2,051 research outputs found

    Amyloid proteotoxicity initiates an inflammatory response blocked by cannabinoids.

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    The beta amyloid (Aβ) and other aggregating proteins in the brain increase with age and are frequently found within neurons. The mechanistic relationship between intracellular amyloid, aging and neurodegeneration is not, however, well understood. We use a proteotoxicity model based upon the inducible expression of Aβ in a human central nervous system nerve cell line to characterize a distinct form of nerve cell death caused by intracellular Aβ. It is shown that intracellular Aβ initiates a toxic inflammatory response leading to the cell's demise. Aβ induces the expression of multiple proinflammatory genes and an increase in both arachidonic acid and eicosanoids, including prostaglandins that are neuroprotective and leukotrienes that potentiate death. Cannabinoids such as tetrahydrocannabinol stimulate the removal of intraneuronal Aβ, block the inflammatory response, and are protective. Altogether these data show that there is a complex and likely autocatalytic inflammatory response within nerve cells caused by the accumulation of intracellular Aβ, and that this early form of proteotoxicity can be blocked by the activation of cannabinoid receptors

    High fat diet causes depletion of intestinal eosinophils associated with intestinal permeability.

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    The development of intestinal permeability and the penetration of microbial products are key factors associated with the onset of metabolic disease. However, the mechanisms underlying this remain unclear. Here we show that, unlike liver or adipose tissue, high fat diet (HFD)/obesity in mice does not cause monocyte/macrophage infiltration into the intestine or pro-inflammatory changes in gene expression. Rather HFD causes depletion of intestinal eosinophils associated with the onset of intestinal permeability. Intestinal eosinophil numbers were restored by returning HFD fed mice to normal chow and were unchanged in leptin-deficient (Ob/Ob) mice, indicating that eosinophil depletion is caused specifically by a high fat diet and not obesity per se. Analysis of different aspects of intestinal permeability in HFD fed and Ob/Ob mice shows an association between eosinophil depletion and ileal paracelullar permeability, as well as leakage of albumin into the feces, but not overall permeability to FITC dextran. These findings provide the first evidence that a high fat diet causes intestinal eosinophil depletion, rather than inflammation, which may contribute to defective barrier integrity and the onset of metabolic disease

    NCoR Repression of LXRs Restricts Macrophage Biosynthesis of Insulin-Sensitizing Omega 3 Fatty Acids

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    SummaryMacrophage-mediated inflammation is a major contributor to obesity-associated insulin resistance. The corepressor NCoR interacts with inflammatory pathway genes in macrophages, suggesting that its removal would result in increased activity of inflammatory responses. Surprisingly, we find that macrophage-specific deletion of NCoR instead results in an anti-inflammatory phenotype along with robust systemic insulin sensitization in obese mice. We present evidence that derepression of LXRs contributes to this paradoxical anti-inflammatory phenotype by causing increased expression of genes that direct biosynthesis of palmitoleic acid and ω3 fatty acids. Remarkably, the increased ω3 fatty acid levels primarily inhibit NF-κB-dependent inflammatory responses by uncoupling NF-κB binding and enhancer/promoter histone acetylation from subsequent steps required for proinflammatory gene activation. This provides a mechanism for the in vivo anti-inflammatory insulin-sensitive phenotype observed in mice with macrophage-specific deletion of NCoR. Therapeutic methods to harness this mechanism could lead to a new approach to insulin-sensitizing therapies

    Probing the earliest phases in the formation of massive galaxies with simulated HST+JWST imaging data from Illustris

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    We use the Illustris-1 simulation to explore the capabilities of the Hubble\textit{Hubble} and James Webb Space Telescope\textit{James Webb Space Telescope} data to analyze the stellar populations in high-redshift galaxies, taking advantage of the combined depth, spatial resolution, and wavelength coverage. For that purpose, we use simulated broad-band ACS, WFC3 and NIRCam data and 2-dimensional stellar population synthesis (2D-SPS) to derive the integrated star formation history (SFH) of massive (M>1010_{\ast}>10^{10}\,M_{\odot}) simulated galaxies at 11011110^{11}\,M_{\odot} galaxy. In particular, we explore the potential of HST and JWST datasets reaching a depth similar to those of the CANDELS and ongoing CEERS observations, respectively, and concentrate on determining the capabilities of this dataset for characterizing the first episodes in the SFH of local M>1011_{\ast}>10^{11}\,M_{\odot} galaxies by studying their progenitors at z>1z>1. The 2D-SPS method presented in this paper has been calibrated to robustly recover the cosmic times when the first star formation episodes occurred in massive galaxies, i.e., the first stages in their integrated SFHs. In particular, we discuss the times when the first 1% to 50% of their total stellar mass formed in the simulation. We demonstrate that we can recover these ages with typical median systematic offset of less than 5% and scatter around 20%-30%. According to our measurements on Illustris data, we are able to recover that local M>1011_{\ast}>10^{11}\,M_{\odot} galaxies would have started their formation by z=16z=16, forming the first 5% of their stellar mass present at z1z \sim 1 by z=4.5z=4.5, 10% by z=3.7z=3.7, and 25% by z=2.7z=2.7.Comment: 28 pages, 13 figures, 4 tables. ApJ in press. Summary of changes from original submission: the major change is that we now include in Sec. 6 the comparison of the results obtained for our sample of massive 1 < z < 4 progenitors with those obtained by considering all massive galaxies at 1 < z < 4 in the simulated images. Several figures and sections have been update

    Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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    This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

    Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

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    Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment
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