Atypical chemokine receptor 4 shapes activated B cell fate

Activated B cells can initially differentiate into three functionally distinct fates-early plasmablasts (PBs), germinal center (GC) B cells, or early memory B cells-by mechanisms that remain poorly understood. Here, we identify atypical chemokine receptor 4 (ACKR4), a decoy receptor that binds and degrades CCR7 ligands CCL19/CCL21, as a regulator of early activated B cell differentiation. By restricting initial access to splenic interfollicular zones (IFZs), ACKR4 limits the early proliferation of activated B cells, reducing the numbers available for subsequent differentiation. Consequently, ACKR4 deficiency enhanced early PB and GC B cell responses in a CCL19/CCL21-dependent and B cell-intrinsic manner. Conversely, aberrant localization of ACKR4-deficient activated B cells to the IFZ was associated with their preferential commitment to the early PB linage. Our results reveal a regulatory mechanism of B cell trafficking via an atypical chemokine receptor that shapes activated B cell fate

Measuring The Evolutionary Rate Of Cooling Of ZZ Ceti

We have finally measured the evolutionary rate of cooling of the pulsating hydrogen atmosphere (DA) white dwarf ZZ Ceti (Ross 548), as reflected by the drift rate of the 213.13260694 s period. Using 41 yr of time-series photometry from 1970 November to 2012 January, we determine the rate of change of this period with time to be dP/dt = (5.2 +/- 1.4) x 10(-15) s s(-1) employing the O - C method and (5.45 +/- 0.79) x 10(-15) s s(-1) using a direct nonlinear least squares fit to the entire lightcurve. We adopt the dP/dt obtained from the nonlinear least squares program as our final determination, but augment the corresponding uncertainty to a more realistic value, ultimately arriving at the measurement of dP/dt = (5.5 +/- 1.0) x 10(-15) s s(-1). After correcting for proper motion, the evolutionary rate of cooling of ZZ Ceti is computed to be (3.3 +/- 1.1) x 10(-15) s s(-1). This value is consistent within uncertainties with the measurement of (4.19 +/- 0.73) x 10(-15) s s(-1) for another similar pulsating DA white dwarf, G 117-B15A. Measuring the cooling rate of ZZ Ceti helps us refine our stellar structure and evolutionary models, as cooling depends mainly on the core composition and stellar mass. Calibrating white dwarf cooling curves with this measurement will reduce the theoretical uncertainties involved in white dwarf cosmochronometry. Should the 213.13 s period be trapped in the hydrogen envelope, then our determination of its drift rate compared to the expected evolutionary rate suggests an additional source of stellar cooling. Attributing the excess cooling to the emission of axions imposes a constraint on the mass of the hypothetical axion particle.NSF AST-1008734, AST-0909107Norman Hackerman Advanced Research Program 003658-0252-2009Astronom

Measuring The Evolutionary Rate Of Cooling Of ZZ Ceti

We have finally measured the evolutionary rate of cooling of the pulsating hydrogen atmosphere (DA) white dwarf ZZ Ceti (Ross 548), as reflected by the drift rate of the 213.13260694 s period. Using 41 yr of time-series photometry from 1970 November to 2012 January, we determine the rate of change of this period with time to be dP/dt = (5.2 +/- 1.4) x 10(-15) s s(-1) employing the O - C method and (5.45 +/- 0.79) x 10(-15) s s(-1) using a direct nonlinear least squares fit to the entire lightcurve. We adopt the dP/dt obtained from the nonlinear least squares program as our final determination, but augment the corresponding uncertainty to a more realistic value, ultimately arriving at the measurement of dP/dt = (5.5 +/- 1.0) x 10(-15) s s(-1). After correcting for proper motion, the evolutionary rate of cooling of ZZ Ceti is computed to be (3.3 +/- 1.1) x 10(-15) s s(-1). This value is consistent within uncertainties with the measurement of (4.19 +/- 0.73) x 10(-15) s s(-1) for another similar pulsating DA white dwarf, G 117-B15A. Measuring the cooling rate of ZZ Ceti helps us refine our stellar structure and evolutionary models, as cooling depends mainly on the core composition and stellar mass. Calibrating white dwarf cooling curves with this measurement will reduce the theoretical uncertainties involved in white dwarf cosmochronometry. Should the 213.13 s period be trapped in the hydrogen envelope, then our determination of its drift rate compared to the expected evolutionary rate suggests an additional source of stellar cooling. Attributing the excess cooling to the emission of axions imposes a constraint on the mass of the hypothetical axion particle.NSF AST-1008734, AST-0909107Norman Hackerman Advanced Research Program 003658-0252-2009Astronom

Metabolic syndrome components and their response to lifestyle and metformin interventions are associated with differences in diabetes risk in persons with impaired glucose tolerance

AIMS: To determine the association of metabolic syndrome (MetS) and its components with diabetes risk in participants with impaired glucose tolerance (IGT), and whether intervention-related changes in MetS lead to differences in diabetes incidence. METHODS: We used the National Cholesterol Education Program/Adult Treatment Panel III (NCEP/ATP III) revised MetS definition at baseline and intervention-related changes of its components to predict incident diabetes using Cox models in 3234 Diabetes Prevention Program (DPP) participants with IGT over an average follow-up of 3.2 years. RESULTS: In an intention-to-treat analysis, the demographic-adjusted hazard ratios (95% confidence interval) for diabetes in those with MetS (vs. no MetS) at baseline were 1.7 (1.3-2.3), 1.7 (1.2-2.3) and 2.0 (1.3-3.0) for placebo, metformin and lifestyle groups, respectively. Higher levels of fasting plasma glucose and triglycerides at baseline were independently associated with increased risk of diabetes. Greater waist circumference (WC) was associated with higher risk in placebo and lifestyle groups, but not in the metformin group. In a multivariate model, favourable changes in WC (placebo and lifestyle) and high-density lipoprotein cholesterol (placebo and metformin) contributed to reduced diabetes risk. CONCLUSIONS: MetS and some of its components are associated with increased diabetes incidence in persons with IGT in a manner that differed according to DPP intervention. After hyperglycaemia, the most predictive factors for diabetes were baseline hypertriglyceridaemia and both baseline and lifestyle-associated changes in WC. Targeting these cardiometabolic risk factors may help to assess the benefits of interventions that reduce diabetes incidence

Questioning the rise of gelatinous zooplankton in the World's oceans

During the past several decades, high numbers of gelatinous zooplankton species have been reported in many estuarine and coastal ecosystems. Coupled with media-driven public perception, a paradigm has evolved in which the global ocean ecosystems are thought to be heading toward being dominated by “nuisance” jellyfish. We question this current paradigm by presenting a broad overview of gelatinous zooplankton in a historicalcontext to develop the hypothesis that population changes reflect the human-mediated alteration of global ocean ecosystems. To this end, we synthesize information related to the evolutionary context of contemporary gelatinous zooplankton blooms, the human frame of reference forchanges in gelatinous zooplankton populations, and whether sufficient data are available to have established the paradigm. We conclude that the current paradigm in which it is believed that there has been a global increase in gelatinous zooplankton is unsubstantiated, and we develop a strategy for addressing the critical questions about long-term, human-related changes in the sea as they relate to gelatinous zooplankton blooms

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

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

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