DeepMoIC: multi-omics data integration via deep graph convolutional networks for cancer subtype classification.

Background: Achieving precise cancer subtype classification is imperative for effective prognosis and treatment. Multi-omics studies, encompassing diverse data modalities, have emerged as powerful tools for unraveling the complexities of cancer. However, owing to the intricacies of biological data, multi-omics datasets generally show variations in data types, scales, and distributions.

Heterogeneous Graph Embedding with Dual Edge Differentiation.

Recently, heterogeneous graphs have attracted widespread attention as a powerful and practical superclass of traditional homogeneous graphs, which reflect the multi-type node entities and edge relations in the real world. Most existing methods adopt meta-path construction as the mainstream to learn long-range heterogeneous semantic messages between nodes. However, such schema constructs the node-wise correlation by connecting nodes via pre-computed fixed paths, which neglects the diversities of meta-paths on the path type and path range.

Association between copper and Achilles tendon disease: a two-sample Mendelian randomization study.

Background: There is a clear association between micronutrients and Achilles tendon disease (AT). An increase in micronutrients may alleviate AT symptoms and have a therapeutic effect. The aim of this study is to clarify the causal relationship between 15 micronutrients (copper, zinc, magnesium, vitamins A, C, E, D, B6, B12, folic acid, carotene, iron, selenium, calcium, and potassium) and AT.

SiamQuality: a ConvNet-based foundation model for photoplethysmography signals.

. Physiological data are often low quality and thereby compromises the effectiveness of related health monitoring. The primary goal of this study is to develop a robust foundation model that can effectively handle low-quality issue in physiological data.

The unexpected effect of the compound microbial agent NP-M2 on microbial community dynamics in a nonylphenol-contaminated soil: the self-stability of soil ecosystem.

Background: Nonylphenol (NP) is widely recognized as a crucial environmental endocrine-disrupting chemical and persistent toxic substance. The remediation of NP-contaminated sites primarily relies on biological degradation. Compound microbial products, as opposed to pure strains, possess a greater variety of metabolic pathways and can thrive in a wider range of environmental conditions.

Attributed Multi-Order Graph Convolutional Network for Heterogeneous Graphs.

Heterogeneous graph neural networks play a crucial role in discovering discriminative node embeddings and relations from multi-relational networks. One of the key challenges in heterogeneous graph learning lies in designing learnable meta-paths, which significantly impact the quality of learned embeddings. In this paper, we propose an Attributed Multi-Order Graph Convolutional Network (AMOGCN), which automatically explores meta-paths that involve multi-hop neighbors by aggregating multi-order adjacency matrices.

Learnable Graph Convolutional Network With Semisupervised Graph Information Bottleneck.

Graph convolutional network (GCN) has gained widespread attention in semisupervised classification tasks. Recent studies show that GCN-based methods have achieved decent performance in numerous fields. However, most of the existing methods generally adopted a fixed graph that cannot dynamically capture both local and global relationships.

Joint learning of feature and topology for multi-view graph convolutional network.

Graph convolutional network has been extensively employed in semi-supervised classification tasks. Although some studies have attempted to leverage graph convolutional networks to explore multi-view data, they mostly consider the fusion of feature and topology individually, leading to the underutilization of the consistency and complementarity of multi-view data. In this paper, we propose an end-to-end joint fusion framework that aims to simultaneously conduct a consistent feature integration and an adaptive topology adjustment.

AGNN: Alternating Graph-Regularized Neural Networks to Alleviate Over-Smoothing.

Graph convolutional network (GCN) with the powerful capacity to explore graph-structural data has gained noticeable success in recent years. Nonetheless, most of the existing GCN-based models suffer from the notorious over-smoothing issue, owing to which shallow networks are extensively adopted. This may be problematic for complex graph datasets because a deeper GCN should be beneficial to propagating information across remote neighbors.

Effects of different laying periods on airborne bacterial diversity and antibiotic resistance genes in layer hen houses.

Poultry farms are a complex environment for close contact between humans and animals. Accumulating evidence has indicated that pathogens and drug resistance genes in chicken houses may pose a serious threat to public health and economic concerns. However, insufficient knowledge of the indoor aerosol microbiome and resistome profiles of layer hen houses hampers the understanding of their health effects.

Rapid detection of influenza A viruses using a real-time reverse transcription recombinase-aided amplification assay.

Introduction: Influenza A viruses (IAVs) are important pathogens of respiratory infections, causing not only seasonal influenza but also influenza pandemics and posing a global threat to public health. IAVs infection spreads rapidly, widely, and across species, causing huge losses, especially zoonotic IAVs infections that are more harmful. Fast and sensitive detection of IAVs is critical for controlling the spread of this disease.

Pathogenicity and Transmissibility of Clade 2.3.4.4h H5N6 Avian Influenza Viruses in Mammals.

Avian influenza viruses (AIVs) have the potential for cross-species transmission and pandemics. In recent years, clade 2.3.

Emergence of H5N8 avian influenza virus in domestic geese in a wild bird habitat, Yishui Lake, north central China.

• H5N8 viruses emerged in the wild bird habitat at Yishui Lake. • The homology between HG12 and a Russian human strain was over 99%. • HG12 can be transmitted through direct contact between guinea pigs.

Oregano Oil Combined with Macleaya Cordata Oral Solution Improves the Growth Performance and Immune Response of Broilers.

The abuse of AGPs in animal husbandry has led to severe problems such as drug resistance and ecological, and environmental destruction, which seriously threaten human health and public health security. In recent years, extracts of oregano oil and macleaya cordata have become a hot spot in the research and application of AGP substitutes for their safety and high efficiency. This study is the first to report the effect of oregano oil combined with macleaya cordata oral solution on broiler growth performance.

SARS-CoV-2 Virus Culture, Genomic and Subgenomic RNA Load, and Rapid Antigen Test in Experimentally Infected Syrian Hamsters.

The duration of SARS-CoV-2 genomic RNA shedding is much longer than that of infectious SARS-CoV-2 in most COVID-19 patients. It is very important to determine the relationship between test results and infectivity for efficient isolation, contact tracing, and post-isolation. We characterized the duration of viable SARS-CoV-2, viral genomic and subgenomic RNA (gRNA and sgRNA), and rapid antigen test positivity in nasal washes, oropharyngeal swabs, and feces of experimentally infected Syrian hamsters.

Epidemiological Investigation of Porcine Pseudorabies Virus in Hebei Province, China, 2017-2018.

Pseudorabies (PR) is a serious disease affecting the pig industry in China, and it is very important to understand the epidemiology of pseudorabies virus (PRV). In the present study, 693 clinical samples were collected from Bartha-K61 vaccinated pigs with symptoms of suspected PRV infection between January 2017 and December 2018. All cases were referred for full clinical autopsy with detailed examination of histopathological examination, virus isolation and genetic evolution analysis of the PRV glycoprotein E () gene.

The Distribution Characteristics of Aerosol Bacteria in Different Types of Pig Houses.

With the development of modern pig raising technology, the increasing density of animals in pig houses leads to the accumulation of microbial aerosols in pig houses. It is an important prerequisite to grasp the characteristics of bacteria in aerosols in different pig houses to solve the problems of air pollution and disease prevention and control in different pig houses. This work investigated the effects of growth stages on bacterial aerosol concentrations and bacterial communities in pig houses.

Anti-Influenza Effect and Mechanisms of Lentinan in an ICR Mouse Model.

Influenza virus is a serious threat to global human health and public health security. There is an urgent need to develop new anti-influenza drugs. Lentinan (LNT) has attracted increasing attention in recent years.

Aerosol Transmission of the Pandemic SARS-CoV-2 and Influenza A Virus Was Blocked by Negative Ions.

The pandemic of respiratory diseases, such as coronavirus disease 2019 (COVID-19) and influenza, has imposed significant public health and economic burdens on the world. Wearing masks is an effective way to cut off the spread of the respiratory virus. However, due to cultural differences and uncomfortable wearing experiences, not everyone is willing to wear masks; there is an urgent need to find alternatives to masks.

SARS-CoV-2-related pangolin coronavirus exhibits similar infection characteristics to SARS-CoV-2 and direct contact transmissibility in hamsters.

To date, intermediate hosts of SARS-CoV-2 remain obscure and controversial. Several studies have shown that SARS-CoV-2-related pangolin coronavirus (Pangolin-CoV) has a high sequence similarity to SARS-CoV-2 and might be the initial source of SARS-CoV-2; however, the biological characteristics of Pangolin-CoV are still largely unknown. In this study, we evaluated the pathogenicity and transmissibility of Pangolin-CoV in Syrian golden hamsters (Linnaeus, 1758) and compared it with SARS-CoV-2.

Learning Deep Sparse Regularizers With Applications to Multi-View Clustering and Semi-Supervised Classification.

Sparsity-constrained optimization problems are common in machine learning, such as sparse coding, low-rank minimization and compressive sensing. However, most of previous studies focused on constructing various hand-crafted sparse regularizers, while little work was devoted to learning adaptive sparse regularizers from given input data for specific tasks. In this paper, we propose a deep sparse regularizer learning model that learns data-driven sparse regularizers adaptively.

Upregulation of PD-L1 by SPP1 mediates macrophage polarization and facilitates immune escape in lung adenocarcinoma.

Tumor-associated macrophages (TAMs) polarization represents a key regulatory process of tumor progression. However, the underlying mechanisms are unclear. This study aimed to investigate the relationship between secreted phosphoprotein 1 (SPP1) and TAMs in lung adenocarcinoma cells.

The long noncoding RNA, TINCR, functions as a competing endogenous RNA to regulate PDK1 expression by sponging miR-375 in gastric cancer.

Background: Accumulating evidence indicates that the long noncoding RNA, TINCR, plays a critical role in cancer progression and metastasis. However, the overall biological role and mechanisms of TINCR that were involved in human gastric cancer (GC) progression remain largely unknown.

Methods: TINCR expression was measured in 56 paired tumor and adjacent nontumor tissue samples by real-time polymerase chain reaction (PCR).

Functional study of a salt-inducible TaSR gene in Triticum aestivum.

The gene expression chip of a salt-tolerant wheat mutant under salt stress was used to clone a salt-induced gene with unknown functions. This gene was designated as TaSR (Triticum aestivum salt-response gene) and submitted to GenBank under accession number EF580107. Quantitative polymerase chain reaction (PCR) analysis showed that gene expression was induced by salt stress.