Immunization expands B cells specific to HIV-1 V3 glycan in mice and macaques.

Broadly neutralizing monoclonal antibodies protect against infection with HIV-1 in animal models, suggesting that a vaccine that elicits these antibodies would be protective in humans. However, it has not yet been possible to induce adequate serological responses by vaccination. Here, to activate B cells that express precursors of broadly neutralizing antibodies within polyclonal repertoires, we developed an immunogen, RC1, that facilitates the recognition of the variable loop 3 (V3)-glycan patch on the envelope protein of HIV-1. RC1 conceals non-conserved immunodominant regions by the addition of glycans and/or multimerization on virus-like particles. Immunization of mice, rabbits and rhesus macaques with RC1 elicited serological responses that targeted the V3-glycan patch. Antibody cloning and cryo-electron microscopy structures of antibody-envelope complexes confirmed that immunization with RC1 expands clones of B cells that carry the anti-V3-glycan patch antibodies, which resemble precursors of human broadly neutralizing antibodies. Thus, RC1 may be a suitable priming immunogen for sequential vaccination strategies in the context of polyclonal repertoires

Reduced level of arousal and increased mortality in adult acute medical admissions: a systematic review and meta-analysis

Abstract Background Reduced level of arousal is commonly observed in medical admissions and may predict in-hospital mortality. Delirium and reduced level of arousal are closely related. We systematically reviewed and conducted a meta-analysis of studies in adult acute medical patients of the relationship between reduced level of arousal on admission and in-hospital mortality. Methods We conducted a systematic review (PROSPERO: CRD42016022048), searching MEDLINE and EMBASE. We included studies of adult patients admitted with acute medical illness with level of arousal assessed on admission and mortality rates reported. We performed meta-analysis using a random effects model. Results From 23,941 studies we included 21 with 14 included in the meta-analysis. Mean age range was 33.4 - 83.8 years. Studies considered unselected general medical admissions (8 studies, n=13,039) or specific medical conditions (13 studies, n=38,882). Methods of evaluating level of arousal varied. The prevalence of reduced level of arousal was 3.1%-76.9% (median 13.5%). Mortality rates were 1.7%-58% (median 15.9%). Reduced level of arousal was associated with higher in-hospital mortality (pooled OR 5.71; 95% CI 4.21-7.74; low quality evidence: high risk of bias, clinical heterogeneity and possible publication bias). Conclusions Reduced level of arousal on hospital admission may be a strong predictor of in-hospital mortality. Most evidence was of low quality. Reduced level of arousal is highly specific to delirium, better formal detection of hypoactive delirium and implementation of care pathways may improve outcomes. Future studies to assess the impact of interventions on in-hospital mortality should use validated assessments of both level of arousal and delirium

Quantitative and Qualitative Analysis of the Antifungal Activity of Allicin Alone and in Combination with Antifungal Drugs

The antifungal activity of allicin and its synergistic effects with the antifungal agents flucytosine and amphotericin B (AmB) were investigated in Candida albicans (C. albicans). C. albicans was treated with different conditions of compounds alone and in combination (allicin, AmB, flucytosine, allicin + AmB, allicin + flucytosine, allicin + AmB + flucytosine). After a 24-hour treatment, cells were examined by scanning electron microscopy (SEM) and atomic force microscopy (AFM) to measure morphological and biophysical properties associated with cell death. The clearing assay was conducted to confirm the effects of allicin. The viability of C. albicans treated by allicin alone or with one antifungal drug (AmB, flucytosine) in addition was more than 40% after a 24-hr treatment, but the viability of groups treated with combinations of more than two drugs was less than 32%. When the cells were treated with allicin alone or one type of drug, the morphology of the cells did not change noticeably, but when cells were treated with combinations of drugs, there were noticeable morphological changes. In particular, cells treated with allicin + AmB had significant membrane damage (burst or collapsed membranes). Classification of cells according to their cell death phase (CDP) allowed us to determine the relationship between cell viability and treatment conditions in detail. The adhesive force was decreased by the treatment in all groups compare to the control. Cells treated with AmB + allicin had a greater adhesive force than cells treated with AmB alone because of the secretion of molecules due to collapsed membranes. All cells treated with allicin or drugs were softer than the control cells. These results suggest that allicin can reduce MIC of AmB while keeping the same efficacy

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry

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

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

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

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

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

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

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

Theoretically-Efficient and Practical Parallel DBSCAN

The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for DBSCAN in Euclidean space that take $O(n\log n)$ work for two dimensions, sub-quadratic work for three or more dimensions, and can be computed approximately in linear work for any constant number of dimensions. However, existing parallel DBSCAN algorithms require quadratic work in the worst case, making them inefficient for large datasets. This paper bridges the gap between theory and practice of parallel DBSCAN by presenting new parallel algorithms for Euclidean exact DBSCAN and approximate DBSCAN that match the work bounds of their sequential counterparts, and are highly parallel (polylogarithmic depth). We present implementations of our algorithms along with optimizations that improve their practical performance. We perform a comprehensive experimental evaluation of our algorithms on a variety of datasets and parameter settings. Our experiments on a 36-core machine with hyper-threading show that we outperform existing parallel DBSCAN implementations by up to several orders of magnitude, and achieve speedups by up to 33x over the best sequential algorithms