RESEARCH Open Access Quantitative assessment of microglial ...€¦ · (length, process volume, and so on) [14]. Our results pro-vide the first comprehensive quantitative mapping

JOURNAL OF NEUROINFLAMMATION

Kongsui et al. Journal of Neuroinflammation 2014, 11:182http://www.jneuroinflammation.com/content/11/1/182

RESEARCH Open Access

Quantitative assessment of microglial morphologyand density reveals remarkable consistency in thedistribution and morphology of cells within thehealthy prefrontal cortex of the ratRatchaniporn Kongsui1,2,3, Sarah B Beynon1,2,3, Sarah J Johnson4 and Frederick Rohan Walker1,2,3,5*

Abstract

Background: Microglial morphology within the healthy brain has been the subject of a number of observationalstudies. These have suggested that microglia may consist of separate classes, which possess substantially differentmorphological features. Critically, there have been no systematic quantitative studies of microglial morphologywithin the healthy brain.

Methods: We examined microglial cells within the adult rat prefrontal cortex. At high magnification, digitalreconstructions of cells labelled with the microglial-specific marker ionized calcium-binding adapter molecule-1(Iba-1) were made in each of the cortical layers. These reconstructions were subsequently analyzed to determinethe convex hull area of the cells, their somal perimeter, the length of processes, the number of processes, theextent of process branching and the volume of processes. We additionally examined whether cells’ morphologicalfeatures were associated with cell size or numerical density.

Results: Our analysis indicated that while there was substantial variability in the size of cells within the prefrontalcortex, cellular morphology was extremely consistent within each of the cortical layers.

Conclusions: Our results provide quantitative confirmation that microglia are largely homogenous in the uninjuredrodent prefrontal cortex.

Keywords: Iba-1, Microglia, Morphology, Prefrontal cortex

BackgroundTo date, the majority of morphological characterization ofmicroglia has occurred in situations of extensive neuroin-flammation (Alzheimer’s disease, Parkinson’s disease, trau-matic brain injury and stroke) [1-7]. Accordingly, ourcurrent understanding of microglial form has been heavilyinfluenced by the study of these cells in their reactive state.By comparison, there is relatively little information con-cerning the morphological characteristics of microglia inthe nondiseased brain. Such information, however, may beof considerable importance, given emerging evidence of

* Correspondence: [email protected] of Biomedical Sciences and Pharmacy, University of Newcastle,Callaghan, NSW, Australia2Priority Research Centre for Brain and Mental Health Research, University ofNewcastle, Callaghan, NSW, AustraliaFull list of author information is available at the end of the article

© 2014 Kongsui et al.; licensee BioMed CentraCommons Attribution License (http://creativecreproduction in any medium, provided the orDedication waiver (http://creativecommons.orunless otherwise stated.

the cells’ involvement in synaptic modelling within thehealthy brain [8-13].Several recent studies have indicated that normal envir-

onmental challenges, for instance changes in sensory ex-perience or exposure to stress, can provoke structuralremodelling of ramified microglia in the absence of anynotable inflammatory disturbance [10,14]. These changesdraw attention to the richness of microglial morphologicaltransformation within the healthy brain [15]. Presently,however, no wholly quantitative studies have been under-taken to identify definitively what the typical properties ofmicroglia are in the rodent. A long history of detailed obser-vational studies of microglial morphology describe widelyvarying cellular structures. Particularly notable amongstthese, Lawson et al. [16] described clear regional differencesin microglial morphology, describing the occurrence of

l Ltd. This is an Open Access article distributed under the terms of the Creativeommons.org/licenses/by/4.0), which permits unrestricted use, distribution, andiginal work is properly credited. The Creative Commons Public Domaing/publicdomain/zero/1.0/) applies to the data made available in this article,

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Kongsui et al. Journal of Neuroinflammation 2014, 11:182 Page 2 of 9http://www.jneuroinflammation.com/content/11/1/182

compact (round, short processes), longitudinally branched(long primary processes) and radially branched (tortuousprocesses with secondary branching) microglia. Lawsonet al. did also note that microglia in each of these classesdiffered somewhat in area and perimeter across each ofthe regions examined. Vela et al. [17], examining the rep-resentation of microglial forms across the mammaliancerebellum, observed that microglial morphology variedaccording to the cells’ extracellular environment. Their re-search suggested that microglial structure might vary in amanner that is dependent upon the synaptic activitywithin a given region, with white matter containing flat-tened microglia, whose processes extended parallel to theaxon projections, and cerebellar nuclei accompanied byhighly branched microglia that extended in all directions.In one of the few studies to examine microglia quantita-tively, Jinno et al. [18] identified that microglia appear tobe homogenously distributed within the hippocampus ofthe adult rat. A more recent study by Yamada and Jinno[19] is the first to classify microglia on the basis of quanti-tative measurements. Following hypoglossal axotomy, theauthors grouped microglia according to discrete morpho-logical measurements, revealing that compromised neuraltissue contains microglia that progress from highly rami-fied to compact, thickened processes. However, theirmodel focused on microglial structure following injury,which would likely have different characteristics from thatof the uninjured brain. Collectively, these studies havesuggested that ramified microglia may fall into distinctcategories based on their morphology and may differ sig-nificantly in their form in a location dependent manner.Recently, Torres-Platas et al. [20] published the first

detailed quantitative neuroanatomical examination ofmicroglia in the human prefrontal cortex and also foundevidence of distinct morphological phenotypes. Specifically,the authors identified four classes of microglia: classicallyramified microglia; primed microglia (wider cell body withstandard ramified processes); reactive microglia (wider cellbody, few ramified processes), and amoeboid microglia.The authors also undertook an observational analysis ofmouse microglia and identified a significantly higher levelof consistency, with the majority of cells being of theramified phenotype.Given Torres-Platas et al.’s recent findings, it is of con-

siderable interest to understand how microglia within theprefrontal cortex of the rat, one of the most commonlyused laboratory species, compares with that observed inthe human brain. Accordingly, we undertook a detailedquantitative analysis of microglia within the prefrontal cor-tex of healthy adult rats. To examine changes in the ratprefrontal cortex, we immunohistochemically identifiedmicroglia, in coronally sectioned tissues, using ionizedcalcium-binding adapter molecule-1 (Iba-1) labelling. Iba-1is a 17 kDa EF hand protein that plays a critical role in the

bundling of F-actin, and is centrally involved in cytoskeletalreorganization [21]. As such, Iba-1 represents an excellentlabelling target to examine morphological changes inmicroglia, and has been used extensively for this purpose[18,22,23]. We created digital reconstructions of Iba-1-labelled microglia from the adult rat prefrontal cortex.Once reconstructed, we examined differences in cellulararea, perimeter, process number, process length, processvolume, soma size and fractal complexity by assessingoverall changes and using Sholl analysis. We further exam-ined differences in metrics within the entire prefrontal cor-tex and across layers (I to VI). We identified substantialdifferences in the area occupied by microglia throughoutthe prefrontal cortex. As we have previously observed thatpsychological stress can differentially influence large andsmall microglia, we also further investigated the relation-ship between cell area and each of the listed metrics(length, process volume, and so on) [14]. Our results pro-vide the first comprehensive quantitative mapping ofmicroglial morphology in the rat prefrontal cortex, andextensively substantiate previous observational work.

MethodsEthics statementExperiments were approved by the University of NewcastleAnimal Care and Ethics Committee and were conductedin strict accordance with the NSW Animal Research Actand Australian code of practice for the use of animals forscientific purposes.

Experimental animalsAdult male Sprague-Dawley rats (N =10; 350 to 450 g; 70days old) were obtained from the Animal Resource Centre(Perth, Western Australia). Animals were acclimatized for1 week in individual cages in temperature-controlledanimal holding rooms (21 ± 1°C) on a 12 h reverse light-dark cycle (lights on at 19:00).

Tissue processing and immunohistochemistryAnimals were deeply anaesthetized with sodium pentobar-bital and transcardially perfused via the ascending aortawith 2% sodium nitrite followed by 4% ice-cold parafor-maldehyde. Brains were removed and post-fixed overnightin the same fixative and then placed into 12.5% sucrose forcryoprotection. Brains were cut into 30 μm sections usinga freezing microtome (Leica, Germany).As previously described [24], coronal sections were

incubated in rabbit polyclonal anti-Iba-1 (1:10,000;Wako Bioproducts, Japan), followed by anti-rabbit sec-ondary antibody (1:500; Jackson Immunoresearch, PA,USA). Iba-1-specific labelling was visualized with anickel-enhanced 3′3-diaminobenzidine reaction. Brainregions were located anatomically in accordance with astereotaxic rat brain atlas, which identified sections


between Bregma coordinates +2.2 and +3.2 (anterior-posterior) as containing the prefrontal cortex (Figure 1A;[25]). Within this region the cortex was divided furtherinto its five layers according to cortical depth from the pialsurface: Layer I, 17.8%; Layer II, 27.9%; Layer III, 46.6%;Layer V, 73.0%; and Layer VI, 100% (Figure 1B; [26,27]).

Microglial reconstructionMicroglia in the prefrontal cortex were reconstructedusing a computer-assisted morphometry system consist-ing of a Zeiss Axioskop photomicroscope equipped withan MAC 6000 XYZ computer-controlled motorizedstage and joystick with focus control (Ludl ElectronicProducts, NY, USA), a Q Imaging video camera (MBFBiosciences, VT, USA), and Neurolucida morphometricsoftware (MBF Biosciences, VT, USA). Microglia werevisualized and reconstructed under a Zeiss Axio Plan ob-jective (NEOFLUAR × 100 objective with a numericalaperture of 1.3 under oil immersion) using Neurolucidasoftware (Figure 1A. Only microglia that displayed intactprocesses unobscured by background labelling or othercells were included in reconstructions. Microglia weretraced throughout the entire thickness of the section,and trace information was then rendered into a 2-dimensional diagram of each cell (Figure 1B). Five cellsper region were randomly selected for a total of 250 cellsincluded for analysis. Cells were ranked in quartiles ac-cording to overall cell size (Q1 = 709.92 to 1,059.68 μm2;Q2 = 1,097.23 to 1,489.34 μm2; Q3 = 1,510.63 to 2,027.75μm2; Q4 = 2,036.26 to 3,784.34 μm2).

Analysis of reconstructed cellsNeuroExplorer software (MBF Biosciences, VT, USA)was used to generate metric analyses of reconstructedmicroglia. The cell body perimeter, number of primaryprocesses, number of nodes (branch points), total lengthof all processes, and total volume of all processes weremeasured. The area encompassed by the entire cell was

Figure 1 Microglia in the prefrontal cortex. (A) Cells were imagedusing a 100× objective on a Zeiss AxioSkop if their processes couldbe fully visualized within the given section. (B) Imaged cells weretraced and ordered according to size (smallest to largest, Q1 to Q4).Scale bars =20 μm.

measured as the convex hull area, determined from thepolygon created from straight lines connecting the mostdistal points of the microglial processes. A box countingprotocol determined the fractal dimension of each cell(k-dim) to determine how fully the cell occupied its con-vex hull area [28]. To account for changes in the cell’scomplexity in relation to distance from the cell soma,Sholl analyses were performed for each microglial cell.Concentric circles (radii) were spaced 5 μm apart, ori-ginating from the soma [29]. The number of branchpoints (nodes) and processes that intersected the radii,and process length, surface area, volume and averagediameter were measured as a function of the distancefrom the cell soma for each radius.

Absolute cell counts and density estimatesMicroglia numbers were exhaustively counted in threesections containing the prefrontal cortex. The regionwas defined as before, and consisted of the region be-tween the forceps minor and the pial surface, approxi-mately 1 mm in width, and extending in height for 1mm from the base of the forceps minor to the borderwith the prelimbic cortex, at Bregma coordinates +2.5,+2.7 and +2.9 (anterior-posterior), according to Paxinosand Watson [25]. The left hemisphere from each sectionwas imaged on a Zeiss Axioskop with Zeiss Axio Planobjective (Neofluor 10× objective) to contain the entireregion within one field of view, and converted to a bin-ary image using Metamorph software (MDS AnalyticalTechnologies, version 7.5.4.0, CA, USA). Each microglialcell within the region was counted and marked to yieldx-y coordinates of each cell. Cellular coordinates werethen extracted and processed in MatLab (Version7.9.0.529 (R2009b), Mathworks, Inc.). The prefrontalcortex was divided into a grid of three by five equallysized rectangles, and the number of cells in each onecounted. These counts were then used to generate heatmaps illustrating the cellular distribution. Overall cellu-lar density measurements were calculated using theformula:

D ¼X

Q= A� Tð Þ;

where ∑Q is the total number of cells in the prefrontalcortex, A is the area of the prefrontal cortex and T is thesection thickness.

Statistical analysisGroup averages for microglia from each cortical layer werecompared using one-way analysis of variance (ANOVA)followed by post-hoc testing with Bonferroni’s correction.Sholl analyses for microglia grouped by cortical layer orsize were compared using one-way ANOVA of groupmeans followed by post-hoc testing. An overall group effect


was determined using the trapezoidal area under eachSholl curve. Bivariate correlations were calculated for mor-phological parameters according to convex hull area. Allstatistical work was performed in IBM SPSS Statistics ver-sion 19.

ResultsMicroglial cells displayed remarkably consistent morph-ologies across all cortical layers, with only a few signifi-cant variations in structure. Indeed, the only differencewe observed was that Layer II microglia possessed sig-nificantly fewer processes than microglia in Layer III orV (Table 1). The microglia within the prefrontal cortexotherwise appeared to be relatively homogenous, onaverage exhibiting between four and five primary pro-cesses that branched on average two times each.Sholl analysis of microglial cells from cortical layers of

the prefrontal cortex did not reveal any further varia-tions in morphological characteristics (Figure 2). In alllayers, microglia followed a similar pattern where thehighest degree of branching and the largest, thickestprocesses were located approximately 10 to 20 μm fromthe soma. After this point, these features steadily de-creased the farther they travelled from the microglial cellbody. Furthermore, for all microglia, processes displayedthe largest diameter at the most proximal position to thesoma, and then tapered towards the distal ends. Nooverall group differences between layers were detected.Our frequency analysis of convex hull areas indicated

that while the size distribution was considerable (800 to3,800 μm2), the distribution was unmistakably unimodal(Figure 3). However, as previous research had indicatedthat microglial cell size can differentially influence cellu-lar morphology in response to environmental challenges[14], we investigated whether the size of microglial cellsimpacts structural characteristics in the normal brain.Correlation of microglial size with morphological param-eters revealed significant correlations with cell complex-ity, branch points, total process length and total processvolume (Figure 4). Thus, larger cells tended to have

Table 1 Morphological characteristics of forebrain microglia

Layer I Layer II

Fractal dimension (k-dim) 0.992 (0.008) 0.980 (0.009)

Convex hull area (μm2) 1,605.52 (88.36) 1,818.78 (95.61)

Cell body perimeter (μm) 34.43 (0.98) 33.81 (1.13)

Branch points 10.81 (0.60) 10.59 (0.54)

Total process length (μm) 243.72 (12.44) 257.63 (12.81)

Total process volume (μm3) 54.13 (4.68) 55.49 (4.32)

Number of processes 4.51 (0.16) 4.39* (0.19)

Microglia from each cortical layer were assessed for size and complexity of branchas mean (± standard error of the mean); *P

Figure 2 Microglial morphology is consistent across cortical layers of the prefrontal cortex. Sholl analysis of microglia according to corticallayer location yielded regular patterns of morphological characteristics. Maxima for all measures were observed approximately 15 μm from thesoma, followed by steady tapering in size and complexity. Values are expressed as mean ± standard error of the mean.


DiscussionThis study is the first to systematically quantify microglialmorphology within the prefrontal cortex of healthy adultrats. The most striking finding to emerge from this study isthe remarkable consistency of microglial morphologyacross each of the cortical layers (I to VI). Despite this lam-inar consistency, microglia were found to vary substantially

Figure 3 Microglia in the prefrontal cortex have a wide rangeof sizes. A frequency histogram of all microglial cells sampledrevealed a right-tailed distribution with a range of approximately3,000 μm2.

with respect to the area that they occupy within the paren-chyma (ranging from 800 to 3,800 μm2). Indeed, analysisof the morphological properties of microglia based on sizerevealed some intriguing phenomena. For instance, while astrong positive relationship was observed between theoverall area of the microglial cell and the magnitude of cer-tain morphological features, not all characteristics were af-fected equally. Similarly, when we compared the propertiesof cells grouped in quartiles according to area, our analysisrevealed that the averages for each quartile did not alwayschange in a graduated pattern. Collectively, these results in-dicate that while the morphology of microglia appear quitehomogenous ‘on average’, there are clear morphological dif-ferences, particularly with respect to size, that suggest theexistence of some degree of cellular specialisation.Absolute microglial cell counts provided important

population information regarding cell representationwithin the prefrontal cortex. Astroglial cells (positive forglial fibrillary acidic protein) are known to exhibit strongmedial-lateral differences within the prefrontal cortex,however, microglial cells have never been examined inthe naïve prefrontal cortex in this way [18]. We foundno difference in microglial cell number in either themedial-lateral or the anterior-posterior directions in theprefrontal cortex. Our observations demonstrate that thedistribution of microglia within the prefrontal cortex is

Figure 4 Microglial size affects the extent of ramification. Bivariate correlation of morphological characteristics with overall microglial cell sizerevealed that increasing cell size directly correlated with an increase in process size and complexity. * P

Table 2 Number and density of microglia in the forebrain

Bregma (anterior-posterior) Single section count (cells) Density (cells/μm3)

+2.5 257.90 (7.28) 9.55 (0.27)

+2.7 244.60 (5.65) 9.06 (0.21)

+2.9 246.20 (4.87) 9.12 (0.18)

Microglia were exhaustively counted within the prefrontal cortex at each Bregma level to yield counts within a single section. Densities were calculated for thevolume between one Bregma level and the next. Values represent means (± standard error of the mean).


relatively homogenous in the absence of injury or in-flammation. From a functional perspective, this form ofdispersion is consistent with the increasingly popularview that microglia actively survey their environment,and their arrangement at regularly-spaced intervals per-mits efficient monitoring [9,12].To assess microglial morphology, we created high-

resolution digital reconstructions of Iba-1-labelledmicroglia, in order to provide the greatest sensitivity totheir intricate morphological features [30]. With respectto our analysis in this study, we identified that the fractaldimension, convex hull area, cell body perimeter, num-ber of branch points, total process length, total processvolume and total numbers of processes were remarkablyconsistent on average across each of the cortical layers.Similarly, our Sholl analysis (that is, our assessment ofthe morphological differences in relation to the radialdistance from the soma) of each of the measured mor-phological parameters was also remarkably consistent

Figure 6 Heat maps demonstrating microglial representation in prefryielded x-y coordinates for each cell. (A) Coordinates were converted into reprfor analysis of population differences. The point (0, 0) represents the most ventrelatively heavily populated regions while blue indicates relatively lightly popul

across layers. While this latter finding might have beenpredicted by consideration of the averages alone, it wasin principle possible for each of the metrics to peak atdifferent points across the layers, a situation that wouldhave had no influence on the averages. Thus, it seemsreasonable to conclude that the morphology of microgliaacross each of the cortical layers is extremely similar. Italso appears possible to conclude, given this consistency,that the density of cells does not meaningfully alter themorphological properties of cells in this region.One result that was of particular note was the

between-cell variability in overall (convex hull) area,which ranged from 800 to 3,800 μm2. Such size variabil-ity has not been previously reported. Our analysis of thedistribution of cell areas revealed an unmistakablyGaussian curve, with the majority (68%) of cells posses-sing an area of 1,130.94 to 2,231.05 μm2. We expectedthat each of the cells’ morphological characteristics(process number, process length, and so on) would

ontal cortex, Bregma +2.5 mm. Absolute cell counts of microgliaesentative heat maps for the region, which was divided into a 3 × 5 gridral point on the pial surface of the prefrontal cortex. Red indicatesated regions. (B) Two-dimensional representation of microglial population.


correlate with the overall area of the cell, as observed inmicroglia from brains post-injury [31]. Surprisingly, thiswas true for some metrics but not others. Specifically,we observed a very strong positive correlation betweenmicroglial process length (r = 0.8624) and branch num-ber (r = 0.6583) with the cells’ overall area. In contrast,there was no observable relationship between microglialarea and the cells’ somal perimeter, fractal complexity, orthe number of primary processes. Our Sholl analysis, onthe basis of cells grouped by quartile according to theirarea, showed a strong relationship between microglialprocess length, branch number and branch volume withthe cells’ overall area.Perhaps one of the more interesting findings to emerge

from this analysis is the relative comparisons that are nowpossible between rat and human microglia. For instance,Torres-Platas et al. [20] identified that ramified microgliain the human prefrontal cortex have on average 5.8 (±0.5)primary processes (that is, those that emerge from the cellbody), and we have determined that there are approxi-mately 5 (±0.2) for the rat. This result is striking in itssimilarity. However, other metrics do not align as closely.For instance, the extent of primary process branchingwould appear to be much higher in the human prefrontalcortex, with an average of 46 branch points being ob-served for the human parenchymal microglia, whereas theaverage in the rat is only 16. Consistent with this finding,the cumulative length of branches in the human pre-frontal cortex is much higher: 590 μm versus an averageof approximately 250 μm for the rat. It is, certainly, tempt-ing to speculate, given recent findings concerning the roleof microglia in monitoring synaptic junctions, that thehigher levels of branching in human microglia might beassociated with increased neuronal number and synapticdensity in our species [9,10,32].This study significantly advances understanding of

microglial morphology within the cerebral cortex. Micro-glia from the healthy brain have been previously describedas belonging to either a compact, longitudinally branched,or radially branched group [16]. Here, we quantified thecharacteristics of microglia belonging to the radiallybranched group, which show that while laminar divisionsdo not affect morphology, size varies markedly. However,our observations are also consistent with the proposal thatthe local environment may dictate microglial morphology.Indeed, the laminar homogeneity of microglial morph-ology is perhaps peculiar to the cerebral cortex, as Velaet al. [17] have noted a distinct medial-lateral pattern tomicroglial branching within the cerebellar cortex. In theirstudy, the authors reported that microglia in the outerlayers ran parallel to the pial surface, whereas microglia inthe medial regions of the cerebellum had more primaryprocesses that extensively branched. These observationswere quite unlike those of the present work, where

primary processes rarely varied, and branching was notdifferent across cortical layers. The differences may reflectthe greater heterogeneity of cellular components withinthe cerebellum, which is distinctly divided amongst whitematter tracts and neuronal nuclei, while the prefrontalcortex consists mainly of neuronal cell bodies.One potential caveat associated with the interpretation

of results presented in this study is the method of section-ing that was used. Specifically, the sections that we in-cluded in the study were taken through the coronal planeand in undertaking our analysis we ensured that each ofthe reconstructed cells was fully located within this planeof the section. Cells that had obviously been bisected dur-ing the sectioning process were not included for analysis.As many of the microglia were 40 to 50 μm in diameter,and our section thickness was 30 μm, we cannot rule thepossibility that our analysis approach did not provide anaccurate representation of the microglia that were primar-ily orientated within the sagittal plane. Accordingly, webelieve it is important that our results can only be consid-ered to be representative of those cells orientated withinthe coronal plane of the prefrontal cortex.

ConclusionsKnowledge of the role played by microglia within thehealthy brain has, in recent years, begun to dramatically ex-pand. While these cells were once considered to be primar-ily involved in the response to injury, it is now clear thatthey also play a direct role in monitoring synaptic functionin the healthy brain [12,13]. Moreover, it is now recognizedthat the cells can be disturbed by significant changes in sen-sory experience, such as changes in the level of light orstressful situations [10,14,19]. It is primarily because of theirrole in regulating normal homeostatic processes that micro-glia have remained unappreciated and have not been exten-sively studied under nonpathological conditions. Indeed,many fundamental neuroanatomical questions that havebeen completely resolved for other cell types, such as neu-rons, remain largely unaddressed for microglia. This issuewas the primary motivation for undertaking this study,namely, to systematically characterize the density andmorphology of microglial cells in the prefrontal cortex. Inbroad terms, our results reveal that the distribution of cellswithin the cortex appears remarkably homogenous, withthe same types occurring in all regions in the same propor-tions. With that said, however, there are also some strikingdifferences, particularly in relation to the size of microglia.This study clearly demonstrates that microglia within thecortex are heterogeneous with respect to size. This is apotentially important finding, given that it is now being rec-ognized that astrocytes, which were also once essentiallyconsidered to be homogenous, possess quite distinct mor-phological, molecular and functional properties [7,33,34].Accordingly, an obvious question for future studies to


address is whether or not microglia that possess quitedistinct sizes (and morphological properties) also differ withrespect to their functional and molecular signatures.

AbbreviationsANOVA: analysis of variance; Iba-1: ionized calcium-binding adaptermolecule-1.

Competing interestsThe authors declare that they have no competing interests.

Authors’ contributionsRK carried out the immunohistochemistry and image analysis. SBBparticipated in the statistical analysis and helped to draft the manuscript.SJJ designed the MatLab program to compute cell density heat maps. FRWconceived the study, participated in its design and coordination, and helpedto draft the manuscript. All authors have read and agree with the contentsof the manuscript.

Author details1School of Biomedical Sciences and Pharmacy, University of Newcastle,Callaghan, NSW, Australia. 2Priority Research Centre for Brain and MentalHealth Research, University of Newcastle, Callaghan, NSW, Australia. 3HunterMedical Research Institute, Newcastle, NSW, Australia. 4School of ElectricalEngineering and Computer Science, University of Newcastle, Callaghan, NSW,Australia. 5Laboratory of Affective Neuroscience, School of BiomedicalSciences, University of Newcastle, Callaghan, NSW, Australia.

Received: 18 September 2014 Accepted: 10 October 2014

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doi:10.1186/s12974-014-0182-7Cite this article as: Kongsui et al.: Quantitative assessment of microglialmorphology and density reveals remarkable consistency in thedistribution and morphology of cells within the healthy prefrontal cortexof the rat. Journal of Neuroinflammation 2014 11:182.

AbstractBackgroundMethodsResultsConclusions

BackgroundMethodsEthics statementExperimental animalsTissue processing and immunohistochemistryMicroglial reconstructionAnalysis of reconstructed cellsAbsolute cell counts and density estimatesStatistical analysis

ResultsDiscussionConclusionsAbbreviationsCompeting interestsAuthors’ contributionsAuthor detailsReferences

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RESEARCH Open Access Quantitative assessment of microglial ...€¦ · (length, process volume, and so on) [14]. Our results pro-vide the first comprehensive quantitative mapping