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1.
Exp Eye Res ; 203: 108416, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33359513

RESUMO

Microglia are immune cells of the central nervous system capable of distinct phenotypic changes and migration in response to injury. These changes most notably include the retraction of fine dendritic structures and adoption of a globular, phagocytic morphology. Due to their characteristic responses, microglia frequently act as histological indicators of injury progression. While algorithms seeking to automate microglia counts and morphological analysis are becoming increasingly popular, few exist that are adequate for use within the retina and manual analysis remains prevalent. To address this, we propose a novel segmentation routine, implemented within FIJI-ImageJ, to perform automated segmentation and cell counting of retinal microglia. We show that our routine could perform cell counts with accuracy similar to manual observers using the I307N Rho model. Tracking cell position relative to retinal vasculature, we observed population migration towards the photoreceptor layer beginning 12 h post light damage. Using feature selection with Chi2 and principal component analysis, we resolved cells along a morphological gradient, demonstrating that extracted features were sufficiently descriptive to capture subtle morphological changes within cell populations in I307N Rho and Balb/c TLR2-/- retinal degeneration models. Taken together, we introduce a novel automated routine capable of efficient image processing and segmentation. Using data retrieved following segmentation, we perform morphological analysis simultaneously on whole populations of cells, rather than individually. Our algorithm was built entirely with open-source software, for use on retinal microglia.


Assuntos
Processamento de Imagem Assistida por Computador/métodos , Luz/efeitos adversos , Microglia/patologia , Lesões Experimentais por Radiação/etiologia , Retina/efeitos da radiação , Degeneração Retiniana/etiologia , Algoritmos , Animais , Contagem de Células , Modelos Animais de Doenças , Imageamento Tridimensional , Imuno-Histoquímica , Camundongos , Camundongos Endogâmicos BALB C , Camundongos Endogâmicos C57BL , Lesões Experimentais por Radiação/patologia , Degeneração Retiniana/patologia , Vasos Retinianos/patologia
2.
Sci Rep ; 10(1): 16967, 2020 10 12.
Artigo em Inglês | MEDLINE | ID: mdl-33046772

RESUMO

Retinitis pigmentosa (RP) is a group of blinding disorders caused by diverse mutations, including in rhodopsin (RHO). Effective therapies have yet to be discovered. The I307N Rho mouse is a light-inducible model of autosomal dominant RP. Our purpose was to describe the glial response in this mouse model to educate future experimentation. I307N Rho mice were exposed to 20,000 lx of light for thirty minutes to induce retinal degeneration. Immunofluorescence staining of cross-sections and flat-mounts was performed to visualize the response of microglia and Müller glia. Histology was correlated with spectral-domain optical coherence tomography imaging (SD-OCT). Microglia dendrites extended between photoreceptors within two hours of induction, withdrew their dendrites between twelve hours and one day, appeared ameboid by three days, and assumed a ramified morphology by one month. Glial activation was more robust in the inferior retina and modulated across the boundary of light damage. SD-OCT hyper-reflectivity overlapped with activated microglia. Finally, microglia transiently adhered to the RPE before which RPE cells appeared dysmorphic. Our data demonstrate the spatial and temporal pattern of glial activation in the I307N Rho mouse, and correlate these patterns with SD-OCT images, assisting in interpretation of SD-OCT images in preclinical models and in human RP.


Assuntos
Dendritos/patologia , Genes Dominantes , Microglia/patologia , Retinose Pigmentar/genética , Retinose Pigmentar/patologia , Animais , Modelos Animais de Doenças , Humanos , Camundongos , Mutação , Células Fotorreceptoras de Vertebrados/patologia , Degeneração Retiniana/patologia , Retinose Pigmentar/diagnóstico por imagem , Retinose Pigmentar/etiologia , Rodopsina/genética , Tomografia de Coerência Óptica/métodos
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