S-PLM: Structure-Aware Protein Language Model via Contrastive Learning Between Sequence and Structure.

Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein functions and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences.

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

Introduction: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cancer types, significantly improving survival rates in patients who respond positively to them. However, only a minority of patients benefit from ICI treatments.

Objectives: Identifying ICI responders before treatment could greatly conserve medical resources, minimize potential drug side effects, and expedite the search for alternative therapies.

Scaffold protein SH3BP2 signalosome is pivotal for immune activation in nephrotic syndrome.

Despite clinical use of immunosuppressive agents, the immunopathogenesis of minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) remains unclear. Src homology 3-binding protein 2 (SH3BP2), a scaffold protein, forms an immune signaling complex (signalosome) with 17 other proteins, including phospholipase Cγ2 (PLCγ2) and Rho-guanine nucleotide exchange factor VAV2 (VAV2). Bioinformatic analysis of human glomerular transcriptome (Nephrotic Syndrome Study Network cohort) revealed upregulated SH3BP2 in MCD and FSGS.

S-PLM: Structure-aware Protein Language Model via Contrastive Learning between Sequence and Structure.

Proteins play an essential role in various biological and engineering processes. Large protein language models (PLMs) present excellent potential to reshape protein research by accelerating the determination of protein function and the design of proteins with the desired functions. The prediction and design capacity of PLMs relies on the representation gained from the protein sequences.

MULocDeep web service for protein localization prediction and visualization at subcellular and suborganellar levels.

Predicting protein localization and understanding its mechanisms are critical in biology and pathology. In this context, we propose a new web application of MULocDeep with improved performance, result interpretation, and visualization. By transferring the original model into species-specific models, MULocDeep achieved competitive prediction performance at the subcellular level against other state-of-the-art methods.

Single-cell biological network inference using a heterogeneous graph transformer.

Single-cell multi-omics (scMulti-omics) allows the quantification of multiple modalities simultaneously to capture the intricacy of complex molecular mechanisms and cellular heterogeneity. Existing tools cannot effectively infer the active biological networks in diverse cell types and the response of these networks to external stimuli. Here we present DeepMAPS for biological network inference from scMulti-omics.

The role of extreme high humidex in depression in chongqing, China: A time series-analysis.

As global climate change intensifies, people are paying increasing attention to the impact of temperature changes on adverse mental health outcomes, especially depression. While increasing attention has been paid to the effect of temperature, there is little research on the effect of humidity. We aimed to investigate the association between humidex, an index combining temperature and humidity to reflect perceived temperature, and outpatient visits for depression from 2014 to 2019 in Chongqing, the largest and one of the most hot and humid cities of China.

Association between ambient carbon monoxide levels and hospitalization costs of patients with myocardial infarction: Potential effect modification by ABO blood group.

Previous researches have reported the association between air pollution and various diseases. However, few researches have investigated whether air pollutants are associated with the economic loss resulting from patients' hospitalization, especially the economic loss of hospitalization due to acute cardiovascular events. The purpose of our research was to explore the association between the levels of carbon monoxide (CO), taken as an index of pollution, and the hospitalization costs of myocardial infarction (MI), and the potential effect modification by the ABO blood group.

The association between short-term ambient sulfur dioxide exposure and hospitalization costs of ischemic stroke: a hospital-based study in Chongqing, China.

Evidence of the short-term effects of ambient sulfur dioxide (SO) exposure on the economic burden of ischemic stroke is limited. This study aimed to explore the association between short-term ambient SO exposure and hospitalization costs for ischemic stroke in Chongqing, the most populous city in China. The hospital-based study included 7271 ischemic stroke inpatients.

Prostanoid receptors in hyperfiltration-mediated glomerular injury: Novel agonists and antagonists reveal opposing roles for EP2 and EP4 receptors.

Increased fluid-flow shear stress (FFSS) contributes to hyperfiltration-induced podocyte and glomerular injury resulting in progression of chronic kidney disease (CKD). We reported that increased FFSS in vitro and in vivo upregulates PGE2 receptor EP2 (but not EP4 expression), COX2-PGE -EP2 axis, and EP2-linked Akt-GSK3β-β-catenin signaling pathway in podocytes. To understand and use the disparities between PGE2 receptors, specific agonists, and antagonists of EP2 and EP4 were used to assess phosphorylation of Akt, GSK3β and β-catenin in podocytes using Western blotting, glomerular filtration barrier function using in vitro albumin permeability (P ) assay, and mitigation of hyperfiltration-induced injury in unilaterally nephrectomized (UNX) mice at 1 and 6 months.

Bioinformatics for plant and agricultural discoveries in the age of multiomics: A review and case study of maize nodal root growth under water deficit.

Advances in next-generation sequencing and other high-throughput technologies have facilitated multiomics research, such as genomics, epigenomics, transcriptomics, proteomics, metabolomics, and phenomics. The resultant emerging multiomics data have brought new challenges as well as opportunities, as seen in the plant and agriculture science domains. We reviewed several bioinformatic and computational methods, models, and platforms, and we have highlighted some of our in-house developed efforts aimed at multiomics data analysis, integration, and management issues faced by the research community.

Single-cell RNA sequencing to characterize the response of pancreatic cancer to anti-PD-1 immunotherapy.

Pancreatic cancer (PaC) is resistant to immune checkpoint therapy, but the underlying mechanisms are largely unknown. In this study, we have established four orthotopic PaC murine models with different PaC cell lines by intra-pancreatic inoculation. Therapeutic examinations demonstrate that only tumors induced with Panc02-H7 cells respond to αPD-1 antibody treatment, leading to significantly reduced tumor growth and increased survival in the recipient mice.

Computational methods for protein localization prediction.

The accurate annotation of protein localization is crucial in understanding protein function in tandem with a broad range of applications such as pathological analysis and drug design. Since most proteins do not have experimentally-determined localization information, the computational prediction of protein localization has been an active research area for more than two decades. In particular, recent machine-learning advancements have fueled the development of new methods in protein localization prediction.

MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation.

Prediction of protein localization plays an important role in understanding protein function and mechanisms. In this paper, we propose a general deep learning-based localization prediction framework, MULocDeep, which can predict multiple localizations of a protein at both subcellular and suborganellar levels. We collected a dataset with 44 suborganellar localization annotations in 10 major subcellular compartments-the most comprehensive suborganelle localization dataset to date.

Variation in Gene Expression between Two Lines Differing in Innate Immunity Response.

Microbe associated molecular pattern (MAMPs) triggered immunity (MTI) is a key component of the plant innate immunity response to microbial recognition. However, most of our current knowledge of MTI comes from model plants (i.e.

A mouse model of prenatal exposure to Interleukin-6 to study the developmental origin of health and disease.

Systemic inflammation in pregnant obese women is associated with 1.5- to 2-fold increase in serum Interleukin-6 (IL-6) and newborns with lower kidney/body weight ratio but the role of IL-6 in increased susceptibility to chronic kidney (CKD) in adult progeny is not known. Since IL-6 crosses the placental barrier, we administered recombinant IL-6 (10 pg/g) to pregnant mice starting at mid-gestation yielded newborns with lower body (p < 0.

Transcription Factor β-Catenin Plays a Key Role in Fluid Flow Shear Stress-Mediated Glomerular Injury in Solitary Kidney.

Increased fluid flow shear stress (FFSS) in solitary kidney alters podocyte function . FFSS-treated cultured podocytes show upregulated AKT-GSK3β-β-catenin signaling. The present study was undertaken to confirm (i) the activation of β-catenin signaling in podocytes in vivo using unilaterally nephrectomized (UNX) TOPGAL mice with the β-galactosidase reporter gene for β-catenin activation, (ii) β-catenin translocation in FFSS-treated mouse podocytes, and (iii) β-catenin signaling using publicly available data from UNX mice.

scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses.

Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differential patterns in gene expression. We introduce the scGNN (single-cell graph neural network) to provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This framework formulates and aggregates cell-cell relationships with graph neural networks and models heterogeneous gene expression patterns using a left-truncated mixture Gaussian model.

DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism.

Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives precise and efficient control for the translation process. There is mounting evidence for the important roles of this process in a variety of cellular events. Computational methods for mRNA subcellular localization prediction provide a useful approach for studying mRNA functions.

Dose-response association between sugar- and artificially sweetened beverage consumption and the risk of metabolic syndrome: a meta-analysis of population-based epidemiological studies.

Objective: The associations between sugar-sweetened beverage (SSB) and artificially sweetened beverage (ASB) consumption and the risk of metabolic syndrome (MetS) remain controversial. A quantitative assessment of dose-response associations has not been reported. This study aims to assess the associations between the risk of MetS and SSB, ASB, and total sweetened beverage (TSB, the combination of SSB and ASB) consumption by reviewing population-based epidemiological studies.

Proteomic and Bioinformatic Profiling of Transporters in Higher Plant Mitochondria.

To function as a metabolic hub, plant mitochondria have to exchange a wide variety of metabolic intermediates as well as inorganic ions with the cytosol. As identified by proteomic profiling or as predicted by MU-LOC, a newly developed bioinformatics tool, mitochondria contain 128 or 143 different transporters, respectively. The largest group is the mitochondrial carrier family, which consists of symporters and antiporters catalyzing secondary active transport of organic acids, amino acids, and nucleotides across the inner mitochondrial membrane.

Upregulated proteoglycan-related signaling pathways in fluid flow shear stress-treated podocytes.

The ultrafiltrate flow over the major processes and cell body generates fluid flow shear stress (FFSS) on podocytes. Hyperfiltration-associated increase in FFSS can lead to podocyte injury and detachment. Previously, we showed that FFSS-induced upregulation of the cyclooxygenase 2 (COX2)-PGE-prostaglandin E receptor 2 (EP2) axis in podocytes activates Akt-glycogen synthase kinase-3β-β-catenin and MAPK/ERK signaling in response to FFSS.