The Spatially Resolved Properties of the GW170817 Host Galaxy

GW170817 is the unique gravitational-wave (GW) event that is associated to the electromagnetic (EM) counterpart GRB 170817A. NGC 4993 is identified as the host galaxy of GW170817/GRB 170817A. In this paper, we particularly focus on the spatially resolved properties of NGC 4993. We present the photometric results from the comprehensive data analysis of the high spatial-resolution images in the different optical bands. The morphological analysis reveals that NGC 4993 is a typical early-type galaxy without significant remnants of major galaxy merger. The spatially resolved stellar population properties of NGC 4993 suggest that the galaxy center has passive evolution with the outskirt formed by gas accretion. We derive the merging rate of the compact object per galaxy by a co-evolution scenario of supermassive black hole and its host galaxy. If the galaxy formation is at redshift 1.0, the merging rate per galaxy is $3.2\times 10^{-4}$ to $7.7\times 10^{-5}$ within the merging decay time from 1.0 to 5.0 Gyr. The results provide the vital information for the ongoing GW EM counterpart detections. The HST data analysis presented in this paper can be also applied for the Chinese Space Station Telescope (CSST) research in the future.Comment: RAA accepte

Ghost field realizations of the spinor W2,sW_{2,s} strings based on the linear W(1,2,s) algebras

It has been shown that certain W algebras can be linearized by the inclusion of a spin-1 current. This Provides a way of obtaining new realizations of the W algebras. In this paper, we investigate the new ghost field realizations of the W(2,s)(s=3,4) algebras, making use of the fact that these two algebras can be linearized. We then construct the nilpotent BRST charges of the spinor non-critical W(2,s) strings with these new realizations.Comment: 10 pages, no figure

Perivascular spaces visible on magnetic resonance imaging predict subsequent delirium in older patients

BackgroundIt remains unknown whether perivascular spaces (PVS) are associated with delirium in older hospitalized patients. We aimed to determine the association between magnetic resonance imaging (MRI)-visible PVS and the risk of delirium in a cohort of older patients.MethodsWe consecutively recruited older patients (≥70 years) admitted to the Geriatric Department of West China Hospital between March 2016 and July 2017, and their imaging data within one year before admission were reviewed retrospectively. PVS was rated on axial T2-weighted images in the basal ganglia (BG) and centrum semiovale (CS) using the validated semiquantitative 4-point ordinal scale. Delirium was screened within 24 h of admission and three times daily thereafter, using the confusion assessment method. Binary logistic regression analyses were performed to investigate the associations between PVS and delirium.ResultsAmong 114 included patients (mean age 84.3 years, 72.8% male), delirium occurred in 20 (17.5%). In patients with MRI examined within 6 months before admission, CS-PVS was found to be associated with delirium (odds ratio [OR] 3.88, 95% confidence interval [CI] 1.07-14.06, unadjusted; and OR 4.24, 95% CI 1.11-16.28, adjusted for age). The associations were enhanced and remained significant even after full adjustment of covariates (OR 7.16, 95% CI 1.16-44.32, adjusted for age, cognitive impairment, smoking, and Charlson Comorbidity Index). Similarly, the relationships between high CS-PVS and delirium were also strengthened after sequentially adjusting all variables of interest, with OR 4.17 (95% CI 1.04-16.73) in unadjusted model and OR 7.95 (95% CI 1.14-55.28) in fully-adjusted model. Adding CS-PVS to the established risk factors improved the risk reclassification for delirium (continuous net reclassification index 62.1%, P = 0.04; and integrated discrimination improvement 12.5%, P = 0.01).ConclusionsCS-PVS on MRI acquired 6 months earlier predicts subsequent delirium in older patients and may have clinical utility in delirium risk stratification to enable proactive interventions

Biomass fuel usage for cooking and frailty among older adults in China: a population-based cohort study

BackgroundAlthough outdoor air pollution is reported to have a negative effect on frailty, evidence involving household air pollution is sparse.MethodsA cohort study on older participants aged ≥65 years from the Chinese Longitudinal Healthy Longevity Survey was conducted between 2011/2012 and 2014. Household cooking fuel types were determined by self-reported questionaries, and were dichotomized into clean or biomass fuels. The frailty status was evaluated via a 46-item frailty index (FI) and the FRAIL scale, respectively. Frailty was identified if FI >0.21 or FRAIL score ≥3. Cox proportional hazards models were employed to examine the relationship between cooking fuels and incident frailty. And the effects of swapping cooking fuels on frailty risk were also explored.ResultsAmong 4,643 participants (mean age at baseline 80.9 ± 9.6 years, 53.7% male) totaling 11,340 person-years, 923 (19.9%) incident frailty was identified using FI. Compared to clean fuels, cooking with biomass fuels was intricately linked to a 23% rise in frailty risk (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.06–1.43). A similar association was detected between biomass cooking fuels and frailty measured by the FRAIL scale (HR 1.24, 95% CI 1.04–1.50). Sensitive analyses supported the independent relationship between biomass fuels and frailty. Stratified analyses revealed that the frailty risk was higher among town residents (HR 1.44, 95% CI 1.13–1.84) and participants not exercising regularly (HR 1.35, 95% CI 1.11–1.64). In comparison with persistent biomass fuels usage, switching to clean fuels had a trend to reduce the frailty risk, and the opposite effect was observed when swapping from clean to biomass fuels.ConclusionCooking with biomass fuels was associated with an increased frailty risk in older adults, especially amongst those living in town and those lacking regular exercise. More studies are needed to confirm our findings and to evaluate the potential benefits of reducing indoor biomass fuel usage

Advances in alternative splicing identification: deep learning and pantranscriptome

In plants, alternative splicing is a crucial mechanism for regulating gene expression at the post-transcriptional level, which leads to diverse proteins by generating multiple mature mRNA isoforms and diversify the gene regulation. Due to the complexity and variability of this process, accurate identification of splicing events is a vital step in studying alternative splicing. This article presents the application of alternative splicing algorithms with or without reference genomes in plants, as well as the integration of advanced deep learning techniques for improved detection accuracy. In addition, we also discuss alternative splicing studies in the pan-genomic background and the usefulness of integrated strategies for fully profiling alternative splicing

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets

Genome-Wide Association Meta-analysis Identifies Novel Variants Associated With Fasting Plasma Glucose in East Asians

Fasting plasma glucose (FPG) has been recognized as an important indicator for the overall glycemic state preceding the onset of metabolic diseases. So far, most indentified genome-wide association loci for FPG were derived from populations with European ancestry, with a few exceptions. To extend a thorough catalog for FPG loci, we conducted meta-analyses of 13 genome-wide association studies in up to 24,740 nondiabetic subjects with East Asian ancestry. Follow-up replication analyses in up to an additional 21,345 participants identified three new FPG loci reaching genome-wide significance in or near PDK1-RAPGEF4, KANK1, and IGF1R. Our results could provide additional insight into the genetic variation implicated in fasting glucose regulation