Fig 2: Schematic model of the role of aging and DJ-1 in the regulation of oxidative stress responses in the RPE and retina. Aging and low-level oxidative stress resulted in no visible degeneration, increased GFAP, and Nile red labeling in WT retinas. However, aging results in increased GFAP and Nile red labeling in DJ-1 KO retinas, while low-level oxidative stress results in retinal degeneration, decreased Nile red, and increased AGEs in the DJ-1 KO retinas. In young mice, expression levels of antioxidant genes were significantly upregulated in the RPE, but downregulated in the retina, of DJ-1 KO mice compared with WT mice. In old mice, expression levels of these genes were significantly downregulated in RPE, but remained unchanged in the retina, of DJ-1 KO mice compared with WT mice. In young mice, low-level oxidative stress upregulated gene expression in the retina of both mice. In young RPE, the majority of genes were not significantly altered in WT mice but were significantly downregulated in DJ-1 KO mice. In old mice, low-level oxidative stress resulted in no modulation of antioxidant gene expression in the retina. Meanwhile, a few of the genes were upregulated in the RPE of WT but not DJ-1 KO mice. (Reprinted with the permission of the Cleveland Clinic Center for Medical Art & Photography © 2019. All Rights Reserved). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig 3: De novo upregulation of SUR1-TRPM4 in dorsal horn astrocytes at spinal segment L3-4 after PNI. (a) and (b) Double immunolabeling for GFAP (red) and SUR1 (green) at low (a) and high (b) magnification, ipsilateral (Ipsi) and contralateral (Contra) to sciatic n. cuffing; superimposed images in (a), right and (b), right. (c) Quantification of SUR1 in the ipsilateral GFAP-positive region of interest in control (CTR) and on pod-1–14 after sciatic n. cuffing; data from 4 CTR mice and 11 with PNI, 2–3 mice/time point; **, P < 0.01. (d) Abcc8 mRNA upregulation relative to S18 shown by qPCR of ipsilateral dorsal horn (PNI) vs. sham; 3 mice/group; *, P < 0.05. (e) Double immunolabeling for SUR1 and Iba1 shows minimal overlap. (f) Analysis of SUR1 co-localization with GFAP, Iba1 and MBP after PNI using Pearson’s correlation coefficient, demonstrating a predominant astrocytic localization; 3 mice/group. (g) Double immunolabeling for SUR1 and TRPM4, ipsilateral to PNI; superimposed images are shown (right). (h) Quantification of TRPM4 in the ipsilateral GFAP-positive region of interest in control (CTR) and on pod-14 after sciatic n. cuffing; data from 4 CTR mice and 5 mice with PNI; **, P < 0.01. I,J: Proximity ligation assay (PLA) for SUR1 and TRPM4 (red) and GFAP immunolabeling (green), at low (i) and high (j) magnification, ipsilateral to sciatic n. cuffing in sham CTR, after PNI in WT mice, and after PNI in mice with pGfap-cre-driven Abcc8 deletion. (k) Quantification of SUR1-TRPM4 PLA in the ipsilateral dorsal horn on pod-14 after sciatic n. cuffing in sham CTR, after PNI in WT mice, and after PNI in mice with pGfap-cre-driven Abcc8 deletion; data from 4, 5 and 5 mice, respectively; **, P < 0.01 with respect to CTR; ##, P < 0.01 with respect to PNI in WT.

Fig 4: Transcriptional profiling of the neurovascular unit of COVID-19 and control brains(A) Schematic representation of the spatial transcriptomic analysis of the neurovascular unit in human brain tissue with the Nanostring DSP platform. Brain tissue sections were stained for abundant cell populations (here: CD31, CD45, GFAP, and nuclei) and hybridized with a library of photocleavable probes for a specific gene panel. Regions of interest are chosen and illuminated, and the hybridized probes are collected only there. Downstream analyses of the collected probes provide a representative picture of RNA expression of genes of interest in this specific location, here, the neurovascular unit.(B) Representative images of cortical regions of control (top) and COVID-19 brains (bottom), stained for GFAP (green), CD31 (yellow), CD45 (red), and DNA (blue). Two representative ROIs that were used for transcriptional analyses are shown. Scale bar, 250 µm; close up, 75 µm.(C) Heatmap summarizing all differentially regulated genes. Gene-dependent h-clustering was performed. Color shows row Z score.(D) Volcano plot showing differentially up- (red) and downregulated (blue) genes. Top differentially regulated genes are labeled.(E) Normalized expression of IFITM1 (top) and IFITM2 (bottom). Shapiro-Wilk tests followed by Mann-Whitney U tests were performed. *p = 0.03 for IFITM1, *p = 0.01 for IFITM2.(F) Gene set enrichment analysis of all detected genes. Color shows log2 fold change.(G) Representative images for IFITM2 staining in brain tissue of control and COVID-19 patients. Images of age-matched pairs are displayed, demonstrating expression of IFITM2 in the neurovascular unit and its upregulation in fatal COVID-19. Scale bar, 50 µm.

Fig 5: Neuroinflammation and neurodegeneration analysis in the hippocampus and cortex. (A) Confocal micrographs depicting Iba1-, CD11b- and GFAP-immunolabeled cells in the cornus amonis CA1/CA3 and dentate gyrus (DG) of the hippocampus or in the cortex, and cortical immunolabeling of glutamine synthetase (GS). Typical surveillant and activated microglia (Iba1+ and CD11b+) phenotypes are indicated by the arrowheads, and expanded below the cortex micrograph. (B) HFHSD had no impact on the Iba1+ area or number of microglia cells, but increased the fraction of activated microglia, which was normalized by diet reversal. (C) Astrocytes were considered all GS+ and/or GFAP+ cells. HFHSD had no impact on the area occupied by GS+ cells or number of astrocytes. (D) Total Iba1 and GFAP levels in the hippocampus or cortex were similar across the experimental groups. (E) Expression of NF-?ß and cytokines in the hippocampus, relative to the 60S ribosomal protein L14. (F) NeuN immunolabeling of neuronal somata was used to estimate the number of mature neurons in the cortex and within the granule cell layer of CA1, CA3 and DG. (G) Doublecortin (DCX)-immunolabeling was used to count immature neurons. DCX+ cells are estimated per DG within a stained brain slice. Dashed lines in micrographs define the granule cell layer in CA1, CA3 and DG. Data is plotted as mean±SD of n=6-8 (half of either gender). Letters over data-points indicate significant differences relative to CD or as indicated (a P<0.05, b P<0.01, c P<0.001) based on Fisher’s LSD post hoc comparison following presence of significant effects of diet or interaction between diet and time in ANOVA tests.