Ye Tian

LHX1 as a potential biomarker regulates EMT induction and cellular behaviors in uterine corpus endometrial carcinoma

To investigate the expression of LHX1 and its role as a biomarker in the diagnosis and prognosis of Uterine Corpus Endometrial Carcinoma (UCEC). The Cancer Genome Atlas (TCGA) database was used to detect the expression level of LHX1 in UCEC cells and tissues, and to find out the effect of LHX1 on prognosis. Co-expressed genes were then identified by Spearman correlation analysis, and the protein-protein interaction network was constructed using Cytoscape software. The R "clusterProfiler" package was used to conduct Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. A series of in vitro experiments were performed to evaluate LHX1 expression and detect UCEC cell proliferation, invasion, and migration. Western blotting was used to determine the effect of LHX1 on expression levels of Epithelial-Mesenchymal Transition (EMT)-related proteins. LHX1 was upregulated in UCEC tissues and correlated with poor overall survival and disease-specific survival outcomes. Functional enrichment analysis suggested that genes co-expressed with LHX1 were enriched in cell adhesion. The expression of LHX1 was positively correlated with the expression levels of genes related to EMT induction and invasion. LHX1 can enhance the proliferation, migration, and invasion activities of UCEC cells in vitro, and alter the expression levels of EMT-related proteins. LHX1 expression was highly upregulated in UCEC cells and tissues, which was correlated with the prognosis of patients with UCEC. LHX1 may regulate UCEC progression at least in part by modulating EMT induction.

Deep Learning‐Enhanced Hand‐Driven Microfluidic Chip for Multiplexed Nucleic Acid Detection Based on RPA/CRISPR

AbstractThe early detection of high‐risk human papillomavirus (HR‐HPV) is crucial for the assessment and improvement of prognosis in cervical cancer. However, existing PCR‐based screening methods suffer from inadequate accessibility, which dampens the enthusiasm for screening among grassroots populations, especially in resource‐limited areas, and contributes to the persistently high mortality rate of cervical cancer. Here, a portable system is proposed for multiplexed nucleic acid detection, termed R‐CHIP, that integrates Recombinase polymerase amplification (RPA), CRISPR detection, Hand‐driven microfluidics, and an artificial Intelligence Platform. The system can go from sample pre‐processing to results readout in less than an hour with simple manual operation. Optimized for sensitivity of 10−17 M for HPV‐16 and 10−18 M for HPV‐18, R‐CHIP has an accuracy of over 95% in 300 tests on clinical samples. In addition, a smartphone microimaging system combined with the ResNet‐18 deep learning model is used to improve the readout efficiency and convenience of the detection system, with initial prediction accuracies of 96.0% and 98.0% for HPV‐16 and HPV‐18, respectively. R‐CHIP, as a user‐friendly and intelligent detection platform, has great potential for community‐level HR‐HPV screening in resource‐constrained settings, and contributes to the prevention and early diagnosis of other diseases.