Fig 2: HH induces microglial activation triggering brain edema. C57BL/6J mice were exposed to HH (7000 m above sea level) for 48 h. (A) Brain water content was measured by the wet–dry weight method. (B–E) Mice were injected with Evens blue via tail vein for 1 h and subsequently perfused with normal saline to remove the dye from the circulation. (B) The whole brain was harvested to observe Evans blue infiltrated in blood vessels and tissues. (C) One half brain was homogenized to quantified dye content by spectrophotometric method. (D and E) Another half brain was sectioned for confocal imaging at 647 nm laser (D) and quantified by Image J software (E). (F and G) Brain sections were incubated with anti-Iba1 antibody to label microglia (F) and evaluate cell activation by counting fluorescence intensity (G). (H) mRNA levels of pro-inflammatory factors Rela, Tnfa, and Il1b in the cortex tissue were measured by real-time PCR. (I and J) Brain sections were co-incubated with anti-Iba1 antibody and anti-AQP4 (I) or anti-Laminin antibody (J) to label microglia and vessel to observe the vascular localization of microglia. (K–M) C57BL/6J mice were pretreated with PLX5622 followed by exposure to HH. (K) Brain sections were incubated with anti-Iba1 antibody to label microglia. (L) Brain water content was measured by the wet–dry weight method. (M) mRNA levels of pro-inflammatory factors Rela, Tnfa, and Il1b in the cortex tissue were measured by real-time PCR. n = 5, *P < 0.05, **P < 0.01, and ***P < 0.001 by Student's t-test.

Fig 3: AQP4 overexpression improves neurobehavioral dysfunction in SAH mice. AAV-specific overexpression of AQP4 is beneficial to the early recovery of neurological function after SAH. (a) Garcia neuroscore. n = 12 per group (ANOVA F(15,220) = 16.37P < 0.0001; *P = 0.0296, post hoc Tukey's test). (b, c) Foot fault test of the left forelimb and left hind limb. n = 12 per group (ANOVA F(15,220) = 28.88P < 0.0001; **P = 0.0079, *P = 0.0133, ***P < 0.001; post hoc Tukey's test. ANOVA F(15,220) = 29.60P < 0.0001; ***P = 0.001, *P = 0.0207, **P = 0.0038; post hoc Tukey's test). (d, e) Adhesive removal test. n = 12 per group (ANOVA F(15,220) = 28.24P < 0.0001; **P = 0.0066, **P = 0.0019, ***P < 0.001; post hoc Tukey's test. ANOVA F(15,220) = 21.80P < 0.0001; *P = 0.0174, **P = 0.002, *P = 0.0154, ***P < 0.001, post hoc Tukey's test). (f) Rotarod test. n = 12 per group (ANOVA F(15,220) = 188.2P < 0.0001; ***P < 0.001, *P = 0.0197; post hoc Tukey's test). Data are the mean ± SD, SAH+AAV-AQP4 group vs. SAH+vector group.

Fig 4: Direct injection of high affinity anti-aquaporin-4 (AQP4) monoclonal antibody into the optic nerve induced neuromyelitis optica (NMO)-like pathology. A Experimental time course. Control-immunoglobulin G (IgG) or anti-AQP4 IgG (E5415A) is directly injected into the optic nerve. B, C Immunohistochemical analysis of Intact, Control/AQP4-IgG-injected rats. Scale bar: 500 μm (low magnification) and 50 μm (high magnification). Longitudinal sections of the optic nerve at 2 days after IgG injection. Representative images of AQP4(red)/Co-immunostaining with DAPI (blue), glial fibrillary acidic protein (GFAP; red). D, E Quantification of AQP4 and GFAP positive area (%) (Intact: n = 5, Control-IgG: n = 5, AQP4-IgG: n = 5, mean ± SEM, *p < 0.05, **p < 0.01, ***p < 0.001 assessed by one-way analysis of variance (ANOVA) followed by Bonferroni tests). F, G Immunohistochemical analysis of Intact, Control/AQP4-IgG-injected rats. Scale bar: 500 μm (low magnification) and 50 μm (high magnification). Longitudinal sections of the optic nerve at 2 and 4 days after IgG injection. Representative images of ionizing calcium-binding adaptor protein-1(Iba1: green), and myeloperoxidase (MPO: red). H, I Quantification of Iba1, MPO positive area (%) (Intact: n = 5, Control-IgG: n = 5, AQP4-IgG: n = 5, mean ± SEM, **p < 0.01, ***p < 0.001 assessed by one-way analysis of variance (ANOVA) followed by Bonferroni test) J, K Quantification of Iba1, MPO positive area (%) (Control-IgG: n = 5, AQP4-IgG: n = 5, mean ± SEM, **p < 0.01, assessed by Student’s t test)

Fig 5: Differential Gene-Expression Analysis between Treatment Time Points Reveals Treatment Stage-Specific Transcriptional Signatures(A) Boxplots showing the expression level of the alveolar signature across treatment time points as well as non-cancerous AT2 cells from our cohort. ***p < 0.001.(B) Fold-change expression of NKX2-1 as quantified by RT-PCR in EGFR mutant PC9 cells after specified treatment duration (see STAR Methods), ***p < 0.001.(C) Representative IHC images of TN, RD, and PD tumor tissue sections stained for AQP4 demonstrating increased expression at the RD time point. Red arrows indicate cancer cells of interest. Scale bars correspond to 50 µm.(D) Kaplan-Meier plot of the relationship between the alveolar signature and patient OS within the TGCA dataset. Patients were stratified by signature expression quartile (Q1 = 128, Q2 = 127, Q3 = 128, Q4 = 127), where Q1 is the lowest expression and Q4 is the highest expression.(E and F) Representative IHC images of TN, RD, and PD tumor tissue sections stained for SUSD2 (E) and CTNNB1 (F) demonstrating increased expression at the RD time point. Red arrows indicate example regions of interest. Scale bars correspond to 50 µm.(G–J) Treatment response upon inhibition of ß-catenin activity in EGFR mutant PC9 cells and ALK fusion-positive H3122 cells. Relative viability is shown as percent confluency compared to DMSO control. PC9 cells were treated with XAV-939 (G) or PRI-724 (H) with or without the combination of 50nM osimertinib. H3122 were treated with XAV-939 (I) or PRI-724 (J) with or without the combination of 50 nM alectinib. p values were calculated for all end points (day 6) values compared to single agent TKI. Error bars represent mean ± standard error of the mean (SEM), n = 4 technical replicates. *p < 0.05, **p < 0.01.(K) Boxplots showing the expression levels of the kynurenine signature expression across different treatment time points. ***p < 0.001.(L) Fold-change expression of QPRT as quantified by RT-PCR in PC9 cells after treatment with osimertinib as in (B) (see STAR Methods) (AR), *p < 0.05.(M) Kaplan-Meier plot of the relationship between the kynurenine signature and patient OS within the TGCA dataset. Patients were stratified by signature expression quartile (Q1 = 128, Q2 = 127, Q3 = 128, Q4 = 127), where Q1 is the lowest expression and Q4 is the highest expression.(N) Boxplot showing the expression levels of the plasminogen activation pathway signature across different treatment time points.(O) Boxplot showing the expression levels of the SERPINE1 across different treatment time points.(P) Kaplan-Meier plot of the relationship between the plasminogen activating pathway signature and patient OS within the TGCA dataset, respectively. Patients were stratified by signature expression quartile (Q1 = 128, Q2 = 127, Q3 = 128, Q4 = 127), where Q1 is the lowest expression and Q4 is the highest expression.(Q) Kaplan-Meier plot of the relationship between SERPINE1 expression and patient OS within the TGCA dataset, respectively. Patients were stratified by signature expression quartile (Q1 = 128, Q2 = 127, Q3 = 128, Q4 = 127), where Q1 is the lowest expression and Q4 is the highest expression.(R) Boxplot showing the expression levels of the gap-junction signature across treatment time points.(S) Kaplan-Meier plots of relationships between the gap-junction signature and patient OS within the TGCA dataset. Patients were stratified by signature expression quartile (Q1 = 128, Q2 = 127, Q3 = 128, Q4 = 127), where Q1 is the lowest expression and Q4 is the highest expression.See also Figures S3, S4, and S5 and Tables S2, S4, S5, and S6.