Neonatal hypoxic-ischemic encephalopathy (HIE), caused by a lack of blood flow and oxygen to the brain, is a major cause of infant mortality. Primary and secondary energy failure caused by HIE activates microglia, resulting in morphological changes and inflammatory cascades that mediate ongoing pathology. Proinflammatory microglia release cytokines and reactive oxygen species that damage oligodendrocytes, the myelinating cells in the brain that supports neuronal function, thereby causing demyelination of neurons. Previous studies in term-equivalent in vivo ferret models showed that microglia respond to injury and treatments with region-dependent cell morphology changes. However, the effect of combinatorial therapy on microglia and oligodendrocyte in a preterm model is unknown. This project aims to quantify image-based morphological features of microglia and oligodendrocyte in response to neuroinflammation and separate and combinatorial treatments in different brain regions of an in vivo preterm ferret model. Using machine learning supported image processing, I quantified microglia and oligodendrocyte morphology in the healthy control group, injury group of two hours of oxygen-glucose deprivation, and treatment groups of azithromycin (AZ), erythropoietin (Epo), and combined AZ+Epo treatment followed by injury. The machine learning algorithm clusters microglia and oligodendrocytes into distinct shape modes with different morphological parameters, such as perimeter, circularity, and aspect ratio. Perimeter and circularity of both microglia and oligodendrocytes show regional heterogeneity within each shape mode while aspect ratio is homogeneous. Microglia perimeter decreases upon injury in crescent and rod-like shape modes. Epo treatment reverses the decrease to the level of nontreated control, but AZ+Epo treatment only partially reversed the decrease. By quantifying microglia and oligodendrocyte morphological response to neuroinflammation and treatments across regions, I non-destructively assessed therapeutic performance of separate and combinatorial treatments in the preterm ferret model. The assessed performance informs therapeutic choices for preterm populations and have the potential for translating to larger animal models.

Immunofluorescent images are a common way to analyze cell response in the presence of brain disease. Microglia - the brain's immune cells - have a range of functional states dependent on their local environment to keep the brain environment healthy. Microglia are typically stained and viewed with immunofluorescent imaging to study the brain's immune response. Microglial functionality and microglia morphology (shape) are highly correlated [5]. By taking and quantifying images of microglia in healthy and diseased brains, we can gain insights into their functional state and their local environment. In addition, most fundamental research about microglia involves the use of animal models, where many species are used to model brain disease. However, limited research directly compares microglia response in one species to another. Previously, research within the Nance Lab has focused on quantifying rat microglial features such as area, perimeter, or circularity [3]. Here, we developed a method to quantify features of microglia, with a focus on microglial branching – the arm-like protrusions from the cell body expanding upon previous work by adding additional branching features to the quantification pipeline to look at the number and length of branches around each cell, which gives us information on the functional state of the cell. We investigated the species-dependent effect on the microglial shape by analyzing images of cells obtained from the neonatal human-term equivalent rat (postnatal day 10, P10), ferret (P21), and mouse (P12). We see qualitative differences in morphology, such as more extensive branching in the rat compared to the ferret. Our ongoing work aims to quantify feature differences in microglia between the rat and ferret and expand to other species.