title: An efficient and reproducible method for quantifying macrophages in different experimental models of central nervous system pathology.
abstract: Historically, microglia/macrophages are quantified in the pathological central nervous system (CNS) by counting cell profiles then expressing the data as cells/mm(2). However, because it is difficult to visualize individual cells in dense clusters and in most cases it is unimportant to know the absolute number of macrophages within lesioned tissue, alternative methods may be more efficient for quantifying the magnitude of the macrophage response in the context of different experimental variables (e.g., therapeutic intervention or time post-injury/infection). The present study provides the first in-depth comparison of different techniques commonly used to quantify microglial/macrophage reactions in the pathological spinal cord. Individuals from the same and different laboratories applied techniques of digital image analysis (DIA), standard cell profile counting and a computer-assisted cell counting method with unbiased sampling to quantify macrophages in focal inflammatory lesions, disseminated lesions caused by autoimmune inflammation or at sites of spinal trauma. Our goal was to find a simple, rapid and sensitive method with minimal variability between trials and users. DIA was consistently the least variable and most time-efficient method for assessing the magnitude of macrophage responses across lesions and between users. When used to evaluate the efficacy of an anti-inflammatory treatment, DIA was 5-35 x faster than cell counting and was sensitive enough to detect group differences while eliminating inter-user variability. Since lesions are clearly defined and single profiles of microglia/macrophages are difficult to discern in most pathological specimens of brain or spinal cord, DIA offers significant advantages over other techniques for quantifying activated macrophages.
authors.affiliation: The Integrated Biomedical Graduate Studies Program, The Ohio State University College of Medicine, Columbus, OH, USA.
authors.forename: Dustin J
authors.initials: DJ
authors.lastname: Donnelly
authors.forename: John C
authors.initials: JC
authors.lastname: Gensel
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Ankeny
authors.forename: Nico
authors.initials: N
authors.lastname: van Rooijen
authors.forename: Phillip G
authors.initials: PG
authors.lastname: Popovich
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D039481:CD11b Antigen / Q000378:metabolism; D002135:Calcium-Binding Proteins; D002452:Cell Count / Q000379:methods; D004268:DNA-Binding Proteins / Q000378:metabolism; D004195:Disease Models, Animal; D004681:Encephalomyelitis, Autoimmune, Experimental / Q000473:pathology*; D005260:Female; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008264:Macrophages / Q000473:pathology* / Q000502:physiology*; D051379:Mice; D008810:Mice, Inbred C57BL; D008840:Microfilament Proteins; D017628:Microglia / Q000473:pathology; D015203:Reproducibility of Results; D013116:Spinal Cord / Q000473:pathology*
chemical_list: C112986:AIF1 protein, human; D039481:CD11b Antigen; D002135:Calcium-Binding Proteins; D004268:DNA-Binding Proteins; D008840:Microfilament Proteins