(S)-[5-Methyl-3-(3-methyl­thio­phen-2-yl)-4,5-dihydro­isoxazol-5-yl]methanol

In the title compound, C10H13NO2S, the thio­phene and isoxazoline rings are almost coplanar, the dihedral angle between their least-squares planes being 2.08 (1)°. The O—H atoms of the methyl hy­droxy group and the N atom of the isoxazole ring are orientated in the same direction to allow for the formation of inter­molecular O—H⋯N hydrogen bonds that lead to a supra­molecular chain along the a axis

Concomitant renal insufficiency and diabetes mellitus as prognostic factors for acute myocardial infarction

<p>Abstract</p> <p>Background</p> <p>Diabetes mellitus and renal dysfunction are prognostic factors after acute myocardial infarction (AMI). However, few studies have assessed the effects of renal insufficiency in association with diabetes in the context of AMI. Here, we investigated the clinical outcomes according to the concomitance of renal dysfunction and diabetes mellitus in patients with AMI.</p> <p>Methods</p> <p>From November 2005 to August 2008, 9905 patients (63 ± 13 years; 70% men) with AMI were enrolled in a nationwide prospective Korea Acute Myocardial Infarction Registry (KAMIR) and were categorized into 4 groups: Group I (n = 5700) had neither diabetes nor renal insufficiency (glomerular filtration rate [GFR] ≥ 60 ml/min/1.73 m²), Group II (n = 1730) had diabetes but no renal insufficiency, Group III (n = 1431) had no diabetes but renal insufficiency, and Group IV (n = 1044) had both diabetes and renal insufficiency. The primary endpoints were major adverse cardiac events (MACE), including a composite of all cause-of-death, myocardial infarction, target lesion revascularization, and coronary artery bypass graft after 1-year clinical follow-up.</p> <p>Results</p> <p>Primary endpoints occurred in 1804 (18.2%) patients. There were significant differences in composite MACE among the 4 groups (Group I, 12.5%; Group II, 15.7%; Group III, 30.5%; Group IV, 36.5%; <it>p </it>< 0.001). In a Cox proportional hazards model, after adjusting for multiple covariates, the 1-year mortality increased stepwise from Group III to IV as compared with Group I (hazard ratio [HR], 1.96; 95% confidence interval [CI], 1.34-2.86; <it>p </it>= 0.001; and HR, 2.42; 95% CI, 1.62-3.62; <it>p </it>< 0.001, respectively). However, Kaplan-Meier analysis showed no significant difference in probability of death at 1 year between Group III and IV (p = 0.288).</p> <p>Conclusions</p> <p>Renal insufficiency, especially in association with diabetes, is associated with the occurrence of composite MACE and indicates poor prognosis in patients with AMI. Categorization of patients with diabetes and/or renal insufficiency provides valuable information for early-risk stratification of AMI patients.</p

Group-regularized individual prediction: theory and application to pain

Multivariate pattern analysis (MVPA) has become an important tool for identifying brain representations of psychological processes and clinical outcomes using fMRI and related methods. Such methods can be used to predict or ‘decode’ psychological states in individual subjects. Single-subject MVPA approaches, however, are limited by the amount and quality of individual-subject data. In spite of higher spatial resolution, predictive accuracy from single-subject data often does not exceed what can be accomplished using coarser, group-level maps, because single-subject patterns are trained on limited amounts of often-noisy data. Here, we present a method that combines population-level priors, in the form of biomarker patterns developed on prior samples, with single-subject MVPA maps to improve single-subject prediction. Theoretical results and simulations motivate a weighting based on the relative variances of biomarker-based prediction—based on population-level predictive maps from prior groups—and individual-subject, cross-validated prediction. Empirical results predicting pain using brain activity on a trial-by-trial basis (single-trial prediction) across 6 studies (N = 180 participants) confirm the theoretical predictions. Regularization based on a population-level biomarker—in this case, the Neurologic Pain Signature (NPS)—improved single-subject prediction accuracy compared with idiographic maps based on the individuals' data alone. The regularization scheme that we propose, which we term group-regularized individual prediction (GRIP), can be applied broadly to within-person MVPA-based prediction. We also show how GRIP can be used to evaluate data quality and provide benchmarks for the appropriateness of population-level maps like the NPS for a given individual or study

Is there any vindication for low dose nonselective β-blocker medication in patients with liver cirrhosis?

Background/AimsNonselective β-blockers (NSBBs), such as propranolol, reportedly exert a pleiotropic effect in liver cirrhosis. A previous report suggested that survival was higher in patients receiving adjusted doses of NSBBs than in ligation patients. This study investigated whether low-dose NSBB medication has beneficial effects in patients with liver cirrhosis, especially in terms of overall survival.MethodsWe retrospectively studied 273 cirrhotic patients (199 males; age 53.6±10.2 years, mean±SD) who visited our institution between March 2003 and December 2007; follow-up data were collected until June 2011. Among them, 138 patients were given a low-dose NSBB (BB group: propranolol, 20-60 mg/day), and the remaining 135 patients were not given an NSBB (NBB group). Both groups were stratified randomly according to Child-Turcotte-Pugh (CTP) classification and age.ResultsThe causes of liver cirrhosis were alcohol (n=109, 39.9%), hepatitis B virus (n=125, 45.8%), hepatitis C virus (n=20, 7.3%), and cryptogenic (n=19, 7.0%). The CTP classes were distributed as follows: A, n=116, 42.5%; B, n=126, 46.2%; and C, n=31, 11.4%. Neither the overall survival (P=0.133) nor the hepatocellular carcinoma (HCC)-free survival (P=0.910) differed significantly between the BB and NBB groups [probability of overall survival at 4 years: 75.1% (95% CI=67.7-82.5%) and 81.2% (95% CI=74.4-88.0%), respectively; P=0.236]. In addition, the delta CTP score did not differ significantly between the two groups.ConclusionsUse of low-dose NSBB medication in patients with liver cirrhosis is not indicated in terms of overall and HCC-free survival

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA&apos;s TEMPO and ESA&apos;s Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts