HEARTSVG: a fast and accurate method for identifying spatially variable genes in large-scale spatial transcriptomics.

Identifying spatially variable genes (SVGs) is crucial for understanding the spatiotemporal characteristics of diseases and tissue structures, posing a distinctive challenge in spatial transcriptomics research. We propose HEARTSVG, a distribution-free, test-based method for fast and accurately identifying spatially variable genes in large-scale spatial transcriptomic data. Extensive simulations demonstrate that HEARTSVG outperforms state-of-the-art methods with higher scores (average Score=0.

Harnessing TME depicted by histological images to improve cancer prognosis through a deep learning system.

Spatial transcriptomics (ST) provides insights into the tumor microenvironment (TME), which is closely associated with cancer prognosis, but ST has limited clinical availability. In this study, we provide a powerful deep learning system to augment TME information based on histological images for patients without ST data, thereby empowering precise cancer prognosis. The system provides two connections to bridge existing gaps.

Bayesian network-based Mendelian randomization for variant prioritization and phenotypic causal inference.

Mendelian randomization is a powerful method for inferring causal relationships. However, obtaining suitable genetic instrumental variables is often challenging due to gene interaction, linkage, and pleiotropy. We propose Bayesian network-based Mendelian randomization (BNMR), a Bayesian causal learning and inference framework using individual-level data.

Improving the accuracy of the SRK/T formula in Chinese with implanting less than 10 D IOL calculated by the SRK/T formula: the SRK/T-Li formula.

Purpose: To explore the accuracy of the improved SRK/T-Li formula in eyes following implantation of intraocular lens (IOL) of less than 10 D as calculated by using the SRK/T formula in Chinese.

Methods: A total of 489 eyes from 489 patients with cataracts were included in this study. These patients were divided into a training set (271 patients) and a testing set (218 patients).

Enhanced Energy Harvesting Performance of Triboelectric Nanogenerators via Dielectric Property Regulation.

Triboelectric nanogenerators (TENGs) hold great application prospects and research values in the field of energy harvest. The friction layer of TENGs plays an important impact role in their output performance. Therefore, composition modulation of the friction layer is of great significance.

A high-efficiency differential expression method for cancer heterogeneity using large-scale single-cell RNA-sequencing data.

Colorectal cancer is a highly heterogeneous disease. Tumor heterogeneity limits the efficacy of cancer treatment. Single-cell RNA-sequencing technology (scRNA-seq) is a powerful tool for studying cancer heterogeneity at cellular resolution.

STS-BN: An efficient Bayesian network method for detecting causal SNPs.

The identification of the causal SNPs of complex diseases in large-scale genome-wide association analysis is beneficial to the studies of pathogenesis, prevention, diagnosis and treatment of these diseases. However, existing applicable methods for large-scale data suffer from low accuracy. Developing powerful and accurate methods for detecting SNPs associated with complex diseases is highly desired.

High-Dimensional Mediation Analysis With Confounders in Survival Models.

Mediation analysis is a common statistical method for investigating the mechanism of environmental exposures on health outcomes. Previous studies have extended mediation models with a single mediator to high-dimensional mediators selection. It is often assumed that there are no confounders that influence the relations among the exposure, mediator, and outcome.

GapClust is a light-weight approach distinguishing rare cells from voluminous single cell expression profiles.

Single cell RNA sequencing (scRNA-seq) is a powerful tool in detailing the cellular landscape within complex tissues. Large-scale single cell transcriptomics provide both opportunities and challenges for identifying rare cells playing crucial roles in development and disease. Here, we develop GapClust, a light-weight algorithm to detect rare cell types from ultra-large scRNA-seq datasets with state-of-the-art speed and memory efficiency.

Extreme risk spillover between chinese and global crude oil futures.

This paper investigates the risk spillover between China's crude oil futures and international crude oil futures by constructing upside and downside VaR connectedness networks. The findings show that China's crude oil futures behave as a net risk receiver in the global crude oil system, in which Brent and WTI play the leading roles in risk transmission in the system. The dynamic results indicate that the risk spillover between Chinese and international crude oil futures presents obvious time-varying characteristics and has risen sharply since the beginning of 2020, induced by the COVID-19 pandemic.

OsIRO3 Plays an Essential Role in Iron Deficiency Responses and Regulates Iron Homeostasis in Rice.

Iron (Fe) homeostasis is essential for plant growth and development, and it is strictly regulated by a group of transcriptional factors. Iron-related transcription factor 3 (OsIRO3) was previously identified as a negative regulator for Fe deficiency response in rice. However, the molecular mechanisms by which OsIRO3 regulate Fe homeostasis is unclear.

Effects of heat treatment, homogenization pressure, and overprocessing on the content of furfural compounds in liquid milk.

Background: Sterilization of milk is aimed at killing the microorganisms present. There are three main sterilization methods commonly used in milk processing: high temperature and short time (HTST) pasteurization, ultrahigh pasteurization (UP), and ultrahigh temperature (UHT) sterilization. The Maillard reaction is of special interest in studying the effect of heat treatment on milk quality.

Association of Two Polymorphisms, rs1061170 and rs1410996, in Complement Factor H with Age-Related Macular Degeneration in an Asian Population: A Meta-Analysis.

Background: With the increasing number of studies indicating that two single-nucleotide polymorphisms (SNPs), rs1061170 and rs1410996, in complement factor H (CFH) might be associated with the susceptibility to age-related macular degeneration (AMD), the exact association still remains uncertain. Thus, we conducted a meta-analysis to systematically summarize and clarify the association between the two SNPs and the AMD risk particularly in an Asian population.

Methods: A systematic search of studies on the association of two SNPs with the susceptibility to AMD was conducted in PubMed, Embase and Web of Science.