Metabolic syndrome, which includes diabetes and obesity, is one of the most widespread medical conditions. It induces systemic inflammation, causing far reaching effects on the body that are still being uncovered. Neuropathologies triggered by metabolic syndrome often result from increased permeability of the blood–brain-barrier (BBB). The BBB, a system designed to restrict entry of toxins, immune cells, and pathogens to the brain, is vital for proper neuronal function. Local and systemic inflammation induced by obesity or type 2 diabetes mellitus can cause BBB breakdown, decreased removal of waste, and increased infiltration of immune cells. This leads to disruption of glial and neuronal cells, causing hormonal dysregulation, increased immune sensitivity, or cognitive impairment depending on the affected brain region. Inflammatory effects of metabolic syndrome have been linked to neurodegenerative diseases. In this review, we discuss the effects of obesity and diabetes-induced inflammation on the BBB, the roles played by leptin and insulin resistance, as well as BBB changes occurring at the molecular level. We explore signaling pathways including VEGF, HIFs, PKC, Rho/ROCK, eNOS, and miRNAs. Finally, we discuss the broader implications of neural inflammation, including its connection to Alzheimer’s disease, multiple sclerosis, and the gut microbiome.

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Fetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI, funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workflow. Open-access fetal fMRI data with manual brain masks from 159 fetuses (1103 total volumes) were used for training and testing the U-net model. We also tested generalizability of the model using 82 locally acquired functional scans from 19 fetuses, which included over 2300 manually segmented volumes. Dice metrics were used to compare performance of funcmasker-flex to the ground truth manually segmented volumes, and segmentations were consistently robust (all Dice metrics ≥0.74). The tool is freely available and can be applied to any BIDS dataset containing fetal bold sequences. Funcmasker-flex reduces the need for manual segmentation, even when applied to novel fetal functional datasets, resulting in significant time-cost savings for performing fetal fMRI analysis.

Astrocytes are intimately linked with brain blood vessels, an essential relationship for neuronal function. However, astroglial factors driving these physical and functional associations during postnatal brain development have yet to be identified. By characterizing structural and transcriptional changes in mouse cortical astrocytes during the first two postnatal weeks, we find that high-mobility group box 1 (Hmgb1), normally upregulated with injury and involved in adult cerebrovascular repair, is highly expressed in astrocytes at birth and then decreases rapidly. Astrocyte-selective ablation of Hmgb1 at birth affects astrocyte morphology and endfoot placement, alters distribution of endfoot proteins connexin43 and aquaporin-4, induces transcriptional changes in astrocytes related to cytoskeleton remodeling, and profoundly disrupts endothelial ultrastructure. While lack of astroglial Hmgb1 does not affect the blood-brain barrier or angiogenesis postnatally, it impairs neurovascular coupling and behavior in adult mice. These findings identify astroglial Hmgb1 as an important player in postnatal gliovascular maturation.

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