5.8. Macroscopic image of stabilized emulsions.
Note: Creaming stability of emulsion after ten times (10x) of dilution and a storage
period of after 4 hours of storage period. Unmodified CNC (C) and lauric acid adsorbed
CNC (CL) with different concentrations of 0.5, 1.0, 1.5 and 2.0% (solid basis).
111
CL due to a hydrophobic-hydrophobic interaction between oil droplets and CL.
Macroscopic images of the beta-carotene O/W emulsions are shown in Fig. 5.8 exhibit
the effect of ten times dilution (10x) on the creaming stability of oil droplets after 4 hrs.
A clear phase separation for the C-0.5, C-1.0, C-1.5, C-2.0 and CL-0.5 can be seen,
except for the CL-1.0, CL-1.5 and CL-2.0 inferred that the CL above 1.0 % can be a
potential candidate for stable Pickering emulsion.
5.3.2.2. Effect of pH on average particle size
The effect of pH ranging from 1 to 11 on the particle size and zeta potential of
the Pickering emulsions are given in Fig. 5.9a. It was observed that the pH level of
above 3.0 had no significant (p>0.05) effect on the average particle size of the Pickering
emulsion for both types of samples; however, a significant (p≤0.05) increase in the
average particle size was recorded at the pH level 1.0. Since an extremely lower pH
can lead to the protonation (H+) of the sulfate anions (-OSO3-) present on the surface
of the CNC, leading to the agglomeration of the CNC (Varanasi et al., 2018). It was
also presumed that the protonation of CNC led the reduced electrostatic repulsion
causing agglomeration of the CNC adsorbed oil droplets, thus flocculation. Bai et al.
(2019a) reported a significant increase in the particle size of the CNC stabilized O/W
Pickering emulsion below the pH level of 2.0. The study concluded that the increase in
the particle size was caused by flocculation rather coalescence/Ostwald ripening, as
confirmed by confocal laser scanning microscopic analysis of the samples. As it was
hypothesized that the lower pH decreased electrostatic repulsion among the oil droplets
due to protonation of the CNC adsorbed oil droplets. Results shown in Fig. 5.9b
displayed a significant change in the zeta potential values of the Pickering emulsions
112
Fig. 5.9. Effect of pH on the average particle size of stabilized emulsion.
Note: Emulsion stabilized with unmodified CNC (C) and lauric acid adsorbed CNC
(CL) with different concentrations of 0.5, 1.0, 1.5 and 2.0% (a). The upper-case letters
denote the significant difference (p ≤0.05) among sample types; however, small letters
denote the significant difference (p≤0.05) among pH (1, 3, 5, 7, 9 and 11). Effect of pH
on the zeta potential of the emulsion stabilized with CNC 2.0% (C-2.0) and lauric acid
adsorbed CNC 2.0% (CL-2.0).
AaAa
Aa
Aa
Ba
Ab AbAb
Ab
AbAb
Ab
Aa
CbCb
Cb
AbAb
AbAb
Aa
Cb
Cb Cb
Ab
Ab AbAb
Aa
CbCb
Cb
Ab
AbAb
Ab
Aa
Cb CbCb
Ab Ab AbAb
Aa
CbCb
Cb
0
1
2
3
4
5
6
C-0.5 C-1.0 C-1.5 C-2.0 CL-0.5 CL-1.0 CL-1.5 CL-2.0
Part
icle
siz
e (µ
m)
Sample types
1 3 5 7 9 11
-60
-50
-40
-30
-20
-10
0
10
1 3 5 7 9 11
Zet
a p
ote
nti
al
(mV
)
pH levels
C-2.0
CL-2.0
(b)
(a)
113
as affected by a decrease in pH; however, a pH of above 7.0 had no significant effect
(p>0.05). A consecutive less negative zeta potential values were recorded with a
gradual decrease in the pH due to protonation of the sulfate ions, causing a charge
inversion to the particles at the pH level of 1.0. This resulted in a positive zeta potential
values of 9.64±0.78 mV and 10.84±1.69 mV below the isoelectric point of the CNC
(pKa = 1.9, Varanasi et al., 2018). The charge inversion of a particle either from
negative to positive or positive to negative is a phenomenon of altering the electric
behavior of a particle with the addition of an excessive number of the opposite ions,
which leads to the overcharge, also known as charge reversal (Schubert et al., 2019).
5.3.2.3. Effect of storage on average particle size
Fig. 5.10 shows the average particle size of the Pickering emulsion stored at
ambient temperature after 1, 2, 3, 5, 10, 15 and 30 days of preparation. Result displayed
that the particle size for the emulsion stabilized with neat CNC (C-0.5, C-1.0, C-1.5
and C-2.0) was constant over the storage period. An insignificant (p>0.05) change in
average particle size for the emulsion with neat CNC can be explained due to the
following reasons: (i) NaCl increased adsorption of CNC to the oil droplet interface
due to increased surface pressure, (ii) increased packing density of CNC at the oil
droplet interface, and (iii) NaCl increased CNC-CNC interactions in the aqueous phase
(Bergfreund & Fischer, 2019; Bertsch et al., 2019; Bai et al., 2020a). Presence of NaCl
increased the interaction of CNC-CNC due to Na+ cations in the continuous phase,
increasing the gel strength of the aqueous phase. The increased gel strength of the
aqueous phase can limit the mobility of the oil droplets resulting in less interaction
among oil droplets, thus stable emulsion. A similar result was recorded for the emulsion
114
Fig. 5.10. Effect of storage periods on the average particle size of stabilized emulsions.
Note: Emulsions stabilized with unmodified CNC (C) and lauric acid adsorbed CNC
(CL) with different concentrations of 0.5, 1.0, 1.5 and 2.0% (solid basis).
stabilized with CL except for the CL-0.5 and CL-1.0. It was observed that the average
particle size for both samples (CL-0.5 and CL-1.0) increased significantly (p≤0.05)
over the storage period. It can be reasonably assumed that the coalescence/Ostwald
ripening of the partially coated or unentrapped oil droplets was caused by the Van der
Waals attraction that increased the average particle size (Bai et al., 2019a).
5.3.2.4. Effect on creaming index
The creaming index (CI) of the Pickering emulsion was estimated to analyze
beta-carotene content present in the top layer of the emulsion and the total beta-carotene
in the emulsion. Results shown in Figure 5.11a, displayed that the dilution had a
significant (p≤0.05) increase in the CI for the emulsion stabilized with neat CNC (C-
0.5, C-1.0, C-1.5 and C-2.0), resulting in up to 90% of the CI at a dilution factor of 10x
(Fig. 5.11a). Reasonably it was due to weakening or complete loss of the gel strength
0
2
4
6
8
10
12
0 1 2 3 5 10 15 30
Pa
rtic
le s
ize
(µm
)
Storage period (Days)
C-0.5C-1.0C-1.5C-2.0CL-0.5CL-1.0
115
Fig. 5.11. Creaming index of the stabilized emulsions.
Note: Effect of dilutions (1x and 10x) after 4 hours (a) and storage periods (b) on the
creaming index. The upper-case letters denote significant differences (p≤0.05) among
sample types; however, small letters denote significant differences (p≤0.05) between
dilutions (1x and 10x).
Aa
Ba BaBa
Ca
Aa
Ba Ba
Ab AbAb
Ab
Cb
Db
Ba Ba
0
20
40
60
80
100
C-0.5 C-1.0 C-1.5 C-2.0 CL-0.5 CL-1.0 CL-1.5 CL-2.0
Cre
am
ing i
nd
ex (
%)
Sample types
1x
10x
-5
10
25
40
55
70
85
100
Intial 1 5 15 30
Cre
am
ing i
nd
ex (
%)
Storage period (Days)
C-0.5 C-1.0 C-1.5 C-2.0CL-0.5 CL-1.0 CL-1.5 CL-2.0
(b)
(a)
116
of the continuous phase resulting coalescence/Ostwald ripening of the oil droplets led
by Van der Waals force of attraction (Bai et al., 2019b). It was also presumed that the
dilution caused the depletion of any adsorbed CNC from the surface of the oil droplets
altering the steric and electrostatic stability of the Pickering emulsion. In contrast to the
effect of dilution on C-0.5, C-1.0, C-1.5 and C-2.0, it was noticed that the dilution did
not affect the CI of Pickering emulsion stabilized with CL except for the CL-0.5 and
CL-1.0. An increase in the CI for the CL-0.5 and CL-1.0 from 51.98 to 69.81% and
17.13 to 24.04% was attributed due to coalescence/Ostwald ripening/flocculation of
the uncoated/partially coated oil droplets. It can be reasonably assumed due to lower
concentration of the CL for the CL-0.5 and CL-1.0 as compared to the CL-1.5 and CL-
2.0. It was observed that an increase in the concentration of the CL in the emulsion
gradually decreased the CI of the Pickering emulsion and so the effect of dilution (Fig
5.11a). UV-Vis spectrum of the beta-carotene from the Pickering emulsion shown in
Fig. 5.12 displayed an indistinguishable change in the absorbance of the beta-carotene
of the samples except for the CL-0.5 and CL-1.0 (Fig 5.12a-b). However, a dilution
factor of 10x resulted in an intense decrease in the absorbance at 452 nm for the C-0.5,
C-1.0, C-1.5 and C-2.0 Pickering emulsions (Fig 5.12c). A decreased absorbance of
the beta-carotene in the emulsion indicated the creaming of the disperse phase (oil
phase) from the continuous phase (aqueous phase), resulting in less beta-carotene in
the continuous phase thus lower absorbance. CI for the Pickering emulsion was
recorded after 1, 5, 15 and 30 days of storage period are shown in Fig 5.11b. Results
indicated that the CI of the samples were not significantly different (p>0.05) over the
30 days of storage period except for the CL-0.5 and CL1.0. A sharp increase in the CI
117
Fig. 5.12. UV-Vis spectra of the beta-carotene of stabilized emulsions.
0
0.5
1
1.5
2
2.5
3
330 380 430 480 530
Ab
sorb
an
ce
Wavelength (nm)
C-0.5 C-1.0
C-1.5 C-2.0
CL-0.5 CL-1.0
CL-1.5 CL-2.0
0
0.5
1
1.5
2
2.5
3
330 380 430 480 530
Ab
sorb
an
ce
Wavelength (nm)
C-0.5 C-1.0
C-1.5 C-2.0
CL-0.5 CL-1.0
CL-1.5 CL-2.0
(a)
(b)
118
Note: Spectra of the beta-carotene from stabilized emulsions after 0 hour (a), 4 hours
(b), 10 times (10x) diluted emulsion after 4 hours (c) and undiluted emulsions after 30
days of storage (d).
0
0.5
1
1.5
2
2.5
3
330 380 430 480 530
Ab
sorb
an
ce
Wavelength (nm)
C-0.5 C-1.0
C-1.5 C-2.0
CL-0.5 CL-1.0
CL-1.5 CL-2.0
0
0.5
1
1.5
2
2.5
3
330 380 430 480 530
Ab
sorb
an
ce
Wavelength (nm)
C-0.5 C-1.0
C-1.5 C-2.0
CL0.5 CL1.0
CL1.5 CL2.0
(c)
(d)
119
of 66.33% was recorded on the first day of storage for the CL-0.5; however, a further
increase in the storage period had an insignificant (p>0.05) effect on the CI of the CL-
0.5. Since the concentration of the CL was the lowest, a quick increase in the CI for the
CL-0.5 was due to coalescence/Ostwald ripening or flocculation of uncoated oil
droplets resulting in creaming and phase separation. However, an increase in the CL
concentration in the emulsion had significantly (p≤0.05) lower CI over the storage
periods. UV-Vis spectrum of the beta-carotene from the Pickering emulsion after 30
days of storage is given in Fig. 5.12d. Results displayed that the absorbance of the beta-
carotene at 452 nm decreased drastically for the CL-0.5 after 30 days of storage.
However, as the concentration of the CL increased above 1.0 %, the absorbance of the
beta-carotene in the continuous phase was unchanged. Bai et al. (2018) found that the
Pickering emulsion stabilized with a lower concentration of CNF had higher CI during
the storage period.
5.3.3. Oxidative stability of emulsions
The oxidative stability of the O/W emulsion is greatly influenced due to the
presence of lipid hydroperoxides and the transition metals in the emulsion system.
Lipid hydroperoxides on the surface of the oil droplets and the presence of transition
metals in the continuous phase are the major cause of the lipid oxidation (Alamed et
al., 2006). Malondialdehyde, an end product of the deterioration of the lipid
hydroperoxides and other primary and secondary lipid peroxidation products (Janero,
1990) is measured by TBARS analysis (Alamed et al., 2006). The oxidative stability
of the Pickering emulsion at ambient temperature over the storage period of 1, 2, 3, 5,
10, 15, 20 and 30 days is shown in Fig. 5.13. Results indicated that the TBARS
120
Fig. 5.13. Thiobarbituric acid reactive substances (TBARS) values of emulsions.
Note: Control emulsion contains gum Arabic, however, other emulsions contain
unmodified CNC (C) and lauric acid adsorbed CNC (CL). The TBARS values were
recorded over the storage periods of 1 to 5 days (a) and from 10 to 30 days (b).
concentration for the Pickering emulsion stabilized with neat CNC (C-0.5, C-1.0, C-
1.5 and C-2.0) and CL (CL-0.5, CL-1.0, CL-1.5 and CL-2.0) increased gradually over
0
0.2
0.4
0.6
0.8
1
0 1 2 3 4 5
TB
AR
S (
µm
ol/
mL
em
uls
ion
)
Storage periods (Days)
Control C-2.0 CL-2.0
0
5
10
15
20
25
30
35
10 15 20 25 30
TB
AR
S (
µm
ol/
mL
em
uls
ion
)
Storage periods (Days)
Control
C-2.0
CL-2.0
(b)
(a)
121
the storage period, recorded a significantly (p≤0.05) higher concentration of TBARS
as compared to the control sample. As not anticipated, a higher TBARS concentration
for the Pickering emulsions with CNC later conformed with mineral composition
analysis of the CNC (Table 5.1). Mineral composition analysis of the CNC revealed
the presence of a wide variety of transition metals. The higher concentration of the
TBARS for the Pickering emulsion stabilized with CNC may have been due to catalytic
effect of the associated higher concentration of the transition metals that induced the
oxidation/deterioration of hydroperoxides on the surface of the lipid droplets producing
malondialdehyde thus higher TBARS value. Since most of the processing tools
involved in the production of CNC are metallic (Nanocellulose Pilot Plant, NFL,
USDA). We assumed that the presence of transition metals in the CNC was the traces
from the involved processing equipment.
Table 5.1. Mineral contents of cellulose nanocrystals (CNC). Superscripts are the unit
values of minerals per gram of CNC.
Note: Results are mean ± standard deviation of triplicate (n=3). α – values in
nanogram (ng/g); β – values are in microgram (µg/g) and γ – values in milligram
(mg/g).
122
5.3.4. Beta-carotene stability
Since beta-carotene possesses a large number of conjugated double bonds and
is very susceptible to oxidative degradation. These conjugated bonds trigger the
oxidative degradation of beta-carotene similar to transition metals, light, heat, singlet
oxygen, etc. (Boon et al., 2010). The stability of beta-carotene during storage in the
Pickering emulsions is shown in Fig. 5.14. It was observed that beta-carotene content
for the control emulsion was significantly higher as compared to the Pickering
emulsion stabilized with neat CNC and CL. However, no significant (p≤0.05)
difference was observed between emulsion stabilized with neat CNC and CL. Since the
CNC, CL and Gum Arabic were only differences among the composition of the
emulsions. It was assumed that the loss of beta-carotene for the C-2.0 and CL-2.0 was
simply assumed due to the presence transition metals such as Fe, which is a primary
cause of the oxidative degradation of the beta-carotene, resulting formation of carotene
cation radical and ferrous iron (Boon et al., 2010). Several studies have been conducted
to ensure the stability of beta-carotene O/W emulsion using a vast number of natural
and synthetic antioxidants. Among them, the metal-chelating antioxidant, i.e., EDTA,
has shown very promising results preventing the degradation of beta-carotene (Boon et
al., 2010; Qian et al., 2012 and Liu et al., 2015).
123
Fig. 5.14. Stability of beta-carotene during storage periods.
3
5
7
9
11
0 1 2 3 5 10 15 20 30
Bet
a-c
aro
ten
e (m
g/1
00 m
L)
Storage periods (Days)
Control C-2.0 CL-2.0
124
5.4. Conclusion
Adsorption of lauric acid with cellulose nanocrystals (CL) resulted in a
physically stable beta-carotene O/W Pickering emulsion at different dilution factors,
pH levels, and storage periods. However, neat CNC (no lauric acid) maintained the
physical stability of the emulsion at different pH and during storage nonetheless
resulted in a significant (p≤0.05) increase in average particle size of the while diluted.
Results displayed that a gradual increase in the concentration of CL from 0.5 to 2.0 had
better physical stabilization activity for the Pickering emulsion, resulting in an average
particle size of 3.41±0.26, 1.53±0.17, 1.33±0.05 and 1.23±0.09 µm (CL-0.5, CL-1.0,
CL-1.5 and CL-2.0), respectively. Dilution resulted in a significant (p≤0.05) increase
in average particle size of the C-0.5, C-1.0, C-1.5 and C-2.0; however no or a moderate
increase was recorded for the CL-0.5, CL-1.0, CL-1.5 and CL-2.0. This was assumed
due to better lipophilic-lipophilic balance between oil droplets and lauric acid present
on the surface of CL, resulting in a stable emulsion. An intriguing result was noticed
during the storage of the Pickering emulsions. Results indicated that emulsion
stabilized with neat CNC and CL had significantly (p≤0.05) higher TBARS
concentration 28.19 and 29.28 µmol (C-2.0 and CL-2.0) and lower beta-carotene 4.33
and 4.02 mg/100 mL (C-2.0 and CL-2.0) as compared to the control emulsion (9.28
µmol and 6.53 mg/100 mL) stabilized with Gum Arabic. This study thus demonstrates
the potential application of adsorption of lauric acid modulating the stability of the O/W
emulsion. The study also highlights the limitation of the CNC and its consequential
cause to the lipid food system due to the presence of transition metals.
125
CHAPTER 6
DEVELOPMENT OF O/W PICKERING EMULSIONS USING LAURIC ACID-
ADSORBED CNC: AN IN VITRO GASTROINTESTINAL TRACT STUDY
6.1. Introduction
Cellulose nanocrystals (CNC), also known as crystalline nanocellulose,
nanocrystalline cellulose, or cellulose nanowhiskers, is a derivative of cellulose, which
is the most common type of polysaccharide available on the earth. CNC is a linear
structure of anhydro D-glucose units condensed through a β-1,4 glycosidic bond
(García, Gandini, Labidi, Belgacem, & Bras, 2016). Morphologically, CNC is a rod or
needle-shaped nanoparticle with a dimension of 150-200 nm long and 5-15 nm wide
(Cheng et al., 2015) and possesses up to 99% crystallinity (Abiaziem et al., 2019). The
properties of CNC include nano-scaled dimension, high crystallinity, surface hydroxyl
groups (O-H) (Natterodt et al., 2017), excellent dispersibility into an aqueous medium
(Cheng et al., 2015), high charge potential due to sulfate ions (-SO3-) (Prathapan et al.,
2016) and non-toxicity (Seabra et al., 2018), thus offering an excellent opportunity to
explore its potential applications. There have been several studies utilizing CNC in
foods (Hedjazi and Razavi, 2018; Aswathanarayan, and Vittal, 2019) and
pharmaceuticals (Ngwabebhoh et al., 2018; Low et al., 2019).
In the last few decades, the market demands have shifted towards healthy and low-
calorie foods due to increased public health concern and development of nutraceutical
and functional foods (Siro et al., 2008; Sharif and Zahid, 2018). Developing
nutraceuticals and functional foods through the Pickering emulsion process is one of
126
the more common techniques that are being used, hence the exploration of novel and
unique coating/stabilizing materials has increased (Dhakane et al., 2017; Hedjazi and
Razavi, 2018; Sharif and Zahid, 2018; Winuprasith et al., 2018). A Pickering emulsion
is a type of emulsion system that is stabilized by solid colloid particles by adsorbing
them onto the interface of two immiscible phases (Pickering, 1907). Since CNC
possesses unique characteristics of being an excellent stabilizer/emulsifier due to its
aforesaid physicochemical properties (Kalashnikova et al., 2012; Zoppe et al., 2012;
Prathapan et al., 2016; Ujala et al., 2016; Meirelles et al., 2020), several researchers
have investigated the effect of CNC on the physicochemical stability of an oil-in-water
(O/W) type emulsion (Rayner et al., 2014; Hedjazi and Razavi, 2018; Sharif and Zahid,
2018; Aswathanarayan, and Vittal, 2019). CNC in a Pickering emulsion system
adsorbed onto the interface of oil droplets, creating either electrostatic (Prathapan et
al., 2016) or steric repulsion (Zoppe et al., 2012) among the oil droplets that leads to a
stable emulsion system. Electrostatic stability is due to the presence -SO3- groups on
the surface of CNC; however, a steric repulsion is due to adsorbed CNC that limits the
coalescence/Ostwald ripening among the droplets. Adsorption of CNC onto the
interface of oil droplets may not be an easy target due to the hydrophilic nature of CNC
due to the presence of a vast number of O-H groups. However, several researchers have
found that the addition of a certain amount of NaCl (0.06%) facilitated the adsorption
of CNC particles onto the interface of oil droplets due to increased surface pressure
(Bergfreund and Fischer 2019; and Bertsch et al., 2019). The addition of NaCl also
increased the CNC-CNC interaction due to the counterion effect of sodium ions (Na+)
altering the rheological properties, e.g., increasing gel strength of aqueous phase
127
(higher viscosity). The increased gel strength of the continuous phase restricts the
mobility of the free oil droplets (no CNC on the interface), resulting in less interaction
among oil droplets, thus forming a stable emulsion (Aaen et al., 2019).
A study conducted by Bai et al. (2019a) has reported a significant increase in the oil
droplet size in the O/W Pickering emulsion stabilized with CNC while investigating
the in vitro gastrointestinal tract (GIT) fate of the Pickering emulsion. Results showed
an average increase of up to 30% in the diameter of the oil droplet at the simulated
stomach phase; nonetheless, no agglomeration of oil droplets was observed by confocal
laser scanning microscopic (CLSM) analysis. However, CLSM images recorded at the
small intestinal phase of the study depicted a clear agglomeration of the oil droplets,
thus increasing the diameter of the oil droplets. It is assumed that agglomeration of oil
droplets could have been due to a gradual dilution of the Pickering emulsion with
simulated digestive juices and the addition of counterions (Wooster, 2006; Maphosa
and Jideani, 2018). It has been reported that dilution can lead to a phase separation of
the stable Pickering emulsion due to the following reasons: (a) reduced surface
pressure, thus desorption of polymers from the interface of oil droplet plunging steric
or electrostatic repulsion among droplets and (b) weaker gel strength of the aqueous
medium thereby increasing droplets’ interaction leading to coalescence/Ostwald
ripening (Wooster, 2006; Maphosa and Jideani, 2018; Yokota et al., 2019).
CNC with hydrophobic or amphiphilic surface properties can be effectively
utilized in creating a stable Pickering emulsion (Zoppe et al., 2012; Girouard et al.,
2016; Saidane et al., 2016). However, the sustainability of the chemical modification
of CNC utilizing non-food grade organic chemicals is a serious concern (Chemat et al.,
128
2019; Spinelli et al., 2019). Prior work suggested that adsorption of amphiphilic
molecules on the interface of hydrophilic molecules can easily be achieved, resulting
in a hydrophobic surface. The adsorption of amphiphilic molecules on the interface of
the hydrophilic surface takes place due to the ligand exchange phenomenon in which
the polar group of the amphiphilic molecules replaces the aqueous molecules from the
interface of hydrophilic molecules and facilitating the adsorption (Paleos, 1969 and
Ulrich et al., 1988).
Additionally, the developed Pickering emulsion can be used for the
stabilization, fortification, and delivery of a wide variety of lipophilic nutraceuticals
(Dhakane et al., 2017; Hedjazi and Razavi, 2018; Sharif and Zahid, 2018; Winuprasith
et al., 2018). However, it is crucial to understand the physicochemical stability and fate
of the digestion of developed nutraceutical-loaded Pickering emulsions for their
potential applications.
Thus, in this work, a medium-chain saturated fatty acid named lauric acid
(C12:0) was adsorbed onto the surface of CNC and lauric acid adsorbed CNC (CL) was
used as an emulsifier to create O/W Pickering emulsion. Beta-carotene was used as
model nutraceutical. Developed Pickering emulsion was investigated for the static in
vitro GIT study. Different concentrations of dried CL viz., 0.5, 1.0, 1.5 and 2.0% (w/v)
was utilized as emulsifier. Stabilized Pickering emulsion was then passed through
various stages of the GIT such as simulated mouth phase, stomach, and small intestinal
phase. Characteristics of the Pickering emulsion such as FTIR, TEM, average particle
size, zeta potential, CLSM analysis, creaming index lipid digestion, and beta-carotene
bioaccessibility were recorded.
129
6.2. Materials and Methods
CNC with a total solid content of 11.5 to 12.5% was procured from the PDC,
University of Maine. The obtained CNC had an average particle length of 150-200 nm
and 5-20 nm wide and contained up to two percent of the surface sulfate group. Cooking
grade canola oil was purchased from the local supermarket of Bangor, Maine (Great
Value, Walmart). Lauric acid flakes (>99% pure) were purchased from Acros
Organics/Fisher Scientific, USA. Enzymes used for in vitro gastrointestinal study such
as α-amylase (from Aspergillus oryzae), pepsin (from porcine gastric mucosa: ~2500
units/mg), lipase type II (from the porcine pancreas), mucin-type III (from the porcine
stomach), porcine bile extracts, uric acid (≥99% crystalline), beta-carotene (>99%) and
Nile red (a fluorescence marker) were purchased from Sigma Aldrich, USA. Other
analytical grade solvents were purchased from Acros Organics/Fisher Scientific, USA.
6.2.1. Adsorption of lauric acid with CNC
Adsorption of lauric acid with CNC was performed dissolving 20 grams of lauric
acid flakes into 400 mL of absolute ethanol. Subsequently, 100 grams of CNC
suspension (11.5 to 12.5%) was mixed to the solution stirring at 500 rpm on a digital
magnetic stirrer plate (Isotemp™, Fisherbrand, USA). The mixture was stirred
continuously overnight at 100 rpm followed by ten times centrifugation at 21,800x g
for 10 minutes at room temperature using a super speed centrifuge (Beckman Coulter
Avanti J-E Floor, CA, USA). Obtained pallet was washed several times with the
subsequent addition of ethanol to remove the unabsorbed lauric acid. Washed pallet
was then dried under vacuum at 60 °C overnight and was considered to be lauric acid-
130
adsorbed CNC (CL). CL was later ground to a fine powder manually using mortar and
pestle and was stored into the airtight LDPE Ziplock bag at room temperature for
further use. The amount of adsorbed lauric acid was subsequently quantified on FTIR
(ABB, FTLA 2000) using a blend of different concentrations of lauric acid with dried
CNC viz., 10, 20, 30, 50, 75, 100, 150, 200 and 250 mg of lauric acid per 500 mg of
CNC (dry basis). The FTIR spectra were recorded as relative percent transmittance
(%T), which was later converted into absorbance following the equation developed by
Toft et al. (1993):
𝐴𝑏𝑠𝑜𝑟𝑏𝑎𝑛𝑐𝑒 = 2 − 𝑙𝑜𝑔 (%𝑇)
The obtained absorbance values were plotted to create a calibration curve to
calculate the amount of lauric acid adsorbed.
The morphology of the unmodified CNC (neat CNC) and CL was characterized
by transmission electron microscopy (TEM CM10, Philips/FEI, Hillsboro, Oregon,
USA). The 100x diluted samples were prepared using the drop-casting method on a
negatively stained copper grid fixed on a carbon film. After 15 minutes, images were
collected under a vacuum at 200 kV.
6.2.2. Preparation of emulsions
An oil-in-water (O/W) type Pickering emulsion was prepared by mixing 10 grams
of beta-carotene dissolved canola oil (1 mg/100 mL) into 90 grams of the aqueous
phase (CL dispersed water). The CL dispersed aqueous phase contained four different
concentrations of CL viz., 0.5, 1.0, 1.5 and 2.0%. Resulting mixtures were coded as
CL-0.5, CL-1.0, CL-1.5 and CL-2.0. Similarly, 10 grams of beta-carotene dissolved
131
canola oil was mixed into another 90 grams of aqueous phase (neat CNC dispersed
water). In this case aqueous phase contained four different concentration of neat CNC
viz., 0.5, 1.0 1.5, and 2.0% and coded as C-0.5, C-1.0, C-1.5, and C-2.0. Neat CNC
with different concentrations were used to compare the stabilization efficacy of CL on
the stability Pickering emulsion.
Oil and aqueous phase as mentioned above were mixed using a homogenizer
(Ultra-Turrax, IKA S 18 N - 19 G Dispersing Element) at 10,000 rpm for 2 minutes
and resulting mixture was considered as coarse emulsion. 0.06 g of NaCl was added to
each C-0.5, C-1.0, C-1.5, and C-2.0 as described by Bai et al. (2018); however, no NaCl
was added to the CL stabilized emulsion. To obtain a fine emulsion, resulting coarse
emulsion was subsequently sonicated for 5 minutes using an ultrasonic dismembrator
(500W, 20 kHz, Fisherbrand™ Model 505, USA) with 0.75-inch titanium alloy
microtip probe. Sonification was performed at 40 percent amplitude, maintaining the
ON and OFF-pulse time at the interval of 15 and 5 seconds (Mehmood et al., 2017).
Resulting Pickering emulsions were used for in vitro GIT study.
6.2.3. In vitro gastrointestinal tract (GIT) study
A static in vitro GIT of the Pickering emulsions was performed following the
protocol of Bai et al. (2019a) with a small adjustment. All the simulated digestive
solutions were prepared, as described in Chapter 3. Simulated digestion solutions were
prepared and preheated at 37 °C just before use. The reaction was performed in a 100
ml amber-colored Erlenmeyer flask to avoid the effect of light on the degradation of
beta-carotene.
132
6.2.3.1. Initial phase of the in vitro GIT
Before starting the in vitro GIT experiment, an initial sample was prepared by
taking 40 mL of Pickering emulsion containing 2% oil (w/w) into the flask. Samples
were incubated in a shaking water bath (JULABO, SW22, Julabo Inc., USA) at 37 °C
for 2 minutes.
6.2.3.2. Simulated saliva juice (SSJ) phase of the in vitro GIT
The SSJ phase of the in vitro GIT, also known as simulated mouth phase, was
performed by withdrawing 20 mL of a sample from the initial phase followed by adding
20 mL of preheated (37 °C) SSJ. The pH of the mixture was maintained at 6.8±0.2
using 0.1 N HCl or 0.1 M NaOH solutions. The reaction was allowed to process for 5
minutes at 37 °C with a continuous shaking speed of 100 rpm.
6.2.3.3. Simulated gastric juice (SGJ) phase of the in vitro GIT
Similar to the SSJ phase, the SGJ or simulated stomach phase of the in vitro
GIT was performed by withdrawing a 20 mL aliquot of the sample from the SSJ phase
and mixing it with 20 mL of preheated SGJ. The pH of the reaction medium was
maintained at 2.0 using 0.1 N HCl, and the digestion was allowed for 2 hours with
continuous shaking at 100 rpm.
6.2.3.4. Small-intestinal juice (SIJ) phase of the in vitro GIT
After 2 hours of digestion, a 20 mL of sample was withdrawn from the SGJ
phase into a separate flask, and pH was immediately brought to 7.0 ±0.2 using 0.1 M
NaOH. Subsequently, 1.5 mL of SIJ was added to the flask, followed by the addition
of 3.5 mL of bile salt and 2.5 mL of lipase solutions (Bai et al., 2019a). Since a pH
133
titration method was used to measure the lipid digestion during the SIJ phase of the in
vitro GIT, the pH of the reaction medium was checked carefully after the addition of
reaction solutions. The reaction was further allowed to process for 2 hours at 37 °C
with continuous shaking at 100 rpm. A replication of three for each sample was
performed. Obtained samples were subsequently investigated for their attributes, as
given below.
6.2.4. Particle size and zeta potential analysis
The average particle size and zeta potential of the Pickering emulsions were
analyzed on a DLS zeta-sizer (Zetasizer Malvern 3000 HSA). Analysis was performed
following the method of Zhang et al. (2019). In brief, samples from each phase of the
in vitro GIT study were diluted with distilled water to prevent the multiple scattering
effects during analysis. The refractive index for the canola oil was fixed at 1.465
(Przybylski, 2001) and 1.330 for water (Zhang et al., 2019).
6.2.5. Creaming index
Creaming index of the samples collected from different phases of the in vitro
GIT was analyzed following the method of Varka et al. (2010) with some
modifications. In brief, the amount of the beta-carotene in the emulsion was measured
using a multi-plate reader UV-Vis spectrophotometer (BioTek Eon, Vermont, USA) at
452 nm. One mL of sample was withdrawn from the separated phase (top layer) and
the continuous phase (bottom phase) separately into 10 mL of n-hexane, then vortexed
for 1 minute. The solutions were then stored at 4 ℃ until a clear layer of the aqueous
phase and n-hexane appeared. A 200 µl of the fraction from the top layer was placed
134
into 96 well microplates and absorbance was recorded at 452 nm. The percent creaming
index was calculated using the following equation:
𝐴𝑏𝑠𝑡𝑜𝑝
𝐴𝑏𝑠𝑡𝑜𝑡𝑎𝑙× 100
𝐴𝑏𝑠𝑡𝑜𝑡𝑎𝑙 = 𝐴𝑏𝑠𝑡𝑜𝑝 + 𝐴𝑏𝑠𝑐𝑜𝑛𝑡𝑖𝑛𝑢𝑜𝑢𝑠 𝑝ℎ𝑎𝑠𝑒
Where Abstop is the absorbance of beta-carotene in the separated oil phase, Abscontinuous
phase is the absorbance of beta-carotene present in the bottom phase.
6.2.6. Confocal laser scanning microscopic (CLSM) analysis
CLSM analysis of the Pickering emulsion obtained each phase of the in vitro
GIT study was performed staining the oil droplets with the Nile red (1 mg/1mL
ethanol) (Winuprasith et al., 2018). A 50 µL of stained emulsion sample was loaded
on a glass slide (75 x 26 x 1 mm) and covered with a glass coverslip. Images were
collected simultaneously on a high-resolution CLSM (Leica TCS SP instrument). An
excitation and emission spectra of 545 and 575 nm were used for scanning using a
20X magnification lens.
6.2.7. Determination of lipid digestion
The digestion of oil droplets of the Pickering emulsion was determined by
quantifying available free fatty acids (%) at the end of the SIJ phase of the in vitro GIT.
A pH titration method was used to quantify the free fatty acids (FFAs), as suggested
by Winuprasith et al. (2018). The obtained sample was titrated with 0.1 M NaOH until
a pH of 7.0 was achieved. Total FFAs (%) were then calculated following the number
of moles of NaOH required (titer value) to neutralize the released FFAs.
135
𝐹𝐹𝐴 (%) =𝑉𝑁𝑎𝑂𝐻 × 𝑚𝑁𝑎𝑂𝐻 × 𝑀𝐿𝑖𝑝𝑖𝑑
𝑊𝐿𝑖𝑝𝑖𝑑 × 2
Where VNaOH is the consumed volume of NaOH (mL) during the titration, mNaOH is the
molarity of the NaOH used (0.1 M), MLipid is the molecular weight of the canola oil
(~876.6 g/mole) and WLipid is the total weight of lipid initially present in the reaction
vessel.
6.2.8. Beta-carotene bioaccessibility
The bioaccessibility of the beta-carotene in the Pickering emulsion was
estimated by the method of Winuprasith et al. (2018). The bioaccessibility is defined
as the percent of beta-carotene available in the form of mixed micelle as compared to
the digesta (total digest resulting after the small intestine phase) for its absorption into
the small intestine (Marze, Meynier, & Anton, 2013). A 5 mL sample of the Pickering
emulsions collected from the SIJ phase was transferred into a 15 mL centrifuge tube
and centrifuged at 1,135x g for 50 min at 20 ºC. The top clear yellowish layer from the
centrifuge tube was considered as the mixed micelle from which an aliquot of 1 mL
was mixed with 5 mL of isooctane and ethyl alcohol (1:3) to extract the beta-carotene.
Mixture was then centrifuged again for 15 minutes at 205x g. Absorbance of the beta-
carotene from the supernatant was recorded at 452 nm on a multi-plate reader UV-Vis
spectrophotometer ((BioTek Eon, Vermont, U.S.A)). The bioaccessibility was then
calculated using the equations below:
𝐵𝑖𝑜𝑎𝑐𝑐𝑒𝑠𝑠𝑖𝑏𝑖𝑙𝑖𝑡𝑦 (%) = (𝐶𝑀𝑖𝑐𝑒𝑙𝑙𝑒
𝐶𝐷𝑖𝑔𝑒𝑠𝑡𝑎) × 100
136
Here, CMicelle is the beta-carotene in the mixed micelle phase; however, CDigesta is the
total beta-carotene in the digesta obtained at the end of the SIJ phase of the in vitro
GIT.
6.2.9. Statistical analysis
Date collected in triplicate were analyzed using a Tukey’s (HSD) post hoc test
on SAS® Studio (Version 9.4, University edition) to identify the significant differences
among the mean values. Analysis of Variance (ANOVA) was used to determine a
significant effect among the sample types and the different stages of the GIT at the
level of p≤0.05.
6.3. Results and Discussion
6.3.1. Characterization of lauric acid adsorbed CNC (CL)
Fourier transforms infrared (FTIR) spectra shown in Fig. 6.1 confirmed the
adsorption of lauric acid onto the surface of CNC. The characteristic peak of the C-H
group of lauric acid between 2800 to 2960 cm-1 confirmed the adsorption of lauric acid.
Moreover, the peak at 1694 cm-1 is due to the stretching vibration of the C=O group of
the lauric acid (Shifu et al., 1989). Using a calibration curve plotted against different
concentrations of the lauric acid, the amount of lauric acid adsorbed onto the surface
of CNC was quantified as 78.62 mg/500 mg of dried CNC.
137
Fig. 6.1. FTIR spectra of cellulose nanocrystal (CNC), lauric acid (LA) and lauric acid
adsorbed CNC (CL).
6.3.2. Morphology of CNC and CL
The structure of CNC and CL was characterized by transmission electron
microscopy (TEM). TEM images are shown in Fig. 6.2 clearly showed that the CNC
particles had rod/spindle-shaped and were uniformly distributed. A previous study
conducted by Bai et al. (2019a) has reported the rod-like structure of the neat CNC
recorded on AFM analysis; however, it is important to understand that the morphology
and diameter of the CNC may vary depending upon the type of analytical tools used
such as TEM, AFM or SEM. Data collected on the Zeta-sizer showed the average
138
Fig. 6.2. Transmission Electron Microscopic (TEM) image of CNC (a) and lauric acid
adsorbed CNC (b)
particle sizes for the CNC and CL were 176±7 and 224±11 nm; however, the zeta
potential values were -52±3 and -54±5 mV. Larger average particle size for CL can be
due to the adsorption of lauric acid on the surface of CNC, thereby widening the
diameter.
6.3.4. In vitro GIT fate of emulsions
6.3.3.1. Initial phase
Initially, the Pickering emulsion was diluted to 2% and incubated for 2 minutes
at 37 °C prior to investigating the fate of Pickering emulsion under GIT conditions.
Data shown in Fig. 6.3, revealed that the average particle size of the Pickering emulsion
stabilized with CL i.e., CL-1.0, CL-1.5 and CL-2.0 had significantly (p≤0.05) smaller
average particle sizes of 1.52±0.15, 1.31±0.03, and 1.21±0.22 µm except for the CL-
0.5 (3.82±0.17 µm) as compared to the emulsion stabilized with neat CNC, 3.14±0.09,
2.46±0.15, 2.18±0.22 and 2.21±0.08 µm (C-0.5, C-1.0, C-1.5 and C-2.0). It has been
139
Fig. 6.3. Effect of in vitro gastrointestinal tract (GIT) phases on average particle size
of the emulsions.
Note: Emulsion stabilized with different concentration of unmodified CNC (i.e., C-0.5,
where C stand for neat CNC and 0.5 is the concentration) and lauric acid adsorbed CNC
(i.e., CL-0.5, where CL stand for lauric adsorbed CNC and 0.5 is the concentration).
The upper-case letters denote significant differences (p ≤0.05) among sample types;
however, small letters denote significant differences (p≤0.05) among in vitro
gastrointestinal tract (GIT) phases. SSJ - simulated saliva juice, SGJ - simulated gastric
juice and SIJ – simulated small-intestinal juice.
mentioned in Chapter 5 that that larger mean particle size for the C-0.5, C-1.0, C-1.5
and C-2.0 was due to the following reasons: firstly, increased packing density of CNC
at the oil droplet interface due to increased surface pressure in the presence of NaCl
leading to increased particle diameter and secondly, NaCl can increases CNC-CNC
interactions in the aqueous phase due to presence of Na+ cations resulting bulkier and
aggregated CNC particles (Bergfreund & Fischer, 2019 and Bertsch et al., 2019).
However, smaller mean particle sizes for the CL-1.0, CL-1.5 and CL-2.0 can be due to
140
thinner packing density of CL at the oil droplets’ interface facilitated by hydrophobic-
hydrophobic interaction rather NaCl-induced interaction and adsorption onto the oil
interface (Zoppe et al., 2012; Girouard et al., 2016; Saidane et al. ,2016).
The data shown in Fig 6.4 are the average zeta potential values of the Pickering
emulsion. Results revealed that the increase in the concentration of CNC and CL had
no significant effect (p>0.05) on the zeta potential of the Pickering emulsion. However,
a significant difference was observed between the Pickering emulsion with CNC and
CL. A comparatively higher zeta potential value of -53.53±5.39 to -50.29±2.11 mV
was recorded for the Pickering emulsion with CL than for the zeta potential value of
the Pickering emulsion with CNC, which ranged from -47.41±2.04 to -48.32±4.41 mV.
Values were comparable with a zeta potential of Pickering emulsion stabilized by CNC
that were reported by Bai et al. (2019a). A higher zeta potential value for the Pickering
emulsion with CL was presumed due to the presence of lauric acid on the surface of
CNC.
6.3.3.2. Simulated saliva juice (SSJ) phase
Incubated Pickering emulsions from the initial stage were exposed to the SSJ
phase of the GIT. Average particle size data shown in Fig. 6.3 displayed an
insignificant (p≥0.05) increase in the average particle size of Pickering emulsion with
CNC from the initial phase to the SSJ phase. A similar trend was observed for the
Pickering emulsion with CL, resulting in an insignificant increase in the average
particle size. Results agreed with the findings of Bai et al. (2019a), who reported a
negligible increase in the mean particle size of Pickering emulsion with CNC.
141
Fig. 6.4. Effect of in vitro gastrointestinal tract (GIT) phases on zeta-potential of
emulsions.
Note: Emulsions stabilized with CNC (i.e., C-0.5, where C stand for neat CNC and 0.5
is the concentration) and lauric acid adsorbed CNC (i.e., CL-0.5, where CL stand for
lauric adsorbed CNC and 0.5 is the concentration). The upper-case letters denote
significant differences (p ≤0.05) among sample types; however, small letters denote
significant differences (p≤0.05) among in-vitro gastrointestinal tract (GIT) phases. SSJ
- simulated saliva juice, SGJ - simulated gastric juice and SIJ – simulated small-
intestinal juice.
However, Winuprasith et al. (2018) reported a slight increase in the mean particle size
of the Pickering emulsion stabilized with whey protein isolates (WPI). An increase in
the mean particle size was hypothesized due to the flocculation of lipid droplets
instigated by deposition of anionic proteins of SSJ, i.e., mucin on the surface of lipid
droplets initiating the bridge flocculation (Sarkar et al., 2009). It was observed that the
C-0.5 and CL-0.5 had a comparably larger average particle size (p≤0.05) than the other
types of Pickering emulsions. CLSM images in Fig. 6.5 depicted that the larger particle
Aa
Ab
Ac
Ab
Aa
Ab
Ac
Ab
Aa
Ab
Ac
Ab
Aa
Ab
Ac
Ab
Ba
Bb
Ac
Bd
Ba
Bb
Ac
Bd
Ba
Bb
Ac
Bd
BaBb
Ac
Bd
-60
-50
-40
-30
-20
-10
0
10
Initial SSJ SGJ SIJ
Zet
a p
ote
nti
al
(mV
)GIT Phases
C-0.5 C-1.0 C-1.5
C-2.0 CL-0.5 CL-1.0
CL-1.5 CL-2.0
142
Fig. 6.5. Confocal laser scanning microscopic images of emulsions.
Note: Unmodified CNC and lauric acid adsorbed CNC stabilized (concentration =
0.5, 1.0, 1.5 and 2.0%) emulsions. Images shows the effect of in vitro gastrointestinal
tract stages on the oil droplet behavior. Scale bar is 20 µm. SSJ - simulated saliva
juice, SGJ - simulated gastric juice and SIJ – simulated small-intestinal juice.
size for the C-0.5 and CL-0.5 could be due to partial flocculation of the oil droplets. A
similar result was observed by Winuprasith et al. (2018) who reported flocculation of
some WPI stabilized lipid droplets at the mouth stage of the GIT. Results shown in Fig.
6.4 displayed a significant (p≤0.05) slight decrease in the average zeta potential of the
Pickering emulsions. It was observed that the negative zeta potential of the particles,
which was recorded -47.41±2.04 to -48.32±4.41 mV at the initial phase, dropped
significantly (p≤0.05) in the range between to -34-42±3.18 to -37.42±2.05 mV for the
Pickering emulsion with neat CNC. A similar trend was observed for the Pickering
emulsion with CL, which initially ranged from -53.53±5.39 to -50.29±2.11 mV
declined to -44.16±1.85 to 46.42±5.21 mV. A decline in the zeta potential for the
particle in the SSJ phase can be assumed due to the electrostatic screening effect of
143
counterions present in the saliva juice (Israelachvili, 2011). Additionally, adsorption of
the anionic polymer from the saliva juice components i.e., mucin, can also decrease the
zeta potential value by masking the surface potential of the particles (Singh & Sarkar,
2011; van Aken et al., 2011).
6.3.3.3. Simulated gastric juice (SGJ) phase
A considerable increase in the average particle size of the Pickering emulsion
was recorded at the end of the SGJ phase. From Fig. 6.3, it can be seen that the average
particle increased significantly (P≤0.05) by approximately 115% for the C-0.5 and by
approximately 140% for the C-1.0, C-1.5 and C-2.0, resulting up to an average particle
size of 7.26±0.23 (C-0.5), 6.23±0.32 (C-1.0), 6.34±0.14 (C-1.5) and 4.95± 0.08 nm (C-
2.0), respectively. A similar effect of the SGJ phase was observed on the average
particle size of the Pickering emulsion stabilized with CL, which accounted for an
increase by approximately 140% for the CL-0.5 and CL-1.0, however, by
approximately 80% for the CL-1.5 and CL-2.0. Resulting an average particle size of
8.78±0.33 (CL-0.5), 4.04±0.05 (CL-1.0), 2.32±0.16 (CL-1.5) and 2.44±0.23 nm (CL-
2.0), respectively. Bai et al. (2019a) has reported a slight increase in the mean particle
size of the Pickering emulsion stabilized with CNC at the stomach phase of the GIT,
recorded an increase by approximately 30%; however, a study conducted by
Winuprasith et al. (2018) reported an insignificant effect of the stomach phase on the
average particle size of the Pickering emulsion stabilized with CNF.
An increase in the average particle of the Pickering emulsion with CNC viz.,
C-0.5, C-1.0, C-1.5 and C-2.0 was hypothesized due to following three phenomena:
firstly, a lower pH of the stomach phase can lead to the protonation (H+) of the sulfate
144
anions (OSO3-) present on the surface of the CNC leading to the agglomeration of the
CNC (Varanasi et al., 2018) thus increased average particle size. Secondly, the
protonation of CNC present on the interface of lipid droplets can lead to a reduced
electrostatic repulsion among the lipid droplets, thus causing flocculation of the lipid
droplets. This effect can also be seen from the CLMS results of Bai et al. (2019b), who
have reported the flocculation of lipid droplets stabilized with CNC at pH 2.0. The third
reason for an increased average particle size of the Pickering emulsion is destabilization
of gel strength (3D network) of the continuous phase (aqueous phase) due to gradual
dilution, leading to the weaker gel strength. The weaker gel strength allows lipid
droplets to interact with other lipid droplets with and coalesce or flocculate. It has been
reported that the presence of NaCl in unmodified CNC stabilized Pickering emulsion
increases the gel strength of the continuous phase, limiting the mobility and interaction
of lipid droplets, therefore stable emulsion (Aaen et al., 2019). Indeed, CLMS images
displayed a large amount of flocculation and coalescence of lipid droplets for the
Pickering emulsion with CNC, i.e., C-0.5, C-1.0, C-1.5 and C-2.0 at SGJ phase of the
GIT (Fig. 6.5). However, a similar effect of the SGJ phase on the Pickering emulsion
with CL i.e., CL-0.5 and CL-1.0, was also noticed. From the CLSM images, it was
noticed that a gradual increase in the concentration of CL from 0.5 to 2.0 maintained
the stability of Pickering emulsion against the SGJ phase. This can simply be assumed
that a higher concentration of CL can facilitate a complete coverage of a lipid droplet’s
interface. Moreover, lauric acid adsorbed on CL developed an amphiphilic surface,
creating a Pickering emulsion that was stable against dilution and lower pH (details in
schematic diagram Fig. 6.6).
145
Fig. 6.6. Schematic illustration of fate of emulsions in small intestine (not to scale).
Results from the zeta potential analysis displayed a significant (p≤0.05) decline
in the zeta potential of the Pickering emulsions after the SGJ phase of the GIT. Zeta
potential values were changed from negative to slightly positive zeta potential (Fig.
6.4). A change in zeta potential from negative to positive can be due to the charge
reversal phenomenon triggered by lower stomach pH (2.0), resulting in protonation of
the sulfate ions present on the surface of CNC. The charge reversal or charge inversion,
either from negative to positive or positive to negative, is a phenomenon of altering the
electric behavior of a particle with the addition of an excessive number of the opposite
ions, which leads to the overcharge (Schubert et al., 2019). Charge reversal occurs
below or above the isoelectric point of the CNC (pKa = 1.9) (Varanasi et al., 2018).
146
Despite extremely low zeta potential, Pickering emulsions, i.e., CL-1.5 and CL-
2.0, had good stability against flocculation and coalescence as compared to the C-0.5,
C-1.0, C-1.5, C-2.0, CL-0.5 and CL-1.0. This finding confirmed that the stability of
CL-1.5 and CL-2.0 at the SGJ phase was due to steric repulsion rather electrostatic
effects (Zoppe et al., 2012 and Meirelles et al., 2020).
Results from the creaming index showed a significant (p≤0.05) increase in the
creaming index from 2-3% (SSJ) to 70-80% (SGJ) for the C-0.5, C-1.0, C-1.5, C-2.0
and CL-0.5. However, a creaming index of up to 23% for CL-1.0 and 5% for the CL-
1.5 and CL-2.0 was recorded (Fig 6.7). This finding again confirmed the strong stability
of CL-01.5 and CL-2.0 against the SGJ phase of the GIT.
Figure 6.7. Effect of in vitro gastrointestinal tract (GIT) phases on creaming index of
emulsions.
Note: Emulsions stabilized with unmodified CNC (C) and lauric acid adsorbed CNC
(CL) with concentrations of 0.5, 1.0, 1.5 and 2.0% (solid basis).
0
20
40
60
80
100
Initial SSJ SGJ SIJ
Cre
am
ing i
nd
ex (
%)
GIT Phases
C-0.5 C-1.0
C-1.5 C-2.0
CL-0.5 CL-1.0
147
6.3.3.4. Simulated small-intestinal juice (SIJ) phase
Similar to the effect of SGJ phase on the Pickering emulsions, a gradual
increase in the average particle size was recorded after the SIJ phase of GIT (Fig. 6.3).
An increase in the particle size for the Pickering emulsion with CNC viz., C-0.5, C-1.0,
C-1.5 and C-2.0 was simply assumed to be due to the effect of continuous dilution with
simulated digestive juices (Winuprasith et al., 2018 and Bai et al., 2020a). As it is
mentioned in the methods (sub-section 6.2.3), a 20 mL of Pickering emulsion mixed
with 20 mL of SSJ and a fraction of 20 mL from the SSJ was further mixed with 20
mL of SGJ. Further, 20 mL from the SGJ phase was mixed with a total of 7.5 mL of
SIJ (1.5 SIJ + 3.5 mL bile juice + 2.5 lipase solution). The addition of this much
digestive juice can cause substantial dilution of a Pickering emulsion leading to the loss
of the initial arrangement of the CNC-CNC and CNC-lipid droplets (Fig. 6.6). CLSM
images clearly displayed flocculation and coalescence of lipid droplets stabilized with
CNC at all the concentrations and lower concentrations of the CL. From these results,
it can be inferred that the dilution of Pickering emulsion may have destabilized the
complex structure of the Pickering structure leading to the flocculation/coalescence of
droplets. In contrast to the above findings, the flocculation/coalescence of the lipid
droplets for the Pickering emulsion stabilized with a higher concentration of CL i.e.,
CL-1.5 and CL-2.5 were quite stable against dilution (Fig. 6.5). A stable lipid droplet
for the CL-1.5 and CL-2.0 against dilution can be due to adsorbed CL onto the interface
of lipid droplets creating steric repulsion (Zoppe et al., 2012). Similarly, Bai et al.
(2019a) have reported a significant increase in the average particle size of the Pickering
emulsion stabilized with CNC during the small intestinal phase of the GIT. An increase
148
in the average particle size was assumed to be due to the fusion of undigested lipid
droplets, the formation of large, aggregated vesicles, and the association of CNC-
micelle with present calcium soap. In contrast to these findings, Winuprasith et al.
(2018) have reported a significant decrease in the average particle size of the Pickering
emulsion stabilized with CNF. A reduction in the average particle size at the small
intestinal phase attributed to the digestion of lipid droplets reducing the diameter and
the formation of a complex mixture of a micelle, small vesicle and calcium soap, which
reflected the light scattering pattern of the samples (McClements et al., 2009).
The zeta potential of the Pickering emulsion reverted to negative when
introduced into the SIJ phase of the GIT, resulting in the average zeta potential of up
to -34.78±5.26 mV for the Pickering emulsion stabilized with CNC. However, up to -
25.71±4.22 mV occurred for the emulsion stabilized with CL (Fig. 6.4). The anionic
zeta potential of the Pickering emulsion at the SIJ phase can be due to the following
reasons: a) the digestion of lipid droplets released anionic molecules such as free fatty
acids that contributed the negative zeta potential, b) the SIJ phase also contained several
anionic molecules of bile extract such as bile salts and phospholipids can be absorbed
on the lipid droplets, creating a negative zeta potential and c) neutralization of pH of a
sample from SGJ phase from 2.0 to 7.0 can lead to the CNC becoming anionic again
above its isoelectric point (pKa = 1.9) (Varanasi et al., 2018). Similar results were
reported by Winuprasith et al. (2018) and Bai et al. (2019a) during in vitro GIT studies
of O/W Pickering emulsion stabilized with CNF and CNC. Results also inferred that
the lower concentration of the CNC or CL had higher zeta potential value (Fig. 6.4). It
149
was assumed that the lower concentration of CNC or CL was due to a rate of higher
lipid digestion, thus a higher amount of released free fatty acids.
6.3.3.5. Lipid digestion
Results shown in Fig 6.8 displayed that the Pickering emulsion containing a lower
amount of CNC or CL had increased lipid digestion, releasing a higher amount of free
fatty acids (FFA) accounted for a total FFA of 73.35±3.29% for C-0.5, 67.27±3.26%.
However, no significant (p>0.05) difference was observed among the FFA values of
C-1.0, C-1.5 and C-2.0. Similarly, a total FFA of 68.27±2.41% for the CL-0.5 and
56.66±1.17% for the CL-1.0 was recorded and an insignificant (p>0.05) difference
between CL-1.5 and CL-2.0 was observed. Results showed that the Pickering stabilized
with CNC had slightly higher lipid digestion than the emulsion stabilized with CL. It
was hypothesized that the higher lipid digestion for the Pickering emulsion stabilized
with CNC can be due to higher lipase and lipid droplet interaction because dilution of
a stable Pickering emulsion can result in a thinner/weaker gel strength of the continuous
phase, disturbing the arrangement of CNC around the interface of lipid droplets, thus
more interfaces available for the lipase activity (Fig. 6.6). However, dilution may not
have affected the adsorbed CL onto the interface of lipid droplets less, thus limited
lipase activity (Fig. 6.6). CL contained amphiphilic molecules on its surface that can
facilitate better interfacial interaction as compared to the CNC (Paleos, 1969 and Ulrich
et al., 1988). Digestibility of a vitamin D-loaded soybean oil Pickering emulsion
stabilized with whey protein isolate (concentration 0.7%) and CNF (concentration 0.1-
0.7%) has been studied by Winuprasith et al. (2018), reported >90% and 75-85%
release of FFA at the small intestinal phase of GIT. However, Bai et al. (2019a) found
150
a total FFA release that ranged from 40-75% for the Pickering emulsion stabilized with
CNC (concentration 0.1 to 1.0%) to >95% for the Pickering emulsion stabilized with
gum arabic. Findings inferred that the CNC adsorbed onto the interface of lipid droplets
limited the lipase activity, reducing the lipid digestion.
Fig. 6.8. Release of free fatty acids during the small intestinal phase.
Note: Emulsion stabilized with neat CNC (C) and lauric acid adsorbed CNC (CL) with
different concentrations of 0.5, 1.0, 1.5 and 2.0% (solid basis). 2% of lauric acid
adsorbed CNC with no emulsion (CL-2.0*) was taken to observe the release of fatty
acid from adsorbed CNC. The alphabets denote significant differences (p ≤0.05) among
sample types.
6.3.3.6. Bioaccessibility of beta-carotene
Beta-carotene was used as a model nutraceutical to explore the influence of
CNC and CL on the bioaccessibility. Results shown in Fig. 6.8 and Fig. 6.9 displayed
an apparent relationship between the degree of lipid digestion and beta-carotene
a
b bb
a
cd d
v
0
20
40
60
80
100
C-0.5 C-1.0 C-1.5 C-2.0 CL-0.5 CL-1.0 CL-1.5 CL-2.0 CL-2.0*
Fre
e fa
tty a
cid
(%
)
Sample types
151
bioavailability. The Pickering emulsion with higher lipid digestion had a higher beta-
carotene bioaccessibility, and so decreased lipid digestion had lower bioaccessibility.
It is well understood that higher the degree of lipid digestion, the more the mixed
micelle formation, thus higher bioaccessibility (Winuprasith et al., 2018). The
application of CNC or CL could significantly limit the bioaccessibility of nutraceuticals
by arresting the lipid digestion process.
Fig. 6.9. Bioaccessibility of beta-carotene.
Note: Alphabet letters denote significant differences (p ≤0.05) among emulsions.
ab
bc
b
de e
0
20
40
60
80
100
C-0.5 C-1.0 C-1.5 C-2.0 CL-0.5 CL-1.0 CL-1.5 CL-2.0
Bio
acc
essi
bil
ity (
%)
Sample types
152
6.4. Conclusion
An O/W type Pickering emulsion containing CNC or lauric acid adsorbed CNC
(CL) has good potential to stabilize lipid droplets by coating the interfacial area.
Adsorption of CNC or CL onto the interface of lipid droplets created a good
electrostatic and steric repulsion maintaining the stability of stabilized Pickering
emulsion during initial and mouth phases of the in vitro GIT study. However, a
substantial flocculation/coalescence of the lipid droplets was observed for the Pickering
emulsion stabilized with CNC during gastric and small intestinal phases of the GIT.
Flocculation or coalescence of the lipid droplets was confirmed with CLSM. In contrast
to the flocculation/coalescence of lipid droplets for the Pickering emulsion stabilized
with CNC, it was observed that CL with a concentration of above 1% displayed a
potential maintaining the stability of lipid droplets through the GIT phases. CL
adsorbed onto the interface of lipid droplets showed a strong steric repulsion at the
gastric phase even though the zeta potential was below zero. Pickering emulsion with
CL had lower lipid digestion as compared to the Pickering emulsion stabilized with
CNC. Similarly, the bioaccessibility of beta-carotene was found to be lower for the
emulsion containing CL as compared to the CNC as compared to the emulsion
stabilized with CNC. Study concluded that lauric acid-adsorbed CNC be effectively
utilized to create a stable emulsion through GIT limiting lipid digestion; however, it
may not be a suitable emulsifier for developing Pickering emulsions to deliver a
nutraceutical for absorption in the small intestine.
153
CHAPTER 7
OVERALL CONCLUSIONS AND RECOMMENDATIONS
This study inferred that the CNC as a biopolymer could significantly be utilized as an
emulsifier or stabilizer for the lipid carriers. However, the surface modification of the
CNC by means of either chemical or physical is needed. A physical modification of
CNC by adsorbing a compatible molecule such as polyethylene glycol (PEG) or
medium-chain fatty acids, i.e., lauric acid on CNC's surface, can add the value to
cellulose nanomaterials industry. CNC modified via adsorption of PEG facilitated the
re-dispersion of the dried CNC into an aqueous medium, and the stabilization of
phycobiliprotein loaded liposomes. Likewise, adsorption of lauric acid on the surface
of CNC (CL) created a stable O/W Pickering emulsion and impede the coalescence of
the beta-carotene loaded lipid droplets. Unlike wise, the Pickering emulsion stabilized
by neat CNC, CL preserved the original particle size of the emulsion during dilution
and in vitro gastrointestinal digestion process. Moreover, it was observed that the CL
impeded the lipolysis process of the beta-carotene loaded O/W emulsion resulting in a
decreased bioaccessibility of the beta-carotene. It was concluded that the modified
CNC might not be a suitable candidate for the encapsulation and delivery of
nutraceuticals due to its hypo-lipolysis activity. However, modified CNC can be used
to extend the rate and degree of lipolysis into the small intestine, hence a sustained
release of the loaded nutraceuticals. CL can also be utilized as a potential emulsifier in
designing low-calorie functional foods. Since lauric acid is an amphiphilic, ethanol-
soluble molecule, adsorption of ethanol-soluble antioxidants on CNC’s surface can
154
facilitate the hydrophobic surface with antioxidant property, which can enhance the
oxidative stability of the emulsion.
These processes may be impractical to implement commercially due to cost and
potential legal barriers. Future research on the adsorptive modification of CNC must
focus on the use of food-grade solvents and other reagents that will be accepted by the
Food and Drug Administration. Additional research is needed in animal and human
trials to verify the biocompatibility/toxicity of the modified CNC as well as the
bioavailability and efficacy of nutraceuticals encapsulated by CNC versus other means
of delivery.
155
REFERENCES
Aaen, R., Brodin, F. W., Simon, S., Heggset, E. B., & Syverud, K. (2019). Oil-in-water
emulsions stabilized by cellulose nanofibrils-The effects of ionic strength and
pH. Nanomaterials, 9(2), 259.
Abiaziem, C. V., Williams, A. B., Inegbenebor, A. I., Onwordi, C. T., Ehi-Eromosele,
C. O., & Petrik, L. F. (2019). Preparation and characterisation of cellulose nanocrystal
from sugarcane peels by XRD, SEM and CP/MAS 13C NMR. In Journal of Physics:
Conference Series (Vol. 1299, No. 1, p. 012123). IOP Publishing.
Aditya, N. P., Espinosa, Y. G., & Norton, I. T. (2017). Encapsulation systems for the
delivery of hydrophilic nutraceuticals: Food application. Biotechnology
Advances, 35(4), 450-457.
Alam, K., Ahmed, M., Akter, S., Islam, N., & Eun, J. B. (2009). Effect of
carboxymethylcellulose and starch as thickening agents on the quality of tomato
ketchup. Pakistan Journal of Nutrition, 8(8), 1144-1149.
Alamed, J., McClements, D. J., & Decker, E. A. (2006). Influence of heat processing
and calcium ions on the ability of EDTA to inhibit lipid oxidation in oil-in-water
emulsions containing omega-3 fatty acids. Food Chemistry, 95(4), 585-590.
Al-Bukhaitia, W. Q., Nomana, A., & Wanga, H. (2018). Emulsions: Micro and nano-
emulsions and their applications in industries - A mini-review. International Journal
of Agriculture Innovations and Research, 7(1), 2319-1473.
Allen, T. M., Hansen, C., Martin, F., Redemann, C., & Yau-Young, A. (1991).
Liposomes containing synthetic lipid derivatives of poly (ethylene glycol) show
prolonged circulation half-lives in vivo. Biochimica et Biophysica Acta (BBA)-
Biomembranes, 1066(1), 29-36.
Amalraj, A., Gopi, S., Thomas, S., & Haponiuk, J. T. (2018, August). Cellulose
Nanomaterials in biomedical, food, and Nutraceutical applications: A review.
In Macromolecular Symposia (Vol. 380, No. 1, p. 1800115).
156
Angkuratipakorn, T., Sriprai, A., Tantrawong, S., Chaiyasit, W., & Singkhonrat, J.
(2017). Fabrication and characterization of rice bran oil-in-water Pickering emulsion
stabilized by cellulose nanocrystals. Colloids and Surfaces A: Physicochemical and
Engineering Aspects, 522, 310-319.
Aoki, A., Akaboshi, H., Ogura, T., Aikawa, T., Kondo, T., Tobori, N., & Yuasa, M.
(2015). Preparation of pH-sensitive anionic liposomes designed for drug delivery
system (DDS) application. Journal of Oleo Science, 64(2), 233-242.
Ashby, N. P., & Binks, B. P. (2000). Pickering emulsions stabilized by Laponite clay
particles. Physical Chemistry Chemical Physics, 2(24), 5640-5646.
Aswathanarayan, J. B., & Vittal, R. R. (2019). Nanoemulsions and their potential
applications in food industry. Frontiers in Sustainable Food Systems, 3(95), 1-21.
Bai, L., Huan, S., Xiang, W., & Rojas, O. J. (2018). Pickering emulsions by combining
cellulose nanofibrils and nanocrystals: Phase behavior and depletion
stabilization. Green Chemistry, 20(7), 1571-1582.
Bai, L., Lv, S., Xiang, W., Huan, S., McClements, D. J., & Rojas, O. J. (2020a). Oil-
in-water Pickering emulsions via microfluidization with cellulose nanocrystals: 2. In-
vitro lipid digestion. Food Hydrocolloids, 96, 709-716.
Bai, L., Lv, S., Xiang, W., Huan, S., McClements, D. J., & Rojas, O. J. (2020b). Oil-
in-water Pickering emulsions via microfluidization with cellulose nanocrystals: 1.
Formation and stability. Food Hydrocolloids, 96, 699-708.
Bally, M., Bailey, K., Sugihara, K., Grieshaber, D., Voros, J., & Stadler, B. (2010).
Liposome and lipid bilayer arrays towards biosensing applications. Small, 6(22), 2481-
2497.
Banerjee, P., & Ray, D. P. (2019). Functional food: A brief overview. International
Journal of Bioresource Science, 6(2), 57-60.
Bao, C., Jiang, P., Chai, J., Jiang, Y., Li, D., Bao, W., ... & Li, Y. (2019). The delivery
of sensitive food bioactive ingredients: Absorption mechanisms, influencing factors,
encapsulation techniques and evaluation models. Food Research International, 120,
130-140.
157
Bekasova, O. D., Borzova, V. A., Shubin, V. V., Kovalyov, L. I., Stein-Margolina, V.
A., & Kurganov, B. I. (2016). An increase in the resistance of R-phycoerythrin to
thermal aggregation by silver nanoparticles synthesized in nanochannels of the
pigment. Applied Biochemistry and Microbiology, 52(1), 98-104.
Beloqui, A., Solinís, M. Á., Rodríguez-Gascón, A., Almeida, A. J., & Préat, V. (2016).
Nanostructured lipid carriers: promising drug delivery systems for future
clinics. Nanomedicine: Nanotechnology, Biology and Medicine, 12(1), 143-161.
Bennett, A., & Bogorad, L. (1973). Complementary chromatic adaptation in a
filamentous blue-green alga. The Journal of Cell Biology, 58(2), 419-435.
Bergfreund, J., Sun, Q., Fischer, P., & Bertsch, P. (2019). Adsorption of charged
anisotropic nanoparticles at oil-water interfaces. Nanoscale Advances, 1(11), 4308-
4312.
Berton-Carabin, C. C., & Schroën, K. (2015). Pickering emulsions for food
applications: background, trends, and challenges. Annual Review of Food Science and
Technology, 6, 263-297.
Bertsch, P., & Fischer, P. (2020). Adsorption and interfacial structure of nanocelluloses
at fluid interfaces. Advances in Colloid and Interface Science, 276,102089.
Boon, C. S., McClements, D. J., Weiss, J., & Decker, E. A. (2010). Factors influencing
the chemical stability of carotenoids in foods. Critical Reviews in Food Science and
Nutrition, 50(6), 515-532.
Braga, A. R. C., Figueira, F. D. S., Silveira, J. T. D., Morais, M. G. D., Costa, J. A. V.,
& Kalil, S. J. (2016). Improvement of Thermal Stability of C‐Phycocyanin by
Nanofiber and Preservative Agents. Journal of Food Processing and
Preservation, 40(6), 1264-1269.
Brinkmann, A., Chen, M., Couillard, M., Jakubek, Z. J., Leng, T., & Johnston, L. J.
(2016). Correlating cellulose nanocrystal particle size and surface
area. Langmuir, 32(24), 6105-6114.
Burdock, G. A., Carabin, I. G., & Griffiths, J. C. (2006). The importance of GRAS to
the functional food and nutraceutical industries. Toxicology, 221(1), 17-27.
158
Cagnasso, M., Boero, V., Franchini, M. A., & Chorover, J. (2010). ATR-FTIR studies
of phospholipid vesicle interactions with α-FeOOH and α-Fe2O3 surfaces. Colloids
and Surfaces B: Biointerfaces, 76(2), 456-467.
Calabrese, V., Courtenay, J. C., Edler, K. J., & Scott, J. L. (2018). Pickering emulsions
stabilized by naturally derived or biodegradable particles. Current Opinion in Green
and Sustainable Chemistry, 12, 83-90.
Caracciolo, G. (2015). Liposome–protein corona in a physiological environment:
challenges and opportunities for targeted delivery of nanomedicines. Nanomedicine:
Nanotechnology, Biology and Medicine, 11(3), 543-557.
Carocho, M., Barreiro, M. F., Morales, P., & Ferreira, I. C. (2014). Adding molecules
to food, pros and cons: A review on synthetic and natural food
additives. Comprehensive Reviews in Food Science and Food Safety, 13(4), 377-399.
Castangia, I., Manca, M. L., Catalán-Latorre, A., Maccioni, A. M., Fadda, A. M., &
Manconi, M. (2016). Phycocyanin-encapsulating hyalurosomes as carrier for skin
delivery and protection from oxidative stress damage. Journal of Materials Science:
Materials in Medicine, 27(4), 75.
Chemat, F., Abert-Vian, M., Fabiano-Tixier, A. S., Strube, J., Uhlenbrock, L.,
Gunjevic, V., & Cravotto, G. (2019). Green extraction of natural products. Origins,
current status, and future challenges. TrAC Trends in Analytical Chemistry, 118, 248-
263.
Chen, C., & Tripp, C. P. (2008). An infrared spectroscopic based method to measure
membrane permeance in liposomes. Biochimica et Biophysica Acta (BBA)-
Biomembranes, 1778(10), 2266-2272.
Chen, Z., Kaplan, D. L., Yang, K., Kumar, J., Marx, K. A., & Tripathy, S. K. (1996).
Phycobiliprotein encapsulated in sol-gel glass. Journal of Sol-Gel Science and
Technology, 7(1-2), 99-108.
Cheng, D., Wen, Y., Wang, L., An, X., Zhu, X., & Ni, Y. (2015). Adsorption of
polyethylene glycol (PEG) onto cellulose nanocrystals to improve its
dispersity. Carbohydrate Polymers, 123, 157-163.
159
Cherhal, F., Cousin, F., & Capron, I. (2016). Structural description of the interface of
Pickering emulsions stabilized by cellulose nanocrystals. Biomacromolecules, 17(2),
496-502.
Chiang, Y. T., Lyu, S. Y., Wen, Y. H. & Lo, C. L. (2018). Preparation and
characterization of electrostatically crosslinked polymer–liposomes in anticancer
therapy. International Journal of Molecular Sciences, 19(6), 1615.
Chibowski, S., & Paszkiewicz, M. (1999). Influence of the molecular weight of
polyethylene glycol and polyethylene oxide on the adsorption and electrochemical
properties of the titania/electrolyte solution interface. Adsorption Science &
Technology, 17(10), 845-855.
Chirayil, C. J., Joy, J., Mathew, L., Mozetic, M., Koetz, J., & Thomas, S. (2014).
Isolation and characterization of cellulose nanofibrils from Helicteres isora
plant. Industrial Crops and Products, 59, 27-34.
Cilla, A., Bosch, L., Barberá, R., & Alegría, A. (2018). Effect of processing on the
bioaccessibility of bioactive compounds–a review focusing on carotenoids, minerals,
ascorbic acid, tocopherols and polyphenols. Journal of Food Composition and
Analysis, 68, 3-15.
Clogston, J. D., & Patri, A. K. (2011). Zeta potential measurement. In Characterization
of nanoparticles intended for drug delivery (pp. 63-70). Humana Press.
Corzo, L., Fernández-Novoa, L., Carrera, I., Martínez, O., Rodríguez, S., Alejo, R., &
Cacabelos, R. (2020). Nutrition, health, and disease: Role of selected marine and
vegetal nutraceuticals. Nutrients, 12(3), 747.
Couvreur, P., Barratt, G., Fattal, E., & Vauthier, C. (2002). Nanocapsule technology: a
review. Critical Reviews in Therapeutic Drug Carrier Systems, 19(2).
Da Silva, F. L. O., Marques, M. B. D. F., Kato, K. C., & Carneiro, G. (2020).
Nanonization techniques to overcome poor water-solubility with drugs. Expert Opinion
on Drug Discovery, 1-12.
Dai, H., Wu, J., Zhang, H., Chen, Y., Ma, L., Huang, H., ... & Zhang, Y. (2020). Recent
advances on cellulose nanocrystals for Pickering emulsions: Development and
challenge. Trends in Food Science & Technology, 102, 16-29.
160
Dai, L., Sun, C., Wei, Y., Mao, L., & Gao, Y. (2018). Characterization of Pickering
emulsion gels stabilized by zein/gum arabic complex colloidal nanoparticles. Food
Hydrocolloids, 74, 239-248.
Damodaran, S., Parkin, K. L., & Fennema, O. R. (Eds.). (2007). Lipids: Fennema's food
chemistry. (pp. 172-231). CRC Press.
Dhakane, J. P., Kar, A., Patel, A. S., & Khan, I. (2017). Effect of soy proteins and
emulsification-evaporation process on physical stability of lycopene
emulsions. International Journal of Chemical Studies, 5(5), 1354-1358.
Dickinson, E. (2012). Use of nanoparticles and microparticles in the formation and
stabilization of food emulsions. Trends in Food Science & Technology, 24(1), 4-12.
Dieng, S. M., Anton, N., Bouriat, P., Thioune, O., Sy, P. M., Massaddeq, N., ... &
Vandamme, T. (2019). Pickering nano-emulsions stabilized by solid lipid nanoparticles
as a temperature sensitive drug delivery system. Soft Matter, 15(40), 8164-8174.
Ding, B., Xia, S., Hayat, K., & Zhang, X. (2009). Preparation and pH stability of ferrous
glycinate liposomes. Journal of Agricultural and Food Chemistry, 57(7), 2938-2944.
Dumay, J., Clément, N., Morançais, M., & Fleurence, J. (2013). Optimization of
hydrolysis conditions of Palmaria palmata to enhance R-phycoerythrin extraction.
Bioresource Technology, 131, 21-27.
Ekvall, S. W. (2017). 36 Constipation and Fiber. Pediatric and Adult Nutrition in
Chronic Diseases, Developmental Disabilities, and Hereditary Metabolic Disorders:
Prevention, Assessment, and Treatment, 265, (pp. 265-270). Oxford University Press.
Eloy, J. O., de Souza, M. C., Petrilli, R., Barcellos, J. P. A., Lee, R. J., & Marchetti, J.
M. (2014). Liposomes as carriers of hydrophilic small molecule drugs: Strategies to
enhance encapsulation and delivery. Colloids and Surfaces B: Biointerfaces, 123, 345-
363.
Espitia, P. J., Fuenmayor, C. A., & Otoni, C. G. (2019). Nanoemulsions: Synthesis,
characterization, and application in bio‐based active food packaging. Comprehensive
Reviews in Food Science and Food Safety, 18(1), 264-285.
161
Eyley, S., Vandamme, D., Lama, S., Van den Mooter, G., Muylaert, K., & Thielemans,
W. (2015). CO2 controlled the flocculation of microalgae using pH-responsive
cellulose nanocrystals. Nanoscale, 7(34), 14413-14421.
Falkeborg, M. F., Roda-Serrat, M. C., Burnaes, K. L., & Nielsen, A. L. D. (2018).
Stabilizing phycocyanin by anionic micelles. Food Chemistry, 239, 771-780.
Fan, Y., Chen, C., Huang, Y., Zhang, F., & Lin, G. (2017). Study of the pH-sensitive
mechanism of tumor-targeting liposomes. Colloids and Surfaces B: Biointerfaces, 151,
19-25.
Feng, J., Cai, H., Wang, H., Li, C., & Liu, S. (2018). Improved oxidative stability of
fish oil emulsion by grafted ovalbumin-catechin conjugates. Food Chemistry, 241, 60-
69.
Flint, H. J., Scott, K. P., Duncan, S. H., Louis, P., & Forano, E. (2012). Microbial
degradation of complex carbohydrates in the gut. Gut Microbes, 3(4), 289-306.
Fu, D., Deng, S., McClements, D. J., Zhou, L., Zou, L., Yi, J., ... & Liu, W. (2019).
Encapsulation of β-carotene in wheat gluten nanoparticle-xanthan gum-stabilized
Pickering emulsions: Enhancement of carotenoid stability and bioaccessibility. Food
Hydrocolloids, 89, 80-89.
Furuta, T., Miyabe, Y., Yasui, H., Kinoshita, Y., & Kishimura, H. (2016). Angiotensin
I converting enzyme inhibitory peptides derived from phycobiliproteins of dulse
(Palmaria palmata). Marine Drugs, 14(2), 32.
Galland-Irmouli, A. V., Pons, L., Lucon, M., Villaume, C., Mrabet, N. T., Gueant, J.
L., & Fleurence, J. (2000). One-step purification of R-phycoerythrin from the red
macroalga Palmaria palmata using preparative polyacrylamide gel
electrophoresis. Journal of Chromatography B: Biomedical Sciences and
Applications, 739(1), 117-123.
Gao, F. S., Feng, L., Zhang, Q., Yan, R. Q., Li, Y. G., & Li, X. S. (2013).
Immunogenicity of two FMDV nonameric peptides encapsulated in liposomes in mice
and the protective efficacy in guinea pigs. PloS One, 8(7), e68658.
Garcia, A., Gandini, A., Labidi, J., Belgacem, N., & Bras, J. (2016). Industrial and crop
wastes: A new source for nanocellulose biorefinery. Industrial Crops and Products, 93,
26-38.
162
Ge, L., Ong, R., Yap, C. W., & Heng, B. H. (2019). Effects of chronic diseases on
health‐related quality of life and self‐rated health among three adult age
groups. Nursing & Health Sciences, 21(2), 214-222.
Genkawa, T., Ahamed, T., Noguchi, R., Takigawa, T., & Ozaki, Y. (2016). Simple and
rapid determination of free fatty acids in brown rice by FTIR spectroscopy in
conjunction with a second-derivative treatment. Food Chemistry, 191, 7-11.
Girouard, N. M., Xu, S., Schueneman, G. T., Shofner, M. L., & Meredith, J. C. (2016).
Site-selective modification of cellulose nanocrystals with isophorone diisocyanate and
formation of polyurethane-CNC composites. ACS Applied Materials &
Interfaces, 8(2), 1458-1467.
Glazer, A. N., & Cohen-Bazire, G. (1971). Subunit structure of the phycobiliproteins
of blue-green algae. Proceedings of the National Academy of Sciences, 68(7), 1398-
1401.
Goi, Y., Fujisawa, S., Saito, T., Yamane, K., Kuroda, K., & Isogai, A. (2019). Dual
functions of tempo-oxidized cellulose nanofibers in oil-in-water emulsions: a Pickering
emulsifier and a unique dispersion stabilizer. Langmuir, 35(33), 10920-10926.
Gonzalez-Ramirez, E., Andujar-Sanchez, M., Ortiz-Salmeron, E., Bacarizo, J., Cuadri,
C., Mazzuca-Sobczuk, T., ... & Martinez-Rodriguez, S. (2014). Thermal and pH
Stability of the B-Phycoerythrin from the Red Algae Porphyridium cruentum. Food
Biophysics, 9(2), 184-192.
Grishkewich, N., Mohammed, N., Tang, J., & Tam, K. C. (2017). Recent advances in
the application of cellulose nanocrystals. Current Opinion in Colloid & Interface
Science, 29, 32-45.
Guichard, E., Galindo-Cuspinera, V., & Feron, G. (2018). Physiological mechanisms
explaining human differences in fat perception and liking in food spreads-a
review. Trends in Food Science & Technology, 74, 46-55.
Guldiken, B., Gibis, M., Boyacioglu, D., Capanoglu, E., & Weiss, J. (2018). Physical
and chemical stability of anthocyanin-rich black carrot extract-loaded liposomes during
storage. Food Research International, 108, 491-497.
163
Guo, J., Du, W., Gao, Y., Cao, Y., & Yin, Y. (2017). Cellulose nanocrystals as water-
in-oil Pickering emulsifiers via intercalative modification. Colloids and Surfaces A:
Physicochemical and Engineering Aspects, 529, 634-642.
Guo, J., Mattos, B. D., Tardy, B. L., Moody, V. M., Xiao, G., Ejima, H., ... &
Richardson, J. J. (2019). Porous inorganic and hybrid systems for drug delivery: future
promise in combatting drug resistance and translation to botanical
applications. Current Medicinal Chemistry, 26(33), 6107-6131.
Gupta, A., Eral, H. B., Hatton, T. A., & Doyle, P. S. (2016). Nanoemulsions: formation,
properties and applications. Soft matter, 12(11), 2826-2841.
Habibi, Y., Lucia, L. A., & Rojas, O. J. (2010). Cellulose nanocrystals: chemistry, self-
assembly, and applications. Chemical Reviews, 110(6), 3479-3500.
Haidar, I., Harding, I. H., Bowater, I. C., Eldridge, D. S., & Charman, W. N. (2017).
The role of lecithin degradation on the pH dependent stability of halofantrine
encapsulated fat nano-emulsions. International Journal of Pharmaceutics, 528(1-2),
524-535.
Hakkarainen, T., Koivuniemi, R., Kosonen, M., Escobedo-Lucea, C., Sanz-Garcia, A.,
Vuola, J., ... & Yliperttula, M. (2016). Nanofibrillar cellulose wound dressing in skin
graft donor site treatment. Journal of Controlled Release, 244, 292-301.
Hashizaki, K., Taguchi, H., Itoh, C., Sakai, H., Abe, M., Saito, Y., & Ogawa, N. (2003).
Effects of poly (ethylene glycol) (PEG) chain length of PEG-lipid on the permeability
of liposomal bilayer membranes. Chemical and Pharmaceutical Bulletin, 51(7), 815-
820.
Hayashi, N., Kondo, T., & Ishihara, M. (2005). Enzymatically produced nano-ordered
short elements containing cellulose Iβ crystalline domains. Carbohydrate
Polymers, 61(2), 191-197.
Hedjazi, S., & Razavi, S. H. (2018). A comparison of Canthaxanthine Pickering
emulsions, stabilized with cellulose nanocrystals of different origins. International
Journal of Biological Macromolecules, 106, 489-497.
Heise, K., Koso, T., Pitkanen, L., Potthast, A., King, A. W., Kostiainen, M. A., &
Kontturi, E. (2019). Knoevenagel condensation for modifying the reducing end groups
of cellulose nanocrystals. ACS Macro Letters, 8(12), 1642-1647.
164
Hettle, R., Corbett, M., Hinde, S., Hodgson, R., Jones-Diette, J., Woolacott, N., &
Palmer, S. (2017). The assessment and appraisal of regenerative medicines and cell
therapy products: an exploration of methods for review, economic evaluation and
appraisal. Health Technology Assessment, 1-204.
Hosseinidoust, Z., Alam, M. N., Sim, G., Tufenkji, N., & van de Ven, T. G. (2015).
Cellulose nanocrystals with tunable surface charge for
nanomedicine. Nanoscale, 7(40), 16647-16657.
Hsieh-Lo, M., Castillo, G., Ochoa-Becerra, M. A., & Mojica, L. (2019). Phycocyanin
and phycoerythrin: Strategies to improve production yield and chemical stability. Algal
Research, 42, 101600.
Hu, B., Wang, K., Han, L., Zhou, B., Yang, J., & Li, S. (2020). Pomegranate seed oil
stabilized with ovalbumin glycated by inulin: Physicochemical stability and oxidative
stability. Food Hydrocolloids, 102, 105602.
Hubbe, M. A., Ferrer, A., Tyagi, P., Yin, Y., Salas, C., Pal, L., & Rojas, O. J. (2017).
Nanocellulose in thin films, coatings, and plies for packaging applications: A
review. BioResources, 12(1), 2143-2233.
Hydbring, P., & Du, J. (2019). Nanoparticle interaction with immune cells for
nanoparticle-mediated (anticancer) immunotherapy. In Theranostic
Bionanomaterials (pp. 55-73). Elsevier.
Israelachvili, J. (2011). Intermolecular and surface forces (3rd ed.). (pp. 291-338).
London: Academic Press.
Janero, D. R. (1990). Malondialdehyde and thiobarbituric acid-reactivity as diagnostic
indices of lipid peroxidation and peroxidative tissue injury. Free Radical Biology and
Medicine, 9(6), 515-540.
Jang, M. H., Kim, C. H., Yoon, H. Y., Sung, S. W., Goh, M. S., Lee, E. S., ... & Choi,
Y. W. (2019). Steric stabilization of RIPL peptide-conjugated liposomes and in vitro
assessment. Journal of Pharmaceutical Investigation, 49(1), 115-125.
Jimenez, L. N., Martínez Narváez, C. D., & Sharma, V. (2020). Capillary breakup and
extensional rheology response of food thickener cellulose gum (NaCMC) in salt-free
and excess salt solutions. Physics of Fluids, 32(1), 012113.
165
Jordan, J. H., Easson, M. W., & Condon, B. D. (2019). Alkali hydrolysis of sulfated
cellulose nanocrystals: optimization of reaction conditions and tailored surface
charge. Nanomaterials, 9(9), 1232.
Jung, J., Deng, Z., & Zhao, Y. (2020). A review of cellulose nanomaterials incorporated
fruit coatings with improved barrier property and stability: Principles and
applications. Journal of Food Process Engineering, 43(2), e13344.
Kabeya, N., Sanz-Jorquera, A., Carboni, S., Davie, A., Oboh, A., & Monroig, O.
(2017). Biosynthesis of polyunsaturated fatty acids in sea urchins: Molecular and
functional characterisation of three fatty acyl desaturases from Paracentrotus lividus
(Lamark 1816). PLoS One, 12(1), e0169374.
Kalashnikova, I., Bizot, H., Cathala, B., & Capron, I. (2012). Modulation of cellulose
nanocrystals amphiphilic properties to stabilize oil/water
interface. Biomacromolecules, 13(1), 267-275.
Kannaujiya, V. K., & Sinha, R. P. (2016). Thermokinetic stability of phycocyanin and
phycoerythrin in food-grade preservatives. Journal of Applied Phycology, 28(2), 1063-
1070.
Kargarzadeh, H., Mariano, M., Gopakumar, D., Ahmad, I., Thomas, S., Dufresne, A.,
... & Lin, N. (2018). Advances in cellulose nanomaterials. Cellulose, 25(4), 2151-2189.
Kasiri, N., & Fathi, M. (2018). Production of cellulose nanocrystals from pistachio
shells and their application for stabilizing Pickering emulsions. International Journal
of Biological Macromolecules, 106, 1023-1031.
Khan, A., Wen, Y., Huq, T., & Ni, Y. (2018). Cellulosic nanomaterials in food and
nutraceutical applications: a review. Journal of Agricultural and Food
Chemistry, 66(1), 8-19.
Khan, I., Saeed, K., & Khan, I. (2019). Nanoparticles: Properties, applications and
toxicities. Arabian Journal of Chemistry, 12(7), 908-931.
Khosa, A., Reddi, S., & Saha, R. N. (2018). Nanostructured lipid carriers for site-
specific drug delivery. Biomedicine & Pharmacotherapy, 103, 598-613.
166
Ko, A., Lee, J. S., Sop Nam, H., & Gyu Lee, H. (2017). Stabilization of black soybean
anthocyanin by chitosan nanoencapsulation and copigmentation. Journal of Food
Biochemistry, 41(2), e12316.
Kono, Y., Iwasaki, A., & Fujita, T. (2018). Effect of surface charge, particle size, and
modification by polyethylene glycol of liposomes on their association with Caco-2 cells
across an unstirred water layer. Die Pharmazie-An International Journal of
Pharmaceutical Sciences, 73(1), 3-8.
Kopechek, J. A., Abruzzo, T. M., Wang, B., Chrzanowski, S. M., Smith, D. A., Kee,
P. H., ... & Holland, C. K. (2008). Ultrasound‐mediated release of hydrophilic and
lipophilic agents from echogenic liposomes. Journal of Ultrasound in
Medicine, 27(11), 1597-1606.
Kresse, K. M., Xu, M., Pazzi, J., García-Ojeda, M., & Subramaniam, A. B. (2016).
Novel application of cellulose paper as a platform for the macromolecular self-
assembly of biomimetic giant liposomes. ACS Applied Materials & Interfaces, 8(47),
32102-32107.
Kuc, J. (2007). Compounds from plants that regulate or participate in disease
resistance. In Ciba Foundation Symposium 154‐Bioactive Compounds from Plants:
Bioactive Compounds from Plants: Ciba Foundation Symposium 154 (pp. 213-230).
Chichester, UK: John Wiley & Sons, Ltd.
Kuddus, M., Singh, P., Thomas, G., & Al-Hazimi, A. (2013). Recent developments in
production and biotechnological applications of C-phycocyanin. BioMed Research
International, 2013, 1-9.
Kuttruff, C. A., Eastgate, M. D., & Baran, P. S. (2014). Natural product synthesis in
the age of scalability. Natural Product Reports, 31(4), 419-432.
Lage-Yusty, M. A., Carames-Adan, P., & Lopez-Hernandez, J. (2013). Determination
of phycobiliproteins by constant-wavelength synchronous spectrofluorimetry method
in red algae. CyTA-Journal of Food, 11(3), 243-247.
Lasekan, A. O., & Nayak, B. (2016). Effects of buffer additives and thermal processing
methods on the solubility of shrimp (Penaeus monodon) proteins and the
immunoreactivity of its major allergen. Food Chemistry, 200, 146-153.
167
Laye, C., McClements, D. J., & Weiss, J. (2008). Formation of biopolymer‐coated
liposomes by electrostatic deposition of chitosan. Journal of Food Science, 73(5), N7-
N15.
Lee, D. U., Park, H. W., & Lee, S. C. (2020). Effect of stigmasterol in liposome bilayer
on the stabilization of encapsulated ascorbic acid. Korean Journal of Food Science and
Technology, 52(2), 200-203.
Lee, D., Nishizawa, M., Shimizu, Y., & Saeki, H. (2017). Anti-inflammatory effects of
dulse (Palmaria palmata) resulting from the simultaneous water-extraction of
phycobiliproteins and chlorophyll a. Food Research International, 100, 514-521.
Lengyel, M., Kállai-Szabó, N., Antal, V., Laki, A. J., & Antal, I. (2019).
Microparticles, microspheres, and microcapsules for advanced drug delivery. Scientia
Pharmaceutica, 87(3), 20.
Lever, E., Scott, S. M., Louis, P., Emery, P. W., & Whelan, K. (2019). The effect of
prunes on stool output, gut transit time and gastrointestinal microbiota: A randomised
controlled trial. Clinical Nutrition, 38(1), 165-173.
Li, W., Ju, B., & Zhang, S. (2020). Novel amphiphilic cellulose nanocrystals for pH-
responsive Pickering emulsions. Carbohydrate Polymers, 229, 115401.
Li, X., Li, J., Gong, J., Kuang, Y., Mo, L., & Song, T. (2018). Cellulose nanocrystals
(CNCs) with different crystalline allomorph for oil in water Pickering
emulsions. Carbohydrate Polymers, 183, 303-310.
Li, Y., Lu, L., Zhang, H., & Wang, J. (2012). The pH regulated phycobiliproteins
loading and releasing of polyelectrolytes multilayer microcapsules. Colloids and
Surfaces B: Biointerfaces, 93, 121-126.
Liu, J., Lu, N., Li, J., Weng, Y., Yuan, B., Yang, K., & Ma, Y. (2013). Influence of
surface chemistry on particle internalization into giant unilamellar
vesicles. Langmuir, 29(25), 8039-8045.
Liu, L. N., Su, H. N., Yan, S. G., Shao, S. M., Xie, B. B., Chen, X. L., ... & Zhang, Y.
Z. (2009). Probing the pH sensitivity of R-phycoerythrin: Investigations of active
conformational and functional variation. Biochimica et Biophysica Acta (BBA)-
Bioenergetics, 1787(7), 939-946.
168
Liu, R., Lu, Y., Pu, W. F., Lian, K., Sun, L., Du, D. J., ... & Sheng, J. J. (2020). Low-
energy Emulsification of Oil-in-water Emulsions with Self-regulating Mobility via a
Nanoparticle Surfactant. Industrial & Engineering Chemistry Research.
DOI:10.1021/acs.iecr.0c03153
Liu, Y., Hou, Z., Yang, J., & Gao, Y. (2015). Effects of antioxidants on the stability of
β-carotene in O/W emulsions stabilized by gum arabic. Journal of Food Science and
Technology, 52(6), 3300-3311.
Lombardo, S., & Thielemans, W. (2018). Thermodynamics of the interactions of
positively charged cellulose nanocrystals with molecules bearing different amounts of
carboxylate anions. Physical Chemistry Chemical Physics, 20(26), 17637-17647.
Low, L. E., Tan, L. T. H., Goh, B. H., Tey, B. T., Ong, B. H., & Tang, S. Y. (2019).
Magnetic cellulose nanocrystal stabilized Pickering emulsions for enhanced bioactive
release and human colon cancer therapy. International Journal of Biological
Macromolecules, 127, 76-84.
Lynch, J., & Smith, G. D. (2005). A life course approach to chronic disease
epidemiology. Annual Review Public Health, 26, 1-35.
Maehre, H. K., Jensen, I. J., & Eilertsen, K. E. (2016). Enzymatic pre-treatment
increases the protein bioaccessibility and extractability in Dulse (Palmaria
palmata). Marine Drugs, 14(11), 196.
Mahmud, M., Piwoni, A., Filiczak, N., Janicka, M., & Gubernator, J. (2016). Long-
circulating curcumin-loaded liposome formulations with high incorporation efficiency,
stability and anticancer activity towards pancreatic adenocarcinoma cell lines in
vitro. PloS One, 11(12), e0167787.
Manconia, M., Pendas, J., Ledon, N., Moreira, T., Sinico, C., Saso, L., & Fadda, A. M.
(2009). Phycocyanin liposomes for topical anti‐inflammatory activity: in‐vitro in‐vivo
studies. Journal of Pharmacy and Pharmacology, 61(4), 423-430.
Manirafasha, E., Ndikubwimana, T., Zeng, X., Lu, Y., & Jing, K. (2016).
Phycobiliprotein: potential microalgae derived pharmaceutical and biological
reagent. Biochemical Engineering Journal, 109, 282-296.
Maoka, T. (2020). Carotenoids as natural functional pigments. Journal of natural
medicines, 1-16.
169
Maphosa, Y., & Jideani, V. A. (2018). Factors affecting the stability of emulsions
stabilized by biopolymers. Science and Technology Behind Nanoemulsions, 65-81.
Maqsood, S., Adiamo, O., Ahmad, M., & Mudgil, P. (2020). Bioactive compounds
from date fruit and seed as potential nutraceutical and functional food ingredients. Food
Chemistry, 308, 125522.
Marquez, R., Forgiarini, A. M., Langevin, D., & Salager, J. L. (2018). Instability of
emulsions made with surfactant–oil–water systems at optimum formulation with
ultralow interfacial tension. Langmuir, 34(31), 9252-9263.
Martelli, G., Folli, C., Visai, L., Daglia, M., & Ferrari, D. (2014). Thermal stability
improvement of blue colorant C-phycocyanin from Spirulina platensis for food
industry applications. Process Biochemistry, 49(1), 154-159.
Martins, M., Vieira, F. A., Correia, I., Ferreira, R. A., Abreu, H., Coutinho, J. A., &
Ventura, S. P. (2016). Recovery of phycobiliproteins from the red macroalga
Gracilaria sp. using ionic liquid aqueous solutions. Green Chemistry, 18(15), 4287-
4296.
Marze, S., Meynier, A., & Anton, M. (2013). In vitro digestion of fish oils rich in n-3
polyunsaturated fatty acids studied in emulsion and at the oil–water interface. Food &
Function, 4(2), 231-239.
McClements, D. J. (2015). Encapsulation, protection, and release of hydrophilic active
components: potential and limitations of colloidal delivery systems. Advances in
Colloid and Interface Science, 219, 27-53.
McClements, D. J. (2018). Enhanced delivery of lipophilic bioactives using emulsions:
a review of major factors affecting vitamin, nutraceutical, and lipid
bioaccessibility. Food & Function, 9(1), 22-41.
McClements, D. J., Decker, E. A., Park, Y., & Weiss, J. (2009). Structural design
principles for delivery of bioactive components in nutraceuticals and functional
foods. Critical Reviews in Food Science and Nutrition, 49(6), 577-606.
Medeiros, D. M., & Wildman, R. E. (2018). Nutraceuticals and functional foods. In
Advanced human nutrition (pp. 419-436). Jones & Bartlett Learning.
170
Mehmood, A., & Zeb, A. (2020). Effects of different cooking techniques on bioactive
contents of leafy vegetables. International Journal of Gastronomy and Food Science,
100246.
Mehmood, T., Ahmad, A., Ahmed, A., & Ahmed, Z. (2017). Optimization of olive oil-
based O/W nanoemulsions prepared through ultrasonic homogenization: A response
surface methodology approach. Food Chemistry, 229, 790-796.
Mehrad, B., Ravanfar, R., Licker, J., Regenstein, J. M., & Abbaspourrad, A. (2018).
Enhancing the physicochemical stability of β-carotene solid lipid nanoparticle (SLNP)
using whey protein isolate. Food Research International, 105, 962-969.
Meirelles, A. A. D., Costa, A. L. R., & Cunha, R. L. (2020). Cellulose nanocrystals
from ultrasound process stabilizing O/W Pickering emulsion. International Journal of
Biological Macromolecules. 158, 75-84.
Menchicchi, B., Fuenzalida, J. P., Hensel, A., Swamy, M. J., David, L., Rochas, C., &
Goycoolea, F. M. (2015). Biophysical analysis of the molecular interactions between
polysaccharides and mucin. Biomacromolecules, 16(3), 924-935.
Midmore, B. R. (1998). Preparation of a novel silica-stabilized oil/water
emulsion. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 132(2-
3), 257-265.
Mo, Y., Guo, R., Liu, J., Lan, Y., Zhang, Y., Xue, W., & Zhang, Y. (2015). Preparation
and properties of PLGA nanofiber membranes reinforced with cellulose
nanocrystals. Colloids and Surfaces B: Biointerfaces, 132, 177-184.
Moon, R. J., Martini, A., Nairn, J., Simonsen, J., & Youngblood, J. (2011). Cellulose
nanomaterials review: structure, properties and nanocomposites. Chemical Society
Reviews, 40(7), 3941-3994.
Munier, M., Jubeau, S., Wijaya, A., Morançais, M., Dumay, J., Marchal, L., ... &
Fleurence, J. (2014). Physicochemical factors affecting the stability of two pigments:
R-phycoerythrin of Grateloupia turuturu and B-phycoerythrin of Porphyridium
cruentum. Food Chemistry, 150, 400-407.
Mustranta, A., Forssell, P., & Poutanen, K. (1995). Comparison of lipases and
phospholipases in the hydrolysis of phospholipids. Process Biochemistry, 30(5), 393-
401.
171
Nahr, F. K., Ghanbarzadeh, B., Hamishehkar, H., & Kafil, H. S. (2018). Food grade
nanostructured lipid-carrier for cardamom essential oil: Preparation, characterization
and antimicrobial activity. Journal of Functional Foods, 40, 1-8.
Nanocellulose Pilot Plant (n.d.). Forest Products Laboratory - USDA Forest Service.
Retrieved June 13, 2020, from
www.fpl.fs.fed.us/research/facilities/nanocellulose_pilot-plant.php.
National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP)
(2020, September 24). Chronic Diseases in America. Retrieved October 08, 2020,
from https://www.cdc.gov/chronicdisease/resources/infographic/chronic-diseases.htm
Natterodt, J. C., Petri-Fink, A., Weder, C., & Zoppe, J. O. (2017). Cellulose
nanocrystals: Surface modification, applications and opportunities at
interfaces. CHIMIA International Journal for Chemistry, 71(6), 376-383.
Navon, Y., Radavidson, H., Putaux, J. L., Jean, B., & Heux, L. (2017). pH-sensitive
interactions between cellulose nanocrystals and DOPC liposomes. Biomacromolecules,
18(9), 2918-2927.
Ngwabebhoh, F. A., Erdagi, S. I., & Yildiz, U. (2018). Pickering emulsions stabilized
nanocellulosic-based nanoparticles for coumarin and curcumin nanoencapsulations: In
vitro release, anticancer and antimicrobial activities. Carbohydrate Polymers, 201,
317-328.
Nikolic, M. R., Minic, S., Macvanin, M., Stanic-Vucinic, D., & Velickovic, T. C.
(2020). Analytical Protocols in Phycobiliproteins Analysis. In Pigments from
Microalgae Handbook (pp. 179-201). Springer, Cham.
Ojeda-Serna, I. E., Rocha-Guzman, N. E., Gallegos-Infante, J. A., Chairez-Ramirez,
M. H., Rosas-Flores, W., Perez-Martinez, J. D., ... & Gonzalez-Laredo, R. F. (2019).
Water-in-oil organogel based emulsions as a tool for increasing bioaccessibility and
cell permeability of poorly water-soluble nutraceuticals. Food Research
International, 120, 415-424.
Ortega, A. M. M., & Campos, M. R. S. (2019). Bioactive Compounds as Therapeutic
Alternatives. In Bioactive compounds (pp. 247-264). Woodhead Publishing.
172
Pagels, F., Guedes, A. C., Amaro, H. M., Kijjoa, A., & Vasconcelos, V. (2019).
Phycobiliproteins from cyanobacteria: Chemistry and biotechnological
applications. Biotechnology Advances, 37(3), 422-443.
Pal, R. (1997). Viscosity and storage/loss moduli for mixtures of fine and coarse
emulsions. Chemical Engineering Journal, 67(1), 37-44.
Palchetti, S., Colapicchioni, V., Digiacomo, L., Caracciolo, G., Pozzi, D., Capriotti, A.
L., ... & Lagana, A. (2016). The protein corona of circulating PEGylated liposomes.
Biochimica et Biophysica Acta (BBA)-Biomembranes, 1858(2), 189-196.
Paleos, J. (1969). Adsorption from aqueous and nonaqueous solutions on hydrophobic
and hydrophilic high surface-area copolymers. Journal of Colloid and Interface
Science, 31(1), 7-18.
Pandey, M. M., Rastogi, S., & Rawat, A. K. S. (2013). Indian traditional ayurvedic
system of medicine and nutritional supplementation. Evidence-Based Complementary
and Alternative Medicine, 2013, 1-12.
Pandey, M., Verma, R. K., & Saraf, S. A. (2010). Nutraceuticals: new era of medicine
and health. Asian Journal of Pharmaceutical and Clinical Research, 3(1), 11-15.
Panja, S., Khatua, D. K., & Halder, M. (2019). Effect of casein on pure lecithin
liposome: mixed biomacromolecular system for providing superior stabilization to
hydrophobic molecules. Colloids and Surfaces B: Biointerfaces, 180, 298-305.
Parise, A., Milelli, A., Tumiatti, V., Minarini, A., Neviani, P., & Zuccari, G. (2015).
Preparation, characterization and in vitro evaluation of sterically stabilized liposome
containing a naphthalenediimide derivative as anticancer agent. Drug Delivery, 22(5),
590-597.
Peciulyte, A., Karlstrom, K., Larsson, P. T., & Olsson, L. (2015). Impact of the
supramolecular structure of cellulose on the efficiency of enzymatic
hydrolysis. Biotechnology for Biofuels, 8(1), 1-13.
Peng, S., Zou, L., Liu, W., Liu, C., & McClements, D. J. (2018). Fabrication and
characterization of curcumin-loaded liposomes formed from sunflower lecithin: Impact
of composition and environmental stress. Journal of Agricultural and Food Chemistry,
66(46), 12421-12430.
173
Peng, S., Zou, L., Zhou, W., Liu, W., Liu, C., & McClements, D. J. (2019).
Encapsulation of lipophilic polyphenols into nanoliposomes using pH-driven method:
Advantages and disadvantages. Journal of Agricultural and Food Chemistry, 67 (26),
7506-7511.
Pickering, S. U. (1907). Cxcvi.-emulsions. Journal of the Chemical Society,
Transactions, 91, 2001-2021.
Pidgeon, C., Apostol, G., & Markovich, R. (1989). Fourier transform infrared assay of
liposomal lipids. Analytical Biochemistry, 181(1), 28-32.
Prado, K. S., & Spinace, M. A. (2019). Isolation and characterization of cellulose
nanocrystals from pineapple crown waste and their potential uses. International
Journal of Biological Macromolecules, 122, 410-416.
Prathapan, R., Thapa, R., Garnier, G., & Tabor, R. F. (2016). Modulating the zeta
potential of cellulose nanocrystals using salts and surfactants. Colloids and Surfaces A:
Physicochemical and Engineering Aspects, 509, 11-18.
Preethi, R., Leena, M. M., Moses, J. A., & Anandharamakrishnan, C. (2020).
Biopolymer nanocomposites and its application in food processing. In Green
Nanomaterials (pp. 283-317). Springer, Singapore.
Przybylski, R. (2001). Canola oil: physical and chemical properties. Canola Council
of Canada, 1. Retrieved June 23, 2020, from
https://fr.canolacouncil.org/media/515239/canola_oil_physical_chemical_properties_
1.pdf
Qian, C., Decker, E. A., Xiao, H., & McClements, D. J. (2012). Inhibition of β-carotene
degradation in oil-in-water nanoemulsions: Influence of oil-soluble and water-soluble
antioxidants. Food Chemistry, 135(3), 1036-1043.
Rasti, B., Jinap, S., Mozafari, M. R., & Yazid, A. M. (2012). Comparative study of the
oxidative and physical stability of liposomal and nanoliposomal polyunsaturated fatty
acids prepared with conventional and Mozafari methods. Food Chemistry, 135(4),
2761-2770.
Rastogi, R. P., Sonani, R. R., & Madamwar, D. (2015). Physico-chemical factors
affecting the in vitro stability of phycobiliproteins from Phormidium rubidum
A09DM. Bioresource Technology, 190, 219-226.
174
Rayner, M., Marku, D., Eriksson, M., Sjöö, M., Dejmek, P., & Wahlgren, M. (2014).
Biomass-based particles for the formulation of Pickering type emulsions in food and
topical applications. Colloids and Surfaces A: Physicochemical and Engineering
Aspects, 458, 48-62.
Riss, J., Decorde, K., Sutra, T., Delage, M., Baccou, J. C., Jouy, N., ... & Rouanet, J.
M. (2007). Phycobiliprotein C-phycocyanin from Spirulina platensis is powerfully
responsible for reducing oxidative stress and NADPH oxidase expression induced by
an atherogenic diet in hamsters. Journal of Agricultural and Food Chemistry, 55(19),
7962-7967.
Riviere, J. E., Scoglio, C., Sahneh, F. D., & Monteiro-Riviere, N. A. (2013).
Computational approaches and metrics required for formulating biologically realistic
nanomaterial pharmacokinetic models. Computational Science & Discovery, 6(1),
014005.
Roman, M., Dong, S., Hirani, A., & Lee, Y. W., (2009). Cellulose nanocrystals for drug
delivery. In: K. J. Edgar, T. Heinze, and C. M. Buchanan, (Eds.), Polysaccharide
materials: Performance by design (pp. 81-91). ACS Symposium Series; American
Chemical Society: Washington, DC.
Roman, S., Sánchez-Siles, L. M., & Siegrist, M. (2017). The importance of food
naturalness for consumers: Results of a systematic review. Trends in Food Science &
Technology, 67, 44-57.
Rossano, R., Ungaro, N., D'Ambrosio, A., Liuzzi, G. M., & Riccio, P. (2003).
Extracting and purifying R-phycoerythrin from Mediterranean red algae Corallina
elongata Ellis & Solander. Journal of Biotechnology, 101(3), 289-293.
Rowell, R. M., Pettersen, R., Han, J. S., Rowell, J. S., & Tshabalala, M. A. (2012). Cell
wall chemistry. Handbook of wood chemistry and wood composites, 2, (pp. 34-70).
CRC Press.
Sadhukhan, J., Gadkari, S., Martinez-Hernandez, E., Ng, K. S., Shemfe, M., Torres-
Garcia, E., & Lynch, J. (2019). Novel macroalgae (seaweed) biorefinery systems for
integrated chemical, protein, salt, nutrient and mineral extractions and environmental
protection by green synthesis and life cycle sustainability assessments. Green
Chemistry, 21(10), 2635-2655.
175
Sahu, S. S., Stiller, C., Cavallaro, S., Karlstrom, A. E., Linnros, J., & Dev, A. (2020).
Influence of molecular size and zeta potential in electrokinetic biosensing. Biosensors
and Bioelectronics, 152, 112005.
Saidane, D., Perrin, E., Cherhal, F., Guellec, F., & Capron, I. (2016). Some
modification of cellulose nanocrystals for functional Pickering
emulsions. Philosophical Transactions of the Royal Society A: Mathematical, Physical
and Engineering Sciences, 374(2072), 20150139.
Saleh, R., Bearth, A., & Siegrist, M. (2019). “Chemophobia” Today: Consumers’
Knowledge and Perceptions of Chemicals. Risk Analysis, 39(12), 2668-2682.
Sampathkumar, K., Tan, K. X., & Loo, S. C. J. (2020). Developing nano-delivery
systems for agriculture and food applications with nature-derived polymers. iScience,
101055.
Santini, A., Tenore, G. C., & Novellino, E. (2017). Nutraceuticals: A paradigm of
proactive medicine. European Journal of Pharmaceutical Sciences, 96, 53-61.
Sappati, P. K., Nayak, B., VanWalsum, G. P., & Mulrey, O. T. (2019). Combined
effects of seasonal variation and drying methods on the physicochemical properties and
antioxidant activity of sugar kelp (Saccharina latissima). Journal of Applied
Phycology, 31(2), 1311-1332.
Sarkar, A., & Dickinson, E. (2020). Sustainable food-grade Pickering emulsions
stabilized by plant-based particles. Current Opinion in Colloid & Interface Science. 49,
69-81.
Sarkar, A., Goh, K. K. T., Singh, R. P., & Singh, H. (2009). Behaviour of an oil-in-
water emulsion stabilized by b-lactoglobulin in an in vitro gastric model. Food
Hydrocolloids, 23(6), 1563-1569.
Sartorius, N. (2006). The meanings of health and its promotion. Croatian medical
journal, 47(4), 662.
Sauer, S., & Plauth, A. (2017). Health-beneficial nutraceuticals—myth or
reality?. Applied Microbiology and Biotechnology, 101(3), 951-961.
176
Schubert, J., Radeke, C., Fery, A., & Chanana, M. (2019). The role of pH, metal ions
and their hydroxides in charge reversal of protein-coated nanoparticles. Physical
Chemistry Chemical Physics, 21(21), 11011-11018.
Seabra, A. B., Bernardes, J. S., Favaro, W. J., Paula, A. J., & Duran, N. (2018).
Cellulose nanocrystals as carriers in medicine and their toxicities: A
review. Carbohydrate Polymers, 181, 514-527.
Sekar, S., & Chandramohan, M. (2008). Phycobiliproteins as a commodity: trends in
applied research, patents and commercialization. Journal of Applied Phycology, 20(2),
113-136.
Shah, B. R., Li, Y., Jin, W., An, Y., He, L., Li, Z., ... & Li, B. (2016). Preparation and
optimization of Pickering emulsion stabilized by chitosan-tripolyphosphate
nanoparticles for curcumin encapsulation. Food Hydrocolloids, 52, 369-377.
Shao, P., Zhang, H., Niu, B., & Jin, W. (2018). Physical stabilities of taro starch
nanoparticles stabilized Pickering emulsions and the potential application of
encapsulated tea polyphenols. International Journal of Biological
Macromolecules, 118, 2032-2039.
Sharif, M. K., & Khalid, R. (2018). Nutraceuticals: myths versus realities.
In Therapeutic foods (pp. 3-21). Academic Press.
Sharif, M. K., & Zahid, A. (2018). Role of food product development in increased food
consumption and value addition. In Food processing for increased quality and
consumption (pp. 455-479). Academic Press.
Sharma, T., Kumar, G. S., Chon, B. H., & Sangwai, J. S. (2015). Thermal stability of
oil-in-water Pickering emulsion in the presence of nanoparticle, surfactant, and
polymer. Journal of Industrial and Engineering Chemistry, 22, 324-334.
Shen, Z., Ye, H., Kroger, M., & Li, Y. (2018). Aggregation of polyethylene glycol
polymers suppresses receptor-mediated endocytosis of PEGylated liposomes.
Nanoscale, 10(9), 4545-4560.
Shifu, W., Jinguang, W., & Guangxian, X. (1989, December). FT-IR spectra of the
C=O and CH stretching vibration of lauric acid. In 7th Intl Conf on Fourier Transform
Spectroscopy (Vol. 1145, pp. 340-341). International Society for Optics and
Photonics.
177
Sidler, W. A. (1994). Phycobilisome and phycobiliprotein structures. In The molecular
biology of cyanobacteria (pp. 139-216). Dordrecht: Springer.
Silberner, J. (2018, November 27) We're Living Longer ... But A Medical Journal Sees
Many Causes For Alarm. Retrieved October 08, 2020, from
https://www.mainepublic.org/post/were-living-longer-medical-journal-sees-many-
causes-alarm
Silva, H. D., Cerqueira, M. A., & Vicente, A. A. (2012). Nanoemulsions for food
applications: development and characterization. Food and Bioprocess
Technology, 5(3), 854-867.
Singh, H., & Sarkar, A. (2011). Behaviour of protein-stabilized emulsions under
various physiological conditions. Advances in Colloid and Interface Science, 165(1),
47-57.
Singh, S. (2006), "Impact of color on marketing", Management Decision, Vol. 44 No.
6, pp. 783-789.
Singh, S., Razak, M. A., Sangam, S. R., Viswanath, B., Begum, P. S., & Rajagopal, S.
(2018). The impact of functional food and nutraceuticals in health. In Therapeutic
Foods (pp. 23-47). Academic Press.
Siro, I., Kapolna, E., Kapolna, B., & Lugasi, A. (2008). Functional food. Product
development, marketing and consumer acceptance-A review. Appetite, 51(3), 456-467.
Sirvio, J. A., Visanko, M., Heiskanen, J. P., & Liimatainen, H. (2016). UV-absorbing
cellulose nanocrystals as functional reinforcing fillers in polymer nanocomposite
films. Journal of Materials Chemistry A, 4(17), 6368-6375.
Sopyan, I., & Gozali, D. (2020). A Review: A novel of efforts to enhance liposome
stability as drug delivery approach. Systematic Reviews in Pharmacy, 11(6).
Spinelli, S., Costa, C., Conte, A., La Porta, N., Padalino, L., & Del Nobile, M. A.
(2019). Bioactive compounds from Norway spruce bark: Comparison among
sustainable extraction techniques for potential food applications. Foods, 8(11), 524.
Stark, N. M. (2016). Opportunities for cellulose nanomaterials in packaging films: A
review and future trends. Journal of Renewable Materials, 4(5), 313-326.
178
Sułkowski, W. W., Pentak, D., Nowak, K., & Sułkowska, A. (2005). The influence of
temperature, cholesterol content and pH on liposome stability. Journal of Molecular
Structure, 744, 737-747.
Sun, G., Zhang, X. Z., & Chu, C. C. (2008). Effect of the molecular weight of
polyethylene glycol (PEG) on the properties of chitosan-PEG-poly (N-
isopropylacrylamide) hydrogels. Journal of Materials Science: Materials in
Medicine, 19(8), 2865-2872.
Sun, L., Wang, S., & Qiao, Z. (2006). Chemical stabilization of the phycocyanin from
cyanobacterium Spirulina platensis. Journal of Biotechnology, 121(4), 563-569.
Suzery, M., Majid, D., Setyawan, D., & Sutanto, H. (2017). Improvement of stability
and antioxidant activities by using phycocyanin-chitosan encapsulation technique.
In IOP Conference Series: Earth and Environmental Science (Vol. 55, No. 1, pp.
012052). IOP Publishing.
Sviderskyi, V., Melnyk, L., Shendera, A., & Fleisher, H. (2018). Rheological properties
of Polymer colloid–cellulose thickener systems. Chemistry & Chemical
Technology, 12(2), 207-212.
Szalontai, B., Gombos, Z., Csizmadia, V., & Lutz, M. (1987). The chromophore
structure and chromophore-protein interactions in C-phycocyanin as studied by
resonance Raman spectroscopy. Biochimica et Biophysica Acta (BBA)-Bioenergetics,
893(2), 296-304.
Tamjidi, F., Shahedi, M., Varshosaz, J., & Nasirpour, A. (2013). Nanostructured lipid
carriers (NLC): A potential delivery system for bioactive food molecules. Innovative
Food Science & Emerging Technologies, 19, 29-43.
Tan, J., da Silva, T. L. T., Martini, S., & Joyner, H. S. (2019). Numerical modeling of
wear behavior of solid fats. Journal of Food Engineering, 260, 12-21.
Tang, C., Spinney, S., Shi, Z., Tang, J., Peng, B., Luo, J., & Tam, K. C. (2018).
Amphiphilic cellulose nanocrystals for enhanced Pickering emulsion
stabilization. Langmuir, 34(43), 12897-12905.
Tang, J., Sisler, J., Grishkewich, N., & Tam, K. C. (2017). Functionalization of
cellulose nanocrystals for advanced applications. Journal of Colloid and Interface
Science, 494, 397-409.
179
Tao, H., Lavoine, N., Jiang, F., Tang, J., & Lin, N. (2020). Reducing end modification
on cellulose nanocrystals: strategy, characterization, applications and
challenges. Nanoscale Horizons, 5(4), 607-627.
Taylor, P., Xu, C., Fletcher, P. D., & Paunov, V. N. (2003). A novel technique for
preparation of monodisperse giant liposomes. Chemical Communications, (14), 1732-
1733.
Tikekar, R. V., Pan, Y., & Nitin, N. (2013). Fate of curcumin encapsulated in silica
nanoparticle stabilized Pickering emulsion during storage and simulated
digestion. Food Research International, 51(1), 370-377.
Toft, J., & Kvalheim, O. M. (1993). Eigenstructure tracking analysis for revealing noise
pattern and local rank in instrumental profiles: application to transmittance and
absorbance IR spectroscopy. Chemometrics and Intelligent Laboratory Systems, 19(1),
65-73.
Trache, D., Hussin, M. H., Haafiz, M. M., & Thakur, V. K. (2017). Recent progress in
cellulose nanocrystals: sources and production. Nanoscale, 9(5), 1763-1786.
U.S. Census Bureau (2016, June 12). Sumter county, fla., is nation’s oldest. Census
Bureau Reports. Retrieved 11 November 11, 2020, from
https://www.census.gov/newsroom/press-releases/2016/cb16-107.html
Ulrich, H. J., Stumm, W., & Cosovic, B. (1988). Adsorption of aliphatic fatty acids on
aquatic interfaces. Comparison between two model surfaces: the mercury electrode and
δ-Al2O3 colloids. Environmental Science & Technology, 22(1), 37-41.
Vafabakhsh, Z., Khosravi-Darani, K., Khajeh, K., Jahadi, M., Komeili, R., &
Mortazavian, A. M. (2013). Stability and catalytic kinetics of protease loaded
liposomes. Biochemical Engineering Journal, 72, 11-17.
van Aken, G. A., Bomhof, E., Zoet, F. D., Verbeek, M., & Oosterveld, A. (2011).
Differences in in vitro gastric behavior between homogenized milk and emulsions
stabilized by Tween 80, whey protein, or whey protein and caseinate. Food
Hydrocolloids, 25(4), 781-788.
Varanasi, S., Henzel, L., Mendoza, L., Prathapan, R., Batchelor, W., Tabor, R., &
Garnier, G. (2018). Pickering emulsions electrostatically stabilized by cellulose
nanocrystals. Frontiers in Chemistry, 6, 409.
180
Varka, E. M., Ampatzidis, C., Kostoglou, M., Karapantsios, T., & Dutschk, V. (2010).
On the use of electrical conductance measurements for the stability of oil-in-water
Pickering emulsions. Colloids and Surfaces A: Physicochemical and Engineering
Aspects, 365(1-3), 181-188.
Vespa, J., Armstrong, D. M., & Medina, L. (2019). Demographic turning points.
Population projections for the United States: 2020 to 2060. Retrieved October 08,
2020, from
https://www.census.gov/content/dam/Census/library/publications/2020/demo/p25-
1144.pdf
Viera, I., Pérez-Gálvez, A., & Roca, M. (2019). Green natural
colorants. Molecules, 24(1), 154.
Vignati, E., Piazza, R., & Lockhart, T. P. (2003). Pickering emulsions: interfacial
tension, colloidal layer morphology, and trapped-particle motion. Langmuir, 19(17),
6650-6656.
Wang, G., & Wang, T. (2008). Oxidative stability of egg and soy lecithin as affected
by transition metal ions and pH in emulsion. Journal of Agricultural and Food
Chemistry, 56(23), 11424-11431.
Wang, J., Wu, S., Suo, X. K., & Liao, H. (2019). The Processes for Fabricating
Nanopowders. In Advanced Nanomaterials and Coatings by Thermal Spray (pp. 13-
25). Elsevier.
Way, A. E., Hsu, L., Shanmuganathan, K., Weder, C., & Rowan, S. J. (2012). pH-
responsive cellulose nanocrystal gels and nanocomposites. ACS Macro Letters, 1(8),
1001-1006.
Whitby, C. P., Fischer, F. E., Fornasiero, D., & Ralston, J. (2011). Shear-induced
coalescence of oil-in-water Pickering emulsions. Journal of Colloid and Interface
Science, 361(1), 170-177.
Wilczek, M. M., Olszewski, R., & Krupienicz, A. (2017). Trans-fatty acids and
cardiovascular disease: urgent need for legislation. Cardiology, 138(4), 254-258.
181
Winuprasith, T., Khomein, P., Mitbumrung, W., Suphantharika, M., Nitithamyong, A.,
& McClements, D. J. (2018). Encapsulation of vitamin D3 in Pickering emulsions
stabilized by nanofibrillated mangosteen cellulose: Impact on in vitro digestion and
bioaccessibility. Food Hydrocolloids, 83, 153-164.
Woodle, M. C., Newman, M. S., & Working, P. K. (2018). Biological properties of
sterically stabilized liposomes. In Stealth liposomes (pp. 123-138). CRC Press.
Wooster, T. J. (2006). Studying the effect of steric layer thickness on emulsion
stability. Retrieved May 16, 2020, from https://www.atascientific.com.au/wp-
content/uploads/2017/02/Studying_the_Effect_of_Steric_Layer_Thickness_on_Emul
sion_Stability-1.pdf
Wu, J., Zhang, H., Chen, Y., Ma, L., Huang, H., ... & Zhang, Y. (2020). Recent
advances on cellulose nanocrystals for Pickering emulsions: Development and
challenge. Trends in Food Science & Technology, 102, 16-29.
Wu, X., Liu, Y., Liu, A., & Wang, W. (2017). Improved thermal-stability and
mechanical properties of type I collagen by crosslinking with casein, keratin and soy
protein isolate using transglutaminase. International Journal of Biological
Macromolecules, 98, 292-301.
Xiao, J., Lu, X., & Huang, Q. (2017). Double emulsion derived from kafirin
nanoparticles stabilized Pickering emulsion: Fabrication, microstructure, stability and
in vitro digestion profile. Food Hydrocolloids, 62, 230-238.
Xiao, Y. D., Huang, W. Y., Li, D. J., Song, J. F., Liu, C. Q., Wei, Q. Y., ... & Yang, Q.
M. (2018). Thermal degradation kinetics of all-trans and cis-carotenoids in a light-
induced model system. Food Chemistry, 239, 360-368.
Yadav, A., Murthy, M. S., Shete, A. S., & Sakhare, S. (2011). Stability aspects of
liposomes. Indian Journal of Pharmaceutical Education and Research, 45(4), 402-
413.
Yahya M, Lee HV, Abd Hamid SB (2015) Preparation of nanocellulose via transition
metal salt catalyzed hydrolysis pathway. BioResources, 10, 7627-7639.
Yan, M., Liu, B., Jiao, X., & Qin, S. (2014). Preparation of phycocyanin microcapsules
and its properties. Food and Bioproducts Processing, 92(1), 89-97.
182
Yang, J., Han, C. R., Duan, J. F., Xu, F., & Sun, R. C. (2013). Mechanical and
viscoelastic properties of cellulose nanocrystals reinforced poly (ethylene glycol)
nanocomposite hydrogels. ACS Applied Materials & Interfaces, 5(8), 3199-3207.
Yang, Y., Fang, Z., Chen, X., Zhang, W., Xie, Y., Chen, Y., ... & Yuan, W. (2017). An
overview of Pickering emulsions: solid-particle materials, classification, morphology,
and applications. Frontiers in Pharmacology, 8, 287.
Yang, Y., Marshall-Breton, C., Leser, M. E., Sher, A. A., & McClements, D. J. (2012).
Fabrication of ultrafine edible emulsions: Comparison of high-energy and low-energy
homogenization methods. Food Hydrocolloids, 29(2), 398-406.
Ye, F., Miao, M., Cui, S. W., Jiang, B., Jin, Z., & Li, X. (2018). Characterisations of
oil-in-water Pickering emulsion stabilized hydrophobic phytoglycogen
nanoparticles. Food Hydrocolloids, 76, 78-87.
Yokota, S., Kamada, K., Sugiyama, A., & Kondo, T. (2019). Pickering emulsion
stabilization by using amphiphilic cellulose nanofibrils prepared by aqueous counter
collision. Carbohydrate Polymers, 226, 115293.
Yoshikawa, T., Zhang, Z., Yamashita, K., & Noda, M. (2016). Biosensing of
interaction between phospholipid membrane of liposome as model cell membrane and
amyloid-beta protein in human serum by dielectric dispersion analysis. Sensors and
Actuators B: Chemical, 236, 1028-1035.
Zaborova, O. V., Filippov, S. K., Chytil, P., Kováčik, L., Ulbrich, K., Yaroslavov, A.
A., & Etrych, T. (2018). A novel approach to increase the stability of liposomal
containers via in prep coating by poly [N‐(2‐hydroxypropyl) methacrylamide] with
covalently attached cholesterol groups. Macromolecular Chemistry and Physics,
219(7), 1700508.
Zalipsky, S. (2018). Polyethylene glycol-lipid conjugates. In Stealth liposomes (pp.
113-122). CRC Press.
Zhang, H., Qian, Y., Chen, S. & Zhao, Y. (2019). Physicochemical characteristics and
emulsification properties of cellulose nanocrystals stabilized O/W Pickering emulsions
with high -OSO3- groups. Food Hydrocolloids 96, 267-277.
183
Zhang, L., Song, J., Kong, L., Yuan, T., Li, W., Zhang, W., ... & Du, G. (2020). The
strategies and techniques of drug discovery from natural products. Pharmacology &
Therapeutics, 107686.
Zoppe, J. O., Venditti, R. A., & Rojas, O. J. (2012). Pickering emulsions stabilized by
cellulose nanocrystals grafted with thermo-responsive polymer brushes. Journal of
Colloid and Interface Science, 369(1), 202-209.
184
BIOGRAPHY OF THE AUTHOR
Avinash Singh Patel was born in Varanasi, Uttar Pradesh state of India on May 07,
1992. He graduated in Biology from Mahatma Gandhi Kashi Vidyapith, Varanasi,
India in June 2012 and attended Center Food Science and Technology at the Banaras
Hindu University, Varanasi, India in July 2012 for his postgraduation study. Avinash
has worked for two and a half years as Senior Research Fellow at the Indian
Agricultural Research Institute, New Delhi, India. He is a recipient of the Netaji Subhas
ICAR Fellowship in 2016. He is a candidate for the Doctor of Philosophy degree in
Food and Nutrition Sciences from the University of Maine in December 2020.
