Novel Infrared Spectroscopic and Imaging Tools For Quality Control

Christian Huck

Institute of Analytical Chemistry and Radiochemistry, University Innsbruck

Austria

AOAC, October 11th 2011

Seite 2

Agenda / Summary slide

Motivation

NIR - Applications

Imaging Techniques

1

2

3

4

Guideline

Fundamentals

Motivation

Plant

Phytomics/Metabolomics

Production Patient

Extraction

Pretreatment

Product

Step 1 Step 2 Step 3 Step 4 Step 5

Approaches

MALDI-TOF-MS/MS

Matrixfree-MALDI

MELDI-TOF

MALDI-imaging/mapping

Near-infrared

Mid-Infrared

Imaging/mapping

Enrichment

Desalting

High-sample througput

LC, LC-MS/MS

µ-LC, µ-LC-MS/MS

CE, CE-MS

CEC

Innovations

Motivation

Non-invasive

Simultaneous determination of

several parameters

Physical and chemical

parameters

Increase in selecticity, speed

High-Throughput

Alternative method

COSTS

Nr of Samples

Fingerprint technique

off-, on- and even in-line

W. Herschel, "Investigation of the powers of the prismatic colours to heat and illuminate objects", Phil. Trans. (1800) 255.Herschel, W., "Experiments on the refrangibility of the invisible rays of the sun.", Phil Trans. (1800) 284.

Frederick William Herschel

(1738 - 1822)

Stretching vibration

Discovery of Infrared Vibration

Infrared spectroscopy

The Electromagnetic Spectrum

Micro- Far Mid NIRVisible

Ultra- Vacuum X-Ray

10 5000 2500 800 400 170 20 nm

10 200 4000 12500 25000 60000

6

5*10 5 cm -1

Overtones

ofMolecular

vibrations

Electronic transitions

rotation vibrations Inner shell

electrons

wave IR IR violet UV

stretch

bend

v

Valenceelectrons ionisation

Molecular bond

HIGH

PHOTON

ENERGY

LOW

PHOTON

ENERGY

Model of the Oscillator

2

1oscosc hE

2

2

1

2

1oscoscosc hhE

χ = anharmonicity constant

Mid-Infrared Near-Infrared

Instrumentation

MIR/NIR chemical

imaging

NIR spectroscopy

FTIR-ATR

spectroscopy

IR fingerprint1082

1170

1244

1301

1395

1451

1450

1656

2872

2957

3057

3304

2921

966

1068

1171

1239

1376

1467

1706

2853

3012

699

1090

1243

1395

1486

1601

1706

2957

1000 1500 2000 2500 3000 3500

Wavenumber [cm-1]

Absorb

an

ce

DNA

Lipids

Proteins

The NIR spectrum is a

fingerprint of the

investigated material.

It is characteristic of its

chemical and physical

properties.

Spectral characteristics

Wavenumber [cm-1] Assignation

~3300 amide A, νN-H of proteins

~3100 amide B, ν N-H with 1. overtone of the amide I band resonant (Fermi), proteins

~3010 ν C-H, lipids, cholesterols, esters

~2920

alternatively 2850

ν C-H (>CH2, Methyl) antisymmetric/symmetric, lipids, proteins, carbohydrates, esters

~2956

alternatively 2872

ν C-H (CH3, Methyl) antisymmetric/symmetric, lipids, proteins, carbohydrates, nucleic

acids

~1745-1735 ν C=O, esters and phospholipids

~1620-1695 amide I-band, proteins

~1550 amide II-band, proteins

~1400 ν C=O of COO--group, fatty acids and amino acids

~1360-1260 amide III-band absorptions (predominantly C-N stretching) with significant

contributions from ν CH2 of carbohydrate residues

~1350-1260 ν PO2-

~1310-1240 amide III-band, proteins

~1250-1220 ν P=O symmetric of the>PO2- groups, phospholipids, nucleic acids

~1225 ν PO2- asymmetric of nucleic acids and phospholipids

~1185-1120 C-O ring vibrations of nucleic acid “sugars”

~1084 ν P=O symmetric of the >PO2- groups nucleic acids, phospholipids

Overview of prominent bands of complex biological samples (4000 cm-1 to 750 cm-1)

RAMAN MID-INFRARED NEAR-INFRARED

M m

HOMONUCLEAR POLAR

e.g. C=C FUNCTIONALITIES e.g. C=O FUNCTIONALITIES

HIGH STRUCTURAL SELECTIVITYLOW STRUCTURAL

SELECTIVITY

0q

0q

0q

ANHARMONICITY

m<<M

CH / OH / NH

/

OFTEN CHEMOMETRICS

NECESSARY

polarizability dipole moment mechanical anharmonicity

Why can we see a signal ?

Measurement Principle

detector

diffuse

reflection

detector

transmission

monochromator

sample

physical properties

particle size, porosity,…

chemical properties

Surface modification,…

sp

ec

tra

chemometrics /

multivariate data analysis

qualitative analysis

quantitative analysis

INTERACTANCE

Fibre optic probe

T R I

I0 It

I0

TRANSMISSION REFLECTANCE

or transflectance

0-45 optics or

integrating sphere

Ir+

-

I0

∞

It=0

NIR – Sample presentation modes

MID-INFRARED NEAR-INFRARED

NO SAMPLE PREPARATION

ONLY VIA ATR

NO SAMPLE

PREPARATION

• NON-INVASIVE FOR HIGH SAMPLE THROUGHPUT

Sample preparation

Source Monochromator Detector

Globar

Tungsten-

Halogen Lamp

Grating

Interferometer

AOTF

MCT

InGaAs, InSb

PbS, Si, Ge

Diode-Array

Sample Sample

or

Instrumentation

Source

Mirrors

Detector

Sample

Beam Splitter

Lightfiber-Bundle

Probe Head with Sapphire Window

Optical Fiber Probe

M: Mirrors S: Sample

: Angle of Incidence

M

4

M

1

M

2

M

3

S

S

Attenuated Total Reflection

Multiple Sample Interaction

Chemometrics

PCA

PLS

NIR - Chemometrics

Univariate / Multivariate Analysis

NIR Strategy of Analysis

Sinupret

Optimization of thereference method

Optimization of theNIR-parameters

NIRHPLCContent of the

leading compound3´,4´,5´-trimethoxyflavone

Content of Flos Primulae veris

HPLC Content of the otherleading compounds

Content of other

plants in Sinupret

Optimization of thereference method

®

®

CH3

O

O

O

O

O

CH3

H

HH

H

H

H

H

CH3

Choice of Sample Set

Frequent Distribution of

Calibration Samples

CONCENTRATION

FR

EQ

UE

NC

Y

Preferential Distribution of

Calibration Samples

CONCENTRATION

FR

EQ

UE

NC

Y

NIR Strategy of Analysis

Charge Area Primula Conc. LC NIR-MW Water EtOH(µV*sec) (g/100g) (ng/µl) (ng/µl) (%) (%)

91102064 28.10.91 70490 0,493 0,219 0,219 80,38 15,7

91112182 05.11.91 71740 0,500 0,222 0,210 80,83 15,2

91112191 08.11.91 61346 0,442 0,197 0,230 80,25 15,7

91112302 22.11.91 66799 0,472 0,210 0,186 81,33 14,5

91112311 28.11.91 81551 0,555 0,245 0,193 79,69 15,7

O

O

O

O

O

CH3

H

HH

H

H

H

H

CH3

CH3

3´,4´,5´- TrimethoxyflavoneLeading Compound 0.14

0.16

0.18

0.20

0.22

0.24

0.26

0.28

0.30

0.16 0.18 0.20 0.22 0.24 0.26 0.28 0.30

True value (HPLC)P

red

icte

d v

alu

e (N

IRS)

R2 0,9594SEE 0,0057SEP 0,0099BIAS –0,0389

1st derivativeNormalisation

10 14 18 22 26 30

10

14

18

22

26

30

vor a

usgesagt e

Wer t

e

True values

EtOH

Reference method: GC

vo

rau

sg

esagte

Wert

e69 73 77 81 85 89

True values

69

73

77

81

85

89

Water

Reference method: Karl-Fischer

NIRS-Analysis of Water- and Ethanol Content

NIRS of Naphthodianthrones and

Phloroglucines in St. John´s Wort

a

b

t ime [ min]

t ime [ min] t ime [ min]

t ime [ min]

AU

AU AU

AU

Determination of (a) naphthodianthrones and (b) phloroglucines.Conditions: Hypersil BDS-C18 (5 µm, 130 Å, 250 × 4 mm); mobilephase, A: 888.0 g buffer (880.0 g bidest, 2 ml 85% H3PO4, TEA (pH2.80)), 80.0 g ACN, B: 49.64 g buffer (50.0 g Bidest, 1 ml 85% H3PO4,TEA (pH 6.10)), 85.04 g methanol, 275.28 g ACN; linearer gradient;sample volume, 20 µl; peak assignment, PrPH, protopseudohypericin;PH, pseudohypericin; CPH, cyclopseudohypericin; PrH, protohypericin;H, hypericin; Hf, hyperforin; Ahf, adhyperforin.

C.W. Huck, G. Abel, M. Popp, G.K. Bonn, „Analysis of naphthodianthrone and phloroglucin

derivatives in St. John´s Wort extracts by near infrared spectroscopy (NIRS) compared to

high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE)”, Anal.

Chim. Acta (2006) doi:10.1016/j.aca.2006.07.062

NIRS of Naphthodianthrones and

Phloroglucines in St. John´s Wort

NIR spectra(a) Original spectra, (b) pretreated spectra Predicted (NIRS) vs. True values (LC)

(a) Hypericin, (b) Hyperforin(n=80). (a) R2=0.99; SEP=0.68; (b) R2=0.99; SEP=0.72

a

b

Quality Control of Achillea Species

Loadings-plot (multiple compound model, MCM)of the four species of Achillea genus. A. millefolium(mil), A. clypeolata (cly), A. collina (col), A. nobilis(nob).

PLS regression lines of the SCM

model for determining the n-

decanoic acid content in the A.

millefolium.

Cluster Analysis Quantitative Analysis

Cooperation with Prof. Guo Lanping, CACMS, Beijing

and Prof. B. Kopp, University Vienna

Antioxidative Potential

Reference: DPPH

Total Phenolic Content

Reference: Folin-Ciocalteau

Total Flavonoid Content

Achillea millefolium, Achillea absinthium,

Artemisa annua, Fagopyrum esculentum,

Genista tinctoria, Gynostemma

pentaphyllum, Leonurus sibiricus,

Mentha arvensis, Origanum dictamnus,

Reseda luteola, Scutellaria baicalensis,

Spilanthes acmella, Tanacetum

parthenium

NIRS Method for the Non-Invasive Determination

of Total Flavonoid, Total Phenol Content and

Antioxidative Potential in Herba

- F -

- S -

1 65432 87 9

Preparative TLC of Flos Primulae veris and RadixPrimulae veris, stationary phase: SiO2 60 F254

20x20, thin layer thickness: 1 mm; mobile phase:chloroform/acetone = 55 / 10; volume: 100 µl;detection: UV 365 nm 1 - 3 = Flos Primulae(butanol), 4 = DC-isolated substance, 5 - 7 = RadexPrimulae, 8 - 9 = purified extract of Flos Primulae.

IR – TLC Mapping of Flavonoids and Leading

Compounds in Phytopharmaceutical Preparations

Quality control of Scutellaria via NIRS

Scatter plot of predicted (NIRS) vs. true

property (HPLC) for determination of baicalein

(B) in radix scutellariae. B shows anti-

inflammatory, antiviral (HIV) , anti-tumor,

antioxidant, free radical scavenging and anti-

SARS coronavirus effects

Principal components score image of the wild and

cultivated radix scutellariae samples.

Dr. Li Hua, China Academy of Traditional Chinese Medicine, Beijing, China

Surface enhanced infrared – Spectroscopy

(SEIRS)

Bsp.

Trypsine

Absolute 1.5 µg

GOLD CARRIER

CaF2

Amid I+II Bande

Surface enhanced infrared – Spectroscopy

(SEIRS)

Tablet Production – On-line Analysis

PLS calibrations

Assay

Acetone

Water

Laboratory probe Process probe

R e f e r e n c e v a l u e s ( % )

N I R

P

r e

d i

c t

i o

n s

(

% )

Infrared Imaging Spectroscopy

Step The Stage To Generate Any Size

Image…

16 element array views sample in blocks of

100 x 6.25 or 400 x 25

Up to 5 steps per second and 80 spectra

per second at 16 cm-1

Hyperspectral cube

Spectrum: from 1 to k at pixel (ni,

mj)

IR image plane:

n m pixels at i

A typical

hyperspectral cube

has up to several

(ten)thousand

spectra.

1

k

ni, mj

i

P. Wilhelm et al.,

Spectroscopy Europe, pp14-19

(May 2004)

SEM

micrograph

Conservative versus imagingspectrosopy

Conservative

Spectroscopy

Single

Detector

Array

Detector

Imaging

Spectroscopy Irradiated

area

Sample

Sample

Irradiated

area

(A)

(B)

The spectrum is

representative

for total

irradiated sample

area

The spectrarecorded by the

individual detectors

represent an image of the

irradiated sample area

Infrared Imaging Spectroscopy

3.9 x 3.9 mm2

20 x ATR-Objective

(Microscope)

260 x 260 m2

50 x 50 m2

3.9 x 3.9 mm2

15 x Objective

(Microscope; Transmission)

1 : 1 Image

(Macro Chamber; Transmission, ATR)

61 m res

10 m res

4 m res

Detector

Workflow

TissueSectioning

Tissue mounting on IR-Window

IR Micro-spectrometry and Imaging

IR Spectra Spectral Diagnose

Image reassembling

Application – Urtica dioica root

1800 1700 1600 1500 1400 1300 1200 1100 1000 900 800

1631

1426

1152

1020

1731

1592

15051456

13691317

1241 1159

1106

1051

1033

1731

1596

14211369

1316

1153

1101

1025

Wavenumber cm-1

Ab

sorb

ance

Rhizodermis

Plerom

Periblem

IR spectra from 800 to 1800 cm-1 of a Urtica sp. root

IR spectroscopic 3 D - imaging

(B)

(C) (D)

(A)

Rhizodermis

Periblem

Plerom

1662-1645 cm-1

1591-1528 cm-1 1138-988 cm-1

A) Optical microscopic image

B) amide I-band proteins

C) amide II-band proteins

D) carbohydrates, nucleic acids and phospholipids

univariate

Ester (1770-1708 cm-1)

Protein Amide II (1563-1480 cm-1)Cellulose OH (3350-3590 cm-1)

Total Scan

IR spectroscopic 2 D - imaging

univariate

Cluster analysis

(B)

(C) (D)

(A)

Rhizodermis

Periblem

Plerom

HCA-Clustering

FCM-Clustering KMC-Clustering

Optical Image

A) Optical microscopic

image

B) Hierarchical cluster

analysis

C) K-means clustering

D) Fuzzy C-means

clustering

multivariate

IR spectroscopic 3 D – hyper space imaging

IR spectroscopic 3 D – hyper space imaging

Prostate tissue

(A) HE stained diagnostic slide:1. cancer2. stroma3. benign glands

(B) nucleic acids, cholesterolphospholipids and ester

(C) proteins(D) lipids and carbohydrates

Principal component analysis (PCA)Each colored data point represents oneregion of interest (ROI). The data setswere chosen from tumor- (red) andstroma- (green) tissue region, which areco-registered with the scanned H&E

C. Pezzei, J. D. Pallua, G. Schaefer, C. Seifarth,V. Huck-Pezzei, L. K. Bittner, H. Klocker, G.Bartsch, G. K. Bonn, C. W. Huck*, Prostatecancer characterization by Fourier Transforminfrared microspectroscopy. Mol. Biosys, 2010,6, 2287

IR Imaging of Prostate Tissue

Imaging Active Ingredients in Tablets

Image Microscopic Picture

Acknowledgements

Prof. Yang Bin, China Academy of TCM, Beijing China

Prof. Dr. M. Popp, Prof. Dr. G. Abel

Prof. Dean Guo, Shanghai Institute of Materia Medica, China

Prof. Kopp, University Vienna, Austria

Prof. Bauer, University Graz, Austria

Prof. Stuppner, University Innsbruck, Austria

I will be happy to answer !

Questions?