Comparative Metabolomics Reveals Endogenous Ligands of DAF-12, a Nuclear Hormone Receptor, Regulating C. elegans Development and Lifespan

SummarySmall-molecule ligands of nuclear hormone receptors (NHRs) govern the transcriptional regulation of metazoan development, cell differentiation, and metabolism. However, the physiological ligands of many NHRs remain poorly characterized, primarily due to lack of robust analytical techniques. Using comparative metabolomics, we identified endogenous steroids that act as ligands of the C. elegans NHR, DAF-12, a vitamin D and liver X receptor homolog regulating larval development, fat metabolism, and lifespan. The identified molecules feature unexpected chemical modifications and include only one of two DAF-12 ligands reported earlier, necessitating a revision of previously proposed ligand biosynthetic pathways. We further show that ligand profiles are regulated by a complex enzymatic network, including the Rieske oxygenase DAF-36, the short-chain dehydrogenase DHS-16, and the hydroxysteroid dehydrogenase HSD-1. Our results demonstrate the advantages of comparative metabolomics over traditional candidate-based approaches and provide a blueprint for the identification of ligands for other C. elegans and mammalian NHRs

Photometric Supernova Cosmology with BEAMS and SDSS-II

Supernova cosmology without spectroscopic confirmation is an exciting new frontier which we address here with the Bayesian Estimation Applied to Multiple Species (BEAMS) algorithm and the full three years of data from the Sloan Digital Sky Survey II Supernova Survey (SDSS-II SN). BEAMS is a Bayesian framework for using data from multiple species in statistical inference when one has the probability that each data point belongs to a given species, corresponding in this context to different types of supernovae with their probabilities derived from their multi-band lightcurves. We run the BEAMS algorithm on both Gaussian and more realistic SNANA simulations with of order 10^4 supernovae, testing the algorithm against various pitfalls one might expect in the new and somewhat uncharted territory of photometric supernova cosmology. We compare the performance of BEAMS to that of both mock spectroscopic surveys and photometric samples which have been cut using typical selection criteria. The latter typically are either biased due to contamination or have significantly larger contours in the cosmological parameters due to small data-sets. We then apply BEAMS to the 792 SDSS-II photometric supernovae with host spectroscopic redshifts. In this case, BEAMS reduces the area of the (\Omega_m,\Omega_\Lambda) contours by a factor of three relative to the case where only spectroscopically confirmed data are used (297 supernovae). In the case of flatness, the constraints obtained on the matter density applying BEAMS to the photometric SDSS-II data are \Omega_m(BEAMS)=0.194\pm0.07. This illustrates the potential power of BEAMS for future large photometric supernova surveys such as LSST.Comment: 25 pages, 15 figures, submitted to Ap

Association of Blood Biomarkers With Acute Sport-Related Concussion in Collegiate Athletes: Findings From the NCAA and Department of Defense CARE Consortium

Importance: There is potential scientific and clinical value in validation of objective biomarkers for sport-related concussion (SRC). Objective: To investigate the association of acute-phase blood biomarker levels with SRC in collegiate athletes. Design, Setting, and Participants: This multicenter, prospective, case-control study was conducted by the National Collegiate Athletic Association (NCAA) and the US Department of Defense Concussion Assessment, Research, and Education (CARE) Consortium from February 20, 2015, to May 31, 2018, at 6 CARE Advanced Research Core sites. A total of 504 collegiate athletes with concussion, contact sport control athletes, and non-contact sport control athletes completed clinical testing and blood collection at preseason baseline, the acute postinjury period, 24 to 48 hours after injury, the point of reporting being asymptomatic, and 7 days after return to play. Data analysis was conducted from March 1 to November 30, 2019. Main Outcomes and Measures: Glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), neurofilament light chain, and tau were quantified using the Quanterix Simoa multiplex assay. Clinical outcome measures included the Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom evaluation, Standardized Assessment of Concussion, Balance Error Scoring System, and Brief Symptom Inventory 18. Results: A total of 264 athletes with concussion (mean [SD] age, 19.08 [1.24] years; 211 [79.9%] male), 138 contact sport controls (mean [SD] age, 19.03 [1.27] years; 107 [77.5%] male), and 102 non-contact sport controls (mean [SD] age, 19.39 [1.25] years; 82 [80.4%] male) were included in the study. Athletes with concussion had significant elevation in GFAP (mean difference, 0.430 pg/mL; 95% CI, 0.339-0.521 pg/mL; P < .001), UCH-L1 (mean difference, 0.449 pg/mL; 95% CI, 0.167-0.732 pg/mL; P < .001), and tau levels (mean difference, 0.221 pg/mL; 95% CI, 0.046-0.396 pg/mL; P = .004) at the acute postinjury time point compared with preseason baseline. Longitudinally, a significant interaction (group × visit) was found for GFAP (F7,1507.36 = 16.18, P < .001), UCH-L1 (F7,1153.09 = 5.71, P < .001), and tau (F7,1480.55 = 6.81, P < .001); the interaction for neurofilament light chain was not significant (F7,1506.90 = 1.33, P = .23). The area under the curve for the combination of GFAP and UCH-L1 in differentiating athletes with concussion from contact sport controls at the acute postinjury period was 0.71 (95% CI, 0.64-0.78; P < .001); the acute postinjury area under the curve for all 4 biomarkers combined was 0.72 (95% CI, 0.65-0.79; P < .001). Beyond SCAT-3 symptom score, GFAP at the acute postinjury time point was associated with the classification of athletes with concussion from contact controls (β = 12.298; 95% CI, 2.776-54.481; P = .001) and non-contact sport controls (β = 5.438; 95% CI, 1.676-17.645; P = .005). Athletes with concussion with loss of consciousness or posttraumatic amnesia had significantly higher levels of GFAP than athletes with concussion with neither loss of consciousness nor posttraumatic amnesia at the acute postinjury time point (mean difference, 0.583 pg/mL; 95% CI, 0.369-0.797 pg/mL; P < .001). Conclusions and Relevance: The results suggest that blood biomarkers can be used as research tools to inform the underlying pathophysiological mechanism of concussion and provide additional support for future studies to optimize and validate biomarkers for potential clinical use in SRC

Results from the Supernova Photometric Classification Challenge

We report results from the Supernova Photometric Classification Challenge (SNPCC), a publicly released mix of simulated supernovae (SNe), with types (Ia, Ibc, and II) selected in proportion to their expected rate. The simulation was realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point-spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). A spectroscopically confirmed subset was provided for training. We challenged scientists to run their classification algorithms and report a type and photo-z for each SN. Participants from 10 groups contributed 13 entries for the sample that included a host-galaxy photo-z for each SN, and 9 entries for the sample that had no redshift information. Several different classification strategies resulted in similar performance, and for all entries the performance was significantly better for the training subset than for the unconfirmed sample. For the spectroscopically unconfirmed subset, the entry with the highest average figure of merit for classifying SNe~Ia has an efficiency of 0.96 and an SN~Ia purity of 0.79. As a public resource for the future development of photometric SN classification and photo-z estimators, we have released updated simulations with improvements based on our experience from the SNPCC, added samples corresponding to the Large Synoptic Survey Telescope (LSST) and the SDSS, and provided the answer keys so that developers can evaluate their own analysis.Comment: accepted by PAS

The TIGR Rice Genome Annotation Resource: improvements and new features

In The Institute for Genomic Research Rice Genome Annotation project (), we have continued to update the rice genome sequence with new data and improve the quality of the annotation. In our current release of annotation (Release 4.0; January 12, 2006), we have identified 42 653 non-transposable element-related genes encoding 49 472 gene models as a result of the detection of alternative splicing. We have refined our identification methods for transposable element-related genes resulting in 13 237 genes that are related to transposable elements. Through incorporation of multiple transcript and proteomic expression data sets, we have been able to annotate 24 799 genes (31 739 gene models), representing ∼50% of the total gene models, as expressed in the rice genome. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 59 tracks. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads

Delayed diagnosis and recovery of fulminant immune checkpoint inhibitor-associated myocarditis on VA-ECMO support

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Measurement of the relative yields of psi(2S) to psi(1S) mesons produced at forward and backward rapidity in p plus p, p plus Al, p + Au, and He-3+Au collisions at root S-NN=200 GeV

The PHENIX Collaboration has measured the ratio of the yields of psi(2S) to psi(1S) mesons produced in p + p, p + Al, p + Au, and He-3+Au collisions at root S-NN = 200 GeV over the forward and backward rapidity intervals 1.2 \u3c | y | \u3c 2.2. We find that the ratio in p + p collisions is consistent with measurements at other collision energies. In collisions with nuclei, we find that in the forward (p-going or He-3-going) direction, the relative yield of psi(2S) mesons to psi(1S) mesons is consistent with the value measured in p + p collisions. However, in the backward (nucleus-going) direction, the psi(2S) meson is preferentially suppressed by a factor of similar to 2. This suppression is attributed in some models to the breakup of the weakly bound psi(2S) meson through final-state interactions with comoving particles, which have a higher density in the nucleus-going direction. These breakup effects may compete with color screening in a deconfined quark-gluon plasma to produce sequential suppression of excited quarkonia states

DGIdb 2.0: Mining clinically relevant drug-gene interactions

The Drug–Gene Interaction Database (DGIdb, www. dgidb.org) is a web resource that consolidates dis-parate data sources describing drug–gene interac-tions and gene druggability. It provides an intuitive graphical user interface and a documented applica-tion programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined in-formation of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specif-ically, nine new sources of drug–gene interactions have been added, including seven resources specifi-cally focused on interactions linked to clinical trials. These additions have more than doubled the over-all count of drug–gene interactions. The total num-ber of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Fi-nally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search function-ality. With these updates, DGIdb represents a com-prehensive and user friendly tool for mining the druggable genome for precision medicine hypothe-sis generation