A quantitative model using multi-parameters in dual-energy CT to preoperatively predict serosal invasion in locally advanced gastric cancer.

Objectives: To develop and validate a quantitative model for predicting serosal invasion based on multi-parameters in preoperative dual-energy CT (DECT).

Materials And Methods: A total of 342 LAGC patients who underwent gastrectomy and DECT from six centers were divided into one training cohort (TC), and two validation cohorts (VCs). Dual-phase enhanced DECT-derived iodine concentration (IC), water concentration, and monochromatic attenuation of lesions, along with clinical information, were measured and collected.

EndoQuad: a comprehensive genome-wide experimentally validated endogenous G-quadruplex database.

G-quadruplexes (G4s) are non-canonical four-stranded structures and are emerging as novel genetic regulatory elements. However, a comprehensive genomic annotation of endogenous G4s (eG4s) and systematic characterization of their regulatory network are still lacking, posing major challenges for eG4 research. Here, we present EndoQuad (https://EndoQuad.

Integrating massive RNA-seq data to elucidate transcriptome dynamics in Drosophila melanogaster.

The volume of ribonucleic acid (RNA)-seq data has increased exponentially, providing numerous new insights into various biological processes. However, due to significant practical challenges, such as data heterogeneity, it is still difficult to ensure the quality of these data when integrated. Although some quality control methods have been developed, sample consistency is rarely considered and these methods are susceptible to artificial factors.

Shape and size design, preparation and test evaluation of color unit in visible light and infrared camouflage.

This study presents a novel method for designing and preparing a visible light-infrared-compatible camouflage sample based on the shape, size of the visible band's color unit and the infrared band's material coatings. The coatings were prepared by using the cold spray method on 1 m × 1 m aluminum substrates with a color unit of the regular hexagonal sample (M1) and regular quadrilateral sample (M2). Then the color difference, the temperature difference and image salience value methods were used to analyze the effectiveness of camouflage samples through the real-scene tests.

GenOrigin: A comprehensive protein-coding gene origination database on the evolutionary timescale of life.

The origination of new genes contributes to the biological diversity of life. New genes may quickly build their network, exert important functions, and generate novel phenotypes. Dating gene age and inferring the origination mechanisms of new genes, like primate-specific genes, is the basis for the functional study of the genes.

pyMeSHSim: an integrative python package for biomedical named entity recognition, normalization, and comparison of MeSH terms.

Background: Many disease causing genes have been identified through different methods, but there have been no uniform annotations of biomedical named entity (bio-NE) of the disease phenotypes of these genes yet. Furthermore, semantic similarity comparison between two bio-NE annotations has become important for data integration or system genetics analysis.

Results: The package pyMeSHSim recognizes bio-NEs by using MetaMap which produces Unified Medical Language System (UMLS) concepts in natural language process.

SAGD: a comprehensive sex-associated gene database from transcriptomes.

Many animal species present sex differences. Sex-associated genes (SAGs), which have female-biased or male-biased expression, have major influences on the remarkable sex differences in important traits such as growth, reproduction, disease resistance and behaviors. However, the SAGs resulting in the vast majority of phenotypic sex differences are still unknown.