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Qi Yu

Publications and source records attributed to Qi Yu.

3 recordsLinked to original sources

Association of Enterocytozoon bieneusi Infection with chronic/persistent diarrhea and ITS genotypic diversity: a hospital-based case-control study in Suburban Shanghai, China.

Enterocytozoon bieneusi is a globally distributed zoonotic enteric pathogen that remains largely overlooked in routine diarrheal disease surveillance. Although previous studies in Shanghai, China, have reported elevated prevalence in diarrheal populations, case-control data from suburban areas at the peri&#x2011;urban interface and the strength of the association between E. bieneusi infection and chronic diarrhea in non-immunocompromised individuals remain poorly characterized. We performed a hospital-based case-control study in suburban Shanghai, enrolling 286 diarrheal outpatients without documented immunodeficiency and 138 asymptomatic controls frequency-matched for age and sex. Fecal specimens were collected and subjected to genomic DNA extraction. E. bieneusi was detected via nested PCR amplification of the ribosomal internal transcribed spacer (ITS) region. Factors associated with infection were identified using multivariate logistic regression. Genotypic diversity and zoonotic potential were assessed by Sanger sequencing and phylogenetic analysis. The overall prevalence of E. bieneusi was 12.2% (35/286) in diarrheal patients, significantly higher than the 2.2% (3/138) observed in asymptomatic controls (P < 0.001). E. bieneusi positivity was independently associated with chronic/persistent diarrhea (adjusted odds ratio = 2.63, 95% confidence interval: 1.25-5.54, P = 0.011). Fourteen distinct ITS genotypes were identified, comprising five known genotypes (D, EbpD, SHW7, Henan-III, and CHG5) and nine novel genotypes (designated SHH2 to SHH10). Thirteen genotypes clustered within Group 1, and one genotype (CHG5) fell within Group 2, two phylogenetic groups that contain genotypes with documented zoonotic potential in global surveillance. E. bieneusi was detected at a relatively high prevalence among diarrheal patients in suburban Shanghai, and its detection was associated with chronic/persistent diarrhea. The predominance of zoonotic genotypes and the identification of nine novel Group 1 genotypes indicate phylogenetic similarity to known zoonotic lineages and warrant further investigation of local zoonotic transmission; no animal or environmental samples were analyzed in this study. These findings suggest that E. bieneusi testing may be considered as part of the differential diagnosis for patients with unexplained chronic/persistent diarrhea and highlight the need for One Health surveillance in the surveyed area.

Diarrhea

Bridging Organ-on-a-Chip and Omics: A Multi-Dimensional Frontier in Biomedical Research.

Organ-on-a-Chip (OOC) technology offers a powerful platform for replicating human tissue-specific microenvironments, thereby narrowing the translational gap between conventional biomedical models and actual human physiology. Concurrently, omics technologies deliver comprehensive molecular-level insights into biological systems. This review highlights the transformative potential of integrating OOC platforms with high-throughput omics methodologies. We systematically examine the classification, structural configurations, and engineering principles underlying OOC systems, alongside the defining attributes of key omics domains-genomics, transcriptomics, proteomics, and metabolomics. The convergence of dynamic OOC models with advanced omics technologies enables high-resolution, multi-dimensional analyses across numerous biomedical applications, including drug metabolism, disease mechanisms, environmental toxicity assessments, and host-microbiome interactions. This interdisciplinary integration is driving a paradigm shift in precision and translational medicine. However, several challenges remain to be addressed, such as the development of whole-organ mimetics, adaptation of sample collection techniques, and real-time artificial intelligence-based integration of biosensor data with multi-omics datasets. Addressing these hurdles will be vital for unlocking the full potential of this technological synergy in biomedical science.

Multiomics