Juan Wang

STNMAE: Identifying Spatial Domains from Spatial Transcriptomics Data with Neighbor-Aware Multi-view Masked Graph Autoencoder

Qi Gao, Junliang Shang, ShaSha Yuan, Feng Li et autres

cn (code pays fourni par la source)

Artificial Sweeteners and Host Response Variability: Insights from the Gut Microbiota for Precise Application

Jie Cai, Qingping Wu, Alaa El-Din Ahmed Bekhit, Juan Wang et autres

• Evidence of artificial sweeteners on health through gut microbiota is summarized. • AS effects on health via gut microbiota is through four potential mechanisms. • AS effects vary in special populations with distinct physiological needs. • Insights support precise application of …

cn, nz, us (code pays fourni par la source)

High Prevalence of Cronobacter in Spices and Emergence of Multidrug-Resistant Salmonella in Retail Foods, Northwest China (2020–2024)

Junxia He, Xianghong Tian, Juan Wang, Wenhui Yan et autres

Given increasing food safety concerns in urbanizing China, this study investigated the microbial contamination of retail foods in Pingliang, a typical inland city in Northwest China (2020-2024). It focused specifically on Cronobacter spp. contamination in spices and antimicrobial resistance in foodborne Salmonella. …

cn (code pays fourni par la source)

A Novel Low-Dimensional Sparse and Low-Rank Representation Method for Single-Cell RNA Sequencing Data Clustering

Zhenduo Zhang, Junliang Shang, Lingyun Dai, Juan Wang

The advancement of single-cell RNA sequencing (scRNA-seq) technology has enabled researchers to capture cellular heterogeneity at the individual cell level, driving progress in diverse fields such as developmental biology, immunology, and cancer research. Accurate cell clustering is a crucial step for researchers …

cn (code pays fourni par la source)

Autoencoder-aided graph convolutional networks integrating multi-view and multi-scale for improving spatial domain identification

Juan Wang, Xuena Liang, Shasha Yuan, Jin‐Xing Liu et autres

cn (code pays fourni par la source)

CoMB-CS: Contribution-aware and multi-armed bandit-based client selection in federated learning for DER forecasting

Linbin Liu, June Li, Juan Wang

cn (code pays fourni par la source)

A multi-source similarity fusion method based on hypergraph convolutional networks and graph transformers for predicting miRNA-disease associations

Ling-Yun Dai, Chris Chunting Mi, Xu Wang, Junliang Shang et autres

cn, tw (code pays fourni par la source)

Association between muscle quality index and depression in adults: A cross-sectional study

Yuanyuan He, Zhenwen Liang, Juan Wang

Background & Aims The muscle quality index (MQI) score is a new indicator of muscle quality and is closely related to physical health. This study aimed to investigate the association between the MQI score and depression in young and middle-aged people. Methods …

cn (code pays fourni par la source)

Fusing spatio-temporal information using supervised local low-rank correlation embedding for depression recognition

Lu Zhang, Peng Xu, Zhijun Yao, Xinyan Zhang et autres

cn (code pays fourni par la source)

Integrating modularity maximization and contrastive learning for identifying spatial domain from spatial transcriptomics

Shasha Yuan, Shengjun Li, Juan Wang

cn (code pays fourni par la source)

Disulfidptosis-associated gene signature predicts prognosis and radioresistance in NSCLC

Jianmin Liu, Juan Wang, Jia Wang, Meng Wu et autres

BACKGROUND: NSCLC has an extremely high mortality rate, and limitations exist in the efficacy of current therapeutic modalities and the choice of treatment strategies. Cells overexpressing cystine/glutamate transporter proteins and experiencing a glucose shortage could lead to NADPH deficiency and excessive disulfide …

cn (code pays fourni par la source)

Cluster-Guided Contrastive Learning With Masked Autoencoder for Spatial Domain Identification Based on Spatial Transcriptomics

Juan Wang, Shasha Yuan, Junliang Shang

Recent advancements in spatial transcriptomics technology have enabled the capture of gene expression profiles while maintaining spatial information. Accurately identifying spatial clustering plays a pivotal role in analyzing spatial transcriptomics data and understanding tissue microenvironments. However, current spatial domain identification methods cannot …

cn (code pays fourni par la source)