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An automated method to quantify microglia morphology and application to monitor activation state longitudinally in vivo.

ABSTRACT: Microglia are specialized immune cells of the brain. Upon insult, microglia initiate a cascade of cellular responses including a characteristic change in cell morphology. To study the dynamics of microglia immune response in situ, we developed an automated image analysis method that enables the quantitative assessment of microglia activation state within tissue based solely on cell morphology. Per cell morphometric analysis of fluorescently labeled microglia is achieved through local iterative threshold segmentation, which reduces errors caused by signal-to-noise variation across large volumes. We demonstrate, utilizing systemic application of lipopolysaccharide as a model of immune challenge, that several morphological parameters, including cell perimeter length, cell roundness and soma size, quantitatively distinguish resting versus activated populations of microglia within tissue comparable to traditional immunohistochemistry methods. Furthermore, we provide proof-of-concept data that monitoring soma size enables the longitudinal assessment of microglia activation in the mouse neocortex imaged via 2-photon in vivo microscopy. The ability to quantify microglia activation automatically by shape alone allows unbiased and rapid analysis of both fixed and in vivo central nervous system tissue.

SUBMITTER: Kozlowski C

PROVIDER: S-EPMC3294422 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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An automated method to quantify microglia morphology and application to monitor activation state longitudinally in vivo.

Kozlowski Cleopatra C Weimer Robby M RM

PloS one 20120228 2

Microglia are specialized immune cells of the brain. Upon insult, microglia initiate a cascade of cellular responses including a characteristic change in cell morphology. To study the dynamics of microglia immune response in situ, we developed an automated image analysis method that enables the quantitative assessment of microglia activation state within tissue based solely on cell morphology. Per cell morphometric analysis of fluorescently labeled microglia is achieved through local iterative t ...[more]

PMID: 22457705

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Project description:Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with human structural brain development is not yet well characterized. Here, we analyzed 1243 longitudinally acquired structural MRI scans from 623 youth (299 female/324 male) to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were stable between ages 5 and 25. Surface-based shape analysis revealed that higher SES is associated with areal expansion of lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and ventrolateral thalamic, and medial amygdalo-hippocampal subregions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Although SES is clearly a complex construct that likely relates to development through diverse, nondeterministic processes, our findings elucidate potential neuroanatomical mediators of the association between SES and cognitive outcomes.SIGNIFICANCE STATEMENT Childhood socioeconomic status (SES) has been associated with developmental disparities in mental health, cognitive ability, and academic achievement, but efforts to understand underlying SES-brain relationships are ongoing. Here, we leverage a unique developmental neuroimaging dataset to longitudinally map the associations between SES and regional brain anatomy at high spatiotemporal resolution. We find widespread associations between SES and global cortical and subcortical volumes and surface area and localize these correlations to a distributed set of cortical, thalamic, and amygdalo-hippocampal subregions. Anatomical variation within a subset of these regions partially mediates the positive relationship between SES and IQ. Our findings help to localize cortical and subcortical systems that represent candidate biological substrates for the known relationships between SES and cognition.

Dataset Information

An automated method to quantify microglia morphology and application to monitor activation state longitudinally in vivo.

Publications

An automated method to quantify microglia morphology and application to monitor activation state longitudinally in vivo.

Similar Datasets

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