Fig 1: Presence and frequency of ILC subtypes within the meninges of severe TBI patients.(A) Dura was collected from consecutive, severe TBI patients undergoing decompressive craniectomy to alleviate elevated intracranial pressure. ILCs were sorted using forward scatter (FSC)/side scatter (SSC) and identified as CD45+, lineage-negative (Lin−), CD127+ lymphoid cells. ILCs subtypes were further defined as ILC1:, CD45+Lin−CD127+CD161+NKp44+; ILC2, CD45+Lin−CD127+GATA3+CRTH2+; and ILC3, CD45+Lin−CD127+RORγt+AhR+, as shown in representative flow cytometry scatterplots. Gray shaded areas indicate isotype controls. To demonstrate functionality, ILCs were further stimulated with cytokine cocktails, and production of signature cytokines was assessed (ILC1, IFN-γ; ILC2, IL-5/IL-13; ILC3, IL-17). (B and C) Frequency of ILC subtypes from individual patients, expressed as total cell number (B) and % leukocytes (C) (n = 5). Scatterplots depict mean ± SD. (D) Computed tomography scan of a TBI patient before (Pre-) and after (Post-) decompressive craniectomy surgery. The dura was collected during surgery at the time of bone flap removal.
Fig 2: Decreased expression of NK cell-activating receptors on NK cells in JORRP patients. (A) Percentage analysis of NKp30, NKp46, NKG2D, and NKp44 expression on NK cells as determined by flow cytometry of HCs (n = 35) and JORRP patients (n = 35) or different subgroups of JORRP patients. Agg, aggressive (n = 11); Non-agg, non-aggressive (n = 19); 6, HPV6 (n = 14); 11, HPV11 (n = 16); 6&11, HPV6&HPV11 (n = 3). (B) Correlation of CD107a expression on NK cells with NKp30, NKp46, NKG2D, and NKp44 expression on NK cells. Spearman’s correlation coefficients are shown. (C) Correlation of NKp30, NKp46, NKG2D, and NKp44 expression on NK cells with surgical times. Spearman’s correlation coefficients are shown. (D) Correlation of NKp30, NKp46, NKG2D, and NKp44 expression on NK cells with interval time of surgical reoccurrence. Spearman’s correlation coefficients are shown. Data are presented as median with interquartile range. Each dot represents a single patient. ns, not significant; *P < 0.05; **P < 0.01; ***P < 0.001.
Fig 3: Increased presence of ILC1 and ILC3 within human CSF after TBI.(A) CSF was collected from consecutive, adult nontraumatic control (normal pressure hydrocephalus; NPH) or severe TBI patients. Human ILCs were sorted using forward scatter (FSC)/side scatter (SSC) and identified as CD45+, lineage-negative (Lin-), CD127+ lymphoid cells. Selected populations were analyzed for ILC subtype as follows: ILC1, Lin-CD127+CD161+NKp44+; ILC2, Lin-CD127+GATA3+CRTH2+; and ILC3, Lin-CD127+AhR+ROR?t+. ILC functionality was further assessed by cytokine production (ILC1, IFN-?; ILC2, IL-5/IL-13; and ILC3, IL-17) after cytokine stimulation, as shown. Gray shaded areas indicate isotype controls. (B and C) Quantified data reveal low basal expression of ILC subtypes, with large increases in all ILC classes after TBI. Scatterplots, which are expressed as mean ± SD, depict ILC subtypes as total cell number (B) and % leukocytes (C). Data from individual patients (n = 6 NPH patients, n = 6 severe TBI patients) were compared within each ILC subtype using a 2-tailed Student’s t test (*P < 0.05, **P < 0.01, ***P < 0.001 versus sham).
Fig 4: Higher Transforming Growth Factor (TGF)-β level in plasma and papillomatosis of JORRP patients and associated with decreased NK cell cytotoxicity. (A) Measurement of multiple cytokine concentrations in plasma of HCs and JORRP patients by CBA (IL-1α, IL-2, IL-10, IL-6, IL-12p70, IL-15, IL-33, IFN-γ) and TGF-β1 by ELISA. (B) Immunohistochemistry of TGF-β1 in tumor sections (right) and paired adjacent nontumor sections (n = 4). Bar: 20 μm. (C) Concentration analysis of TGF-β1 in different subgroups of JORRP patients. Agg, aggressive (n = 11); Non-agg, non-aggressive (n = 19); 6, HPV6 (n = 7); 11, HPV11 (n = 16); 6&11, HPV6&HPV11 (n = 3). (D) Correlation of plasma TGF-β1 with age of first occurrence, interval time, the percentage of CD56bright and CD56dim NK, CD107a, NKp30, NKp46, NKG2D, and NKp44 expression on NK cells. Spearman’s correlation coefficients are shown. Data are presented as mean ± SD. Each dot represents a single patient. *P < 0.05.
Fig 5: Innate lymphoid cell distribution in colonic biopsies of active IBD patients. Gating strategy for identification of innate lymphoid cells (ILCs) in intestinal biopsies. Gating was based on FMO and tonsil staining. Representative data in (A) are shown as contour plots (5%) with outliers (A). Innate lymphoid cells were defined as living CD45+ lineage- CD161+ CD127+ cells. Among the ILCs, ILC2 was identified by the expression of CRTH2+ (CD294); NCR- ILC3 was defined as CRTH2- CD117+ NKp44- cells; NCR+ ILC3 was defined as CRTH2- CD117+ NKp44+ cells and ILC1 as CRTH2- CD117- NKp44- cells. Contribution of the ILC population to the total CD45 population isolated from the biopsies (B). Comparison of ILC1 (C), NCR+ ILC3 (D), NCR- ILC3 (E) and ILC2 (F) (each as proportion of total ILC and as percentage of total CD45+ leukocyte population) between healthy controls (n = 17) (left) and IBD patients (n = 28, CD = 15, UC = 13) (right). Mann–Whitney U testing; *p < 0.05, **p = 0.01, ***p = 0.001, and ****p < 0.0001.
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