Spatially resolved MaNGA observations of the host galaxy of superluminous supernova 2017egm

Superluminous supernovae (SLSNe) are found predominantly in dwarf galaxies, indicating that their progenitors have a low metallicity. However, the most nearby SLSN to date, SN 2017egm, occurred in the spiral galaxy NGC 3191, which has a relatively high stellar mass and correspondingly high metallicity. In this paper, we present detailed analysis of the nearby environment of SN 2017egm using MaNGA IFU data, which provides spectral data on kiloparsec scales. From the velocity map we find no evidence that SN 2017egm occurred within some intervening satellite galaxy, and at the SN position most metallicity diagnostics yield a solar and above solar metallicity (12 + log (O/H) = 8.8-9.1). Additionally we measure a small H-alpha equivalent width (EW) at the SN position of just 34 Angs, which is one of the lowest EWs measured at any SLSN or Gamma-Ray Burst position, and indicative of the progenitor star being comparatively old. We also compare the observed properties of NGC 3191 with other SLSN host galaxies. The solar-metallicity environment at the position of SN 2017egm presents a challenge to our theoretical understanding, and our spatially resolved spectral analysis provides further constraints on the progenitors of SLSNe.Comment: Accepted version in ApJ Letter. Thank you for useful comment

Fluoroquinolones are associated with delayed treatment and resistance in tuberculosis: a systematic review and meta-analysis

SummaryBackgroundCurrent guidelines for treating community-acquired pneumonia recommend the use of fluoroquinolones for high-risk patients. Previous studies have reported controversial results as to whether fluoroquinolones are associated with delayed diagnosis and treatment of pulmonary tuberculosis (TB) and the development of fluoroquinolone-resistant Mycobacterium tuberculosis. We performed a systematic review and meta-analysis to clarify these issues.MethodsThe following databases were searched through September 30, 2010: PubMed, EMBASE, CINAHL, Cochrane Library, Web of Science, BIOSIS Previews, and the ACP Journal Club. We considered studies that addressed the issues of delay in diagnosis and treatment of TB and the development of resistance.ResultsNine eligible studies (four for delays and five for resistance issues) were included in the meta-analysis from the 770 articles originally identified in the database search. The mean duration of delayed diagnosis and treatment of pulmonary TB in the fluoroquinolone prescription group was 19.03 days, significantly longer than that in the non-fluoroquinolone group (95% confidence interval (CI) 10.87 to 27.18, p<0.001). The pooled odds ratio of developing a fluoroquinolone-resistant M. tuberculosis strain was 2.70 (95% CI 1.30 to 5.60, p=0.008). No significant heterogeneity was found among studies in the meta-analysis.ConclusionsEmpirical fluoroquinolone prescriptions for pneumonia are associated with longer delays in diagnosis and treatment of pulmonary TB and a higher risk of developing fluoroquinolone-resistant M. tuberculosis

Genome-Wide Gene-Environment Interaction Analysis Using Set-Based Association Tests

The identification of gene-environment interactions (G × E) may eventually guide health-related choices and medical interventions for complex diseases. More powerful methods must be developed to identify G × E. The “adaptive combination of Bayes factors method” (ADABF) has been proposed as a powerful genome-wide polygenic approach to detect G × E. In this work, we evaluate its performance when serving as a gene-based G × E test. We compare ADABF with six tests including the “Set-Based gene-EnviRonment InterAction test” (SBERIA), “gene-environment set association test” (GESAT), etc. With extensive simulations, SBERIA and ADABF are found to be more powerful than other G × E tests. However, SBERIA suffers from a power loss when 50% SNP main effects are in the same direction with the SNP × E interaction effects while 50% are in the opposite direction. We further applied these seven G × E methods to the Taiwan Biobank data to explore gene× alcohol interactions on blood pressure levels. The ADAMTS7P1 gene at chromosome 15q25.2 was detected to interact with alcohol consumption on diastolic blood pressure (p = 9.5 × 10−7, according to the GESAT test). At this gene, the P-values provided by other six tests all reached the suggestive significance level (p &lt; 5 × 10−5). Regarding the computation time required for a genome-wide G × E analysis, SBERIA is the fastest method, followed by ADABF. Considering the validity, power performance, robustness, and computation time, ADABF is recommended for genome-wide G × E analyses

Single nucleotide polymorphisms of one-carbon metabolism and cancers of the esophagus, stomach, and liver in a Chinese population.

One-carbon metabolism (folate metabolism) is considered important in carcinogenesis because of its involvement in DNA synthesis and biological methylation reactions. We investigated the associations of single nucleotide polymorphisms (SNPs) in folate metabolic pathway and the risk of three GI cancers in a population-based case-control study in Taixing City, China, with 218 esophageal cancer cases, 206 stomach cancer cases, 204 liver cancer cases, and 415 healthy population controls. Study participants were interviewed with a standardized questionnaire, and blood samples were collected after the interviews. We genotyped SNPs of the MTHFR, MTR, MTRR, DNMT1, and ALDH2 genes, using PCR-RFLP, SNPlex, or TaqMan assays. To account for multiple comparisons and reduce the chances of false reports, we employed semi-Bayes (SB) shrinkage analysis. After shrinkage and adjusting for potential confounding factors, we found positive associations between MTHFR rs1801133 and stomach cancer (any T versus C/C, SB odds-ratio [SBOR]: 1.79, 95% posterior limits: 1.18, 2.71) and liver cancer (SBOR: 1.51, 95% posterior limits: 0.98, 2.32). There was an inverse association between DNMT1 rs2228612 and esophageal cancer (any G versus A/A, SBOR: 0.60, 95% posterior limits: 0.39, 0.94). In addition, we detected potential heterogeneity across alcohol drinking status for ORs relating MTRR rs1801394 to esophageal (posterior homogeneity P = 0.005) and stomach cancer (posterior homogeneity P = 0.004), and ORs relating MTR rs1805087 to liver cancer (posterior homogeneity P = 0.021). Among non-alcohol drinkers, the variant allele (allele G) of these two SNPs was inversely associated with the risk of these cancers; while a positive association was observed among ever-alcohol drinkers. Our results suggest that genetic polymorphisms related to one-carbon metabolism may be associated with cancers of the esophagus, stomach, and liver. Heterogeneity across alcohol consumption status of the associations between MTR/MTRR polymorphisms and these cancers indicates potential interactions between alcohol drinking and one-carbon metabolic pathway

Strong Gravitational Lensing Parameter Estimation with Vision Transformer

Quantifying the parameters and corresponding uncertainties of hundreds of strongly lensed quasar systems holds the key to resolving one of the most important scientific questions: the Hubble constant ($H_{0}$) tension. The commonly used Markov chain Monte Carlo (MCMC) method has been too time-consuming to achieve this goal, yet recent work has shown that convolution neural networks (CNNs) can be an alternative with seven orders of magnitude improvement in speed. With 31,200 simulated strongly lensed quasar images, we explore the usage of Vision Transformer (ViT) for simulated strong gravitational lensing for the first time. We show that ViT could reach competitive results compared with CNNs, and is specifically good at some lensing parameters, including the most important mass-related parameters such as the center of lens $\theta_{1}$ and $\theta_{2}$, the ellipticities $e_1$ and $e_2$, and the radial power-law slope $\gamma'$. With this promising preliminary result, we believe the ViT (or attention-based) network architecture can be an important tool for strong lensing science for the next generation of surveys. The open source of our code and data is in \url{https://github.com/kuanweih/strong_lensing_vit_resnet}.Comment: Accepted by ECCV 2022 AI for Space Worksho