Reactive astrogliosis is a condition where astrocytes, a type of brain cell, undergo morphological – shape - changes upon exposure to brain injury. Morphological changes of astrocytes are a key indicator of activation and can be beneficial in stopping initial brain injury effects, but chronic activation can drive glial scarring, which is detrimental for full recovery of normal brain function. Glial scarring has been linked to several diseases, including traumatic brain injury, Alzheimer’s Disease, and dementia. The purpose of this work is to quantitatively analyze the relationship between frequency and extent of reactive astrogliosis with relation to distance from the primary site of brain injury. My approach is to build a Python-based image analysis pipeline to quantify astrocyte cell features. The Nance Lab’s prior work using Python packages was effective in developing a pipeline to identify and quantify microglial - a different type of brain cell - shape properties. We are now building a pipeline to study astrocytes in brain slices from the injured preterm ferret brain, which were stained with an antibody for glial fibrillary acidic protein (GFAP). Images of cells at 20x magnification are provided by Dr. Tommy Wood. Since response to injury can be brain region and animal sex dependent, I analyze astrocyte cell features in each region of the brain from both sexes of ferrets. I used SciKit-Image along with other packages to segment, label, and quantify features of our cells, including perimeter, area, and circularity, among others. Expected results include a significant reduction in area and an increase in perimeter (larger surface-to-volume ratio) of cells that are closer to the injury. This image analysis pipeline will give us quantitative information about the cells morphology which are associated with biological markers that can be targets for future therapeutic treatment. Clear biological markers help researchers develop better treatment.

Brain extracellular matrix (ECM) structure mediates many aspects of neuronal function. When ECM structure becomes dysregulated in neurological disease, one resulting impact is impaired neuronal function. Therefore, probing changes in the ECM structure could provide insights into disease mechanisms and expose potential therapeutic pathways. Previous work in our group determined that degrading neural ECM structures leads to a significant increase in the diffusive ability of nanoparticles navigating the brain extracellular space. However, this diffusion-based analysis provides little insight into changes in ECM-specific morphology or structure; analysis only predicts if they are present and the degree of alteration from normal. With this project, we aimed to characterize changes in perineuronal net (PNN) structure with high spatial resolution using a fluorescence-based imaging approach. PNNs, a structure that impact neuronal function were stained using a fluorescently labeled lectin (Wisteria floribunda agglutinin) and images acquired via confocal microscopy. Images were collected from the cortex of brains spanning an age range of post-natal day 14 to adulthood. We first manually quantified morphological features associated with PNNs, including the total number of branches, average branch length, and total branch length using the image processing program ImageJ. To reduce image processing time and minimize user-bias, I am building a Python-based, automated quantification workflow for future use. Regarding the manually quantified PNN features, we observed an increase in both the total branch length/PNN and average branch length/PNN as brains increased in age. The total number of branches/PNN remained relatively consistent across age groups. Future work will focus on applying the same approach to a model of neonatal hypoxia ischemia to study injury effect on PNN structure. Collectively, this project established a methodology that can be applied for enhanced characterization of ECM-related structural changes induced by neurological disease, and has the potential to unveil new avenues of therapeutic intervention.

The study of cell morphology is important and prevalent in understanding normal and pathological conditions in the brain. Brain cells are common targets for treatment for brain diseases. Specifically, microglia – the brain’s resident immune cells – undergo a range of morphological changes in response to injury and are targets of many mitigating treatments. Image processing has been a valuable tool to assess microglial cell morphology via the analysis of microglial shape features and there continue to be additional opportunities for further investigation. Prior research has indicated a connection between features such as solidity and extent, two shape features that measure the ratio of cell areas. In this study, we examine three shape features of fluorescently labeled microglia: Euler number, extent, and solidity, in the context of ischemic injury. Ischemic injury was modeled using oxygen-glucose deprivation (OGD) in cultured whole hemisphere brain slices. Using python, images were thresholded with the Otsu threshold. Shape features were extracted from the binarized images. These shape features were analyzed based on brain region (cortex, hippocampus, thalamus), generalized treatment type (non-treated, injured, injured with treatment), and specific treatment type (OGD 0.5 hour, 1.5 hours, 3 hours, 1.5 hours with azithromycin treatment, 3 hours with superoxide dismutase treatment) and visualized using seaborn. The results verified trends in effects of injury and recovery after treatment on extent and solidity. Both findings support the expected shift from a circular shape of microglia in the injured state to more branched in the healthier state. The Otsu thresholding is limited in its accuracy, and, hence, these results provide an opportunity to optimize cell segmentation protocol for higher quality thresholded images. The results of this work have the potential to be applied to various forms of injury and cell types.

Vulnerable immigration statuses in Latinx children in the US are often associated with poor health, development and social service access. This adversity can be mitigated by positive and responsive parenting that promotes resilience and supports the childhood stress of migration. In this study, we aimed to understand the parenting strengths, stressors and law needs of Latinx families in order to adapt a brief, responsive parenting behavioral skills intervention—Social, Emotional, and Academic Competence for Children and Parents (SEACAP) and pair it with immigration law and policy education and resources. We conducted 15 qualitative interviews, 30-60 minutes in length, with Latinx parents of young children with vulnerable immigration status. The interviews were conducted by a bilingual-bicultural member of the study team in Spanish. The interviews were recorded, transcribed and organized using Dedoose software; and reviewed by myself and additional research associates using thematic analysis coding methodology to segment and categorize important concepts within our dataset by generating codes. A codebook was created with the consensus of a coding team using Dedoose software. There have been a total of 15 qualitative interviews conducted, transcribed, coded and are currently in process of further thematic analysis. Preliminary major code themes that have been revealed include: Migration Strengths and Stressors, Stress Level Comparison, Push/ Pull factors and Health. The themes identified in the ongoing analyses will inform the adaptation of the SEACAP curriculum and the development of the law and policy education and resources to support Latinx families with vulnerable immigration status. Implemented through community partnered organizations, this program aims to provide parents with information about warm, consistent parenting and scaffolding to improve children’s development of self-regulation and positive social, emotional and academic outcomes. This program will also include legal advice and information related to immigration and education, offered by the North West Justice Project.