Biomedical subjects

Shijun Li

Publications and source records attributed to Shijun Li.

3 recordsLinked to original sources

PubMed2026

GICPIdb: an archival repository of multimodal data focusing on pathological images for gastrointestinal cancers.

INTRODUCTION: Deep learning (DL) shows great potential for predicting biomarkers from routine histopathological slides of gastrointestinal (GI) cancers. Yet most existing models are validated on limited patient cohorts, while pathological image annotation and molecular marker standardization demand substantial professional expertise. To address these gaps, we constructed the Gastrointestinal Cancer Pathological Image Archive (GICPIdb, gicpidb.shubuzuo.top), a dedicated database and web platform covering seven major GI cancer types. METHODS: High-quality hematoxylin and eosin (H&E)-stained whole-slide images were collected from multiple sources and uniformly processed. Image annotations were performed by board-certified pathologists following standardized protocols. GICPIdb offers five interactive web modules for data uploading, quality control, feature extraction, online annotation and AI-based prediction. Its intuitive interface supports data browsing, retrieval, visualization and downloading. RESULTS: The database houses 2,863 pathologist-annotated, uniformly processed, high-quality H&E stained images collected from 2,655 patients. Of these, 1,699 patients were sourced from The Cancer Genome Atlas (TCGA), 182 from the Clinical Proteomic Tumor Analysis Consortium (CPTAC), and 424 from China-Japan Friendship Hospital and 350 from Chifeng Municipal Hospital in Inner Mongolia, China. It also integrates data on over 50 key molecular markers (e.g., MSI, TMB) and prognostic labels related to survival, recurrence and metastasis. DISCUSSION: GICPIdb aims to promote the development of DL-driven AI tools for cancer research and clinical translation. The multi-institutional data collection and standardized annotation pipeline are expected to enhance the generalizability and reproducibility of AI-based prediction models across diverse patient populations.

deep learning↗

PubMed2026

Genomic surveillance reveals escalating antimicrobial resistance and plasmid diversity in clinical Salmonella 1,4,[5],12:i:- ST34 isolates from Guizhou Province, China.

INTRODUCTION: Salmonella 1,4,[5],12:i:- ST34 has emerged as a significant public health issue due to its association with various antimicrobial resistance genes (ARGs) and transferable plasmids. However, its genomic characteristics and potential influence on public health in Guizhou have not been comprehensively assessed. METHODS: From 2019 to 2023, a 5-year surveillance was conducted in nine cities (prefectures) of Guizhou Province. We integrated phenotypic and genomic analyses of 281 clinical Salmonella 1,4,[5],12:i:- ST34 isolates to investigate the prevalence of ARGs and plasmids and to analyze the molecular epidemiology and evolution. RESULTS: The isolates exhibited resistance to first-line antibiotics, with 22.4% for ciprofloxacin, 11.4% for azithromycin, 18.5% for ceftazidime, and 39.1% for cefotaxime. ARGs showed substantial agreement with phenotypes for tetracycline, macrolides, third-generation cephalosporins (3GCs), carbapenems, and colistin (80.8-100.0% consistency; Kappa: 0.50-1.00). Plasmid analysis identified IncQ1 (84.3%) and IncHI2/IncHI2A (26.3%) as the main replicons, with the variety of plasmid replicons increasing from 7 to 21 over the 5 years. ARGs associated with resistance to critically important antibiotics (CIAs) were frequently predicted to be located on plasmid-associated contigs, with significant associations observed between IncHI2/IncHI2A plasmids and ARGs conferring resistance to fluoroquinolones, macrolides, and cephalosporins (P < 0.05). Molecular typing divided 281 isolates into 37 cgSTs, with cgST52428 being the most common. Molecular epidemiological analysis revealed that Guizhou isolates primarily clustered together, sharing close genetic ties with those from Sichuan and Guangdong, and exhibited the highest genetic similarity to pork-derived isolates. Phylogenetic analysis revealed clustering of CIA-resistant ARGs and plasmids in Clades 4 and 5, with a significant association between IncHI2/IncHI2A plasmids and CIA-resistant ARGs (χ2 = 112.12, P < 0.001). Additionally, class 1 integron was associated with higher ARG burdens, while virulence-associated genes were conserved and predominantly chromosome-associated. Gene-content analysis revealed that isolates in Clades 4 and 5 harbored the largest mean gene complements, and cgST52428 isolates also harbored the largest among dominant cgSTs. DISCUSSION: This study presents a comprehensive genomic profile of Salmonella 1,4,[5],12:i:- ST34 in Guizhou, providing essential data for exploring the resistance characteristics and investigating the molecular epidemiology of Salmonella 1,4,[5],12:i:-.

ST34↗

PubMed2026

Genomic and virulence characteristics of Staphylococcus aureus isolates from foodborne outbreak cases.

This study aimed to investigate the genomic characteristics, enterotoxin production, and antimicrobial resistance profiles of Staphylococcus aureus isolates associated with foodborne outbreaks. A total of 19 bacterial isolates were collected from foodborne outbreaks in Guizhou Province, China between 2014 and 2023. Following biochemical identification, all isolates were confirmed as S. aureus. Phylogenetic analysis divided the 19 strains into seven branches. Enterotoxin production was detected using standard microbiological techniques and immunoassays. Antimicrobial susceptibility was evaluated using the broth microdilution method. Whole-genome sequencing and subsequent bioinformatic analyses were conducted to characterize virulence genes, antimicrobial resistance genes, multilocus sequence typing (MLST) genotypes, and phylogenetic relationships among the isolates. This study found that all strains produced classical staphylococcal enterotoxins, with staphylococcal enterotoxin (SEA) showing the highest detection rate (63.16%). Virulence gene profiling revealed widespread presence of hlb, hlgA, nuc, clfB, spa, and set genes. All strains were resistant to penicillin, with high resistance rates for erythromycin and cefoxitin. Multidrug resistance occurred in 11 of the 19 strains, and 22 resistance genes were identified. MLST analysis showed that ST6 and ST59 were the dominant types, with ST59 methicillin-resistant S. aureus (MRSA) strains displaying stronger resistance and more virulence determinants. These findings provide insights into the virulence, resistance, and molecular epidemiology of S. aureus strains involved in foodborne outbreaks, and may provide useful information for future surveillance and risk assessment.

Staphylococcus aureus↗