A Kind of New Surface Modeling Method Based on DEM Data

Surface elevation changes greatly in the river erosion area. Due to the limitation of the acquisition equipment and cost, the traditional seismic acquisition data has sparse physical points both horizontally and longitudinally, the density of surface measurement data is not enough to survey the surface structure in detail. With the development of science and technology, and the application of satellite technology, the DEM elevation data obtained from the geographic information system (GIS) are becoming more and more accurate. In this paper, a precise modeling is performed on the surface based on the geographic information from the river erosion area and combined with the results of the surface survey control points, a good effect is achieved.Key words: River erosion area; Geographic information; Similarity coefficient; Kriging interpolation; Surface modeling; High and low frequency static

In Vitro/Vivo Activity of Potential MCR-1 Inhibitor in Combination With Colistin Againsts mcr-1-Positive Klebsiella pneumonia

Carbapenem resistance among strains of the nosocomial pathogen Klebsiella pneumoniae is increasing worldwide, causing serious clinical infections and higher mortality rates. Polymyxins are some of the few “last resort” options for treatment of carbapenem-resistant Enterobacteriaceae, including K. pneumoniae, however, the emergence of plasmid-mediated colistin resistance gene mcr-1 has largely rendered polymyxin-class antibiotics ineffective in a clinical setting. We previously identified a natural compound, pterostilbene, which has a synergistic effect in combination with polymyxins. Here, we aimed to determine whether pterostilbene application can restore the bactericidal activity of polymyxins against mcr-1-positive K. pneumoniae. Checkerboard MIC studies confirmed that pterostilbene reduces the MIC of colistin against mcr-1-positive clinical K. pneumoniae isolates, with the bacteria going from resistant to sensitive, and also demonstrated a synergistic effect with colistin (FIC index = 0.11 ± 0.04 or 0.28 ± 0.00). Time-killing assays showed that individually, both pterostilbene and colistin failed to eradicate K. pneumoniae strains, while in combination, the two drugs effectively eliminated K. pneumoniae ZJ02 and K. pneumoniae ZJ05 by 1–3 h post-inoculation. The combined disk test also showed increases in the zones of inhibition only for mcr-1-positive Escherichia coli and K. pneumoniae isolates. A mouse infection model demonstrated that the survival rate of mice at 7 days post-intraperitoneal injection with a lethal dose of K. pneumoniae ZJ05 was significantly promoted from 0 to 67% following combination therapy. This is the first time a MCR-1 inhibitor has successfully been used in combination with colistin against human clinical MCR-1 producing K. pneumoniae ZJ05 isolate

A multicenter study of fetal chromosomal abnormalities in Chinese women of advanced maternal age

AbstractObjectiveThis study aimed to determine the rates of different fetal chromosomal abnormalities among women of advanced maternal age in China and to discuss the possible misdiagnosis risks of newer molecular techniques, for selection of appropriate prenatal screening and diagnostic technologies.Materials and MethodsSecond trimester amniocentesis and fetal karyotype results of 46,258 women were retrospectively reviewed. All women were ≥ 35 years old with singleton pregnancies. The rates of clinically significant chromosomal abnormalities (CSCAs), incidence of chromosomal abnormalities, and correlations with age were determined.ResultsFrom 2001 to 2010, the proportion of women of advanced maternal age undergoing prenatal diagnosis increased from 20% to 46%. The mean age was 37.4 years (range, 35–46 years). A total of 708 cases of CSCAs, with a rate of 1.53% were found. Trisomy 21 was the most common single chromosome abnormality and accounted for 55.9% of all CSCAs with an incidence of 0.86%. Trisomy 13, trisomy 18, and trisomy 21, the most common chromosome autosomal aneuploidies, accounted for 73.6% of all CSCAs, with a rate of 1.13%. As a group, the most common chromosomal aneuploidies (13/18/21/X/Y) accounted for 93.9% of all abnormalities, with a rate of 1.44%. The incidence of trisomy 21, trisomy 13/18/21 as a group, and 13/18/21/X/Y as a group was significantly greater in women aged 39 years and older (p < 0.001), but was not different between women aged 35 years, 36 years, 37 years, and 38 years.ConclusionThese findings may assist in genetic counseling of advanced maternal age pregnant women, and provide a basis for the selection of prenatal screening and diagnostic technologies

Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As LLMs find applications across diverse domains, the reliability and accuracy of their outputs become vital. We define the Factuality Issue as the probability of LLMs to produce content inconsistent with established facts. We first delve into the implications of these inaccuracies, highlighting the potential consequences and challenges posed by factual errors in LLM outputs. Subsequently, we analyze the mechanisms through which LLMs store and process facts, seeking the primary causes of factual errors. Our discussion then transitions to methodologies for evaluating LLM factuality, emphasizing key metrics, benchmarks, and studies. We further explore strategies for enhancing LLM factuality, including approaches tailored for specific domains. We focus two primary LLM configurations standalone LLMs and Retrieval-Augmented LLMs that utilizes external data, we detail their unique challenges and potential enhancements. Our survey offers a structured guide for researchers aiming to fortify the factual reliability of LLMs.Comment: 62 pages; 300+ reference

Transcriptional and Functional Analysis of the Effects of Magnolol: Inhibition of Autolysis and Biofilms in Staphylococcus aureus

BACKGROUND: The targeting of Staphylococcus aureus biofilm structures are now gaining interest as an alternative strategy for developing new types of antimicrobial agents. Magnolol (MOL) shows inhibitory activity against S. aureus biofilms and Triton X-100-induced autolysis in vitro, although there are no data regarding the molecular mechanisms of MOL action in bacteria. METHODOLOGY/PRINCIPAL FINDINGS: The molecular basis of the markedly reduced autolytic phenotype and biofilm inhibition triggered by MOL were explored using transcriptomic analysis, and the transcription of important genes were verified by real-time RT-PCR. The inhibition of autolysis by MOL was evaluated using quantitative bacteriolytic assays and zymographic analysis, and antibiofilm activity assays and confocal laser scanning microscopy were used to elucidate the inhibition of biofilm formation caused by MOL in 20 clinical isolates or standard strains. The reduction in cidA, atl, sle1, and lytN transcript levels following MOL treatment was consistent with the induced expression of their autolytic repressors lrgA, lrgB, arlR, and sarA. MOL generally inhibited or reversed the expression of most of the genes involved in biofilm production. The growth of S. aureus strain ATCC 25923 in the presence of MOL dose-dependently led to decreases in Triton X-100-induced autolysis, extracellular murein hydrolase activity, and the amount of extracellular DNA (eDNA). MOL may impede biofilm formation by reducing the expression of cidA, a murein hydrolase regulator, to inhibit autolysis and eDNA release, or MOL may directly repress biofilm formation. CONCLUSIONS/SIGNIFICANCE: MOL shows in vitro antimicrobial activity against clinical and standard S. aureus strains grown in planktonic and biofilm cultures, suggesting that the structure of MOL may potentially be used as a basis for the development of drugs targeting biofilms

Modeling islet enhancers using deep learning identifies candidate causal variants at loci associated with T2D and glycemic traits.

Genetic association studies have identified hundreds of independent signals associated with type 2 diabetes (T2D) and related traits. Despite these successes, the identification of specific causal variants underlying a genetic association signal remains challenging. In this study, we describe a deep learning (DL) method to analyze the impact of sequence variants on enhancers. Focusing on pancreatic islets, a T2D relevant tissue, we show that our model learns islet-specific transcription factor (TF) regulatory patterns and can be used to prioritize candidate causal variants. At 101 genetic signals associated with T2D and related glycemic traits where multiple variants occur in linkage disequilibrium, our method nominates a single causal variant for each association signal, including three variants previously shown to alter reporter activity in islet-relevant cell types. For another signal associated with blood glucose levels, we biochemically test all candidate causal variants from statistical fine-mapping using a pancreatic islet beta cell line and show biochemical evidence of allelic effects on TF binding for the model-prioritized variant. To aid in future research, we publicly distribute our model and islet enhancer perturbation scores across ~67 million genetic variants. We anticipate that DL methods like the one presented in this study will enhance the prioritization of candidate causal variants for functional studies

Genomic data for 78 chickens from 14 populations

Background: Since the domestication of the red jungle fowls (Gallus gallus; dating back to~10 000 B.P.) in Asia, domestic chickens (Gallus gallus domesticus) have been subjected to the combined effects of natural selection and human-driven artificial selection; this has resulted in marked phenotypic diversity in a number of traits, including behavior, body composition, egg production, and skin color. Population genomic variations through diversifying selection have not been fully investigated. Findings: The whole genomes of 78 domestic chickens were sequenced to an average of 18-fold coverage for each bird. By combining this data with publicly available genomes of five wild red jungle fowls and eight Xishuangbanna game fowls, we conducted a comprehensive comparative genomics analysis of 91 chickens from 17 populations. After aligning ~21.30 gigabases (Gb) of high-quality data from each individual to the reference chicken genome, we identified ~6.44 million (M) single nucleotide polymorphisms (SNPs) for each population. These SNPs included 1.10 M novel SNPs in 17 populations that were absent in the current chicken dbSNP (Build 145) entries. Conclusions: The current data is important for population genetics and further studies in chickens and will serve as a valuable resource for investigating diversifying selection and candidate genes for selective breeding in chickens.Peer reviewedAnimal Scienc

Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives

Abstract Background: Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown. Findings: We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression–based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation. Conclusions: These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments