Objective·To investigate the effects of Otoferlin gene-knockout on transcriptional profiles and cellular homeostasis of different cochlear cell subsets in mice, and to explore its role in the pathogenesis of hereditary deafness.Methods·Otoferlin-knockout mice (Otof -/- group) and wild-type mice (WT group) with the same genetic background were used. Single-cell RNA sequencing was performed to obtain transcriptional profiles of cochlear cells. Cell-specific marker genes were used to identify cochlear cell subsets. Differentially expressed genes (DEGs) were screened, followed by Gene Ontology (GO) functional enrichment analysis. Immunofluorescence staining, endolymphatic potential (EP) measurement, and morphological assessment of the stria vascularis were applied for functional validation. Proteomics and gene set module scoring were further used to reveal the impacts of Otoferlin knockout on cochlear cells.Results·A total of 24 cochlear cell subsets were identified via single-cell sequencing. No significant difference was observed in the overall proportions of cell subsets between the two groups, while DEGs exhibited obvious cell-type-specific distribution patterns. DEGs were most enriched in supporting cells, including outer sulcus cells, pillar cells, and Deiters' cells, and were mainly involved in extracellular matrix organization, cochlear development, and ribosome metabolism. DEGs in outer hair cells were significantly enriched in mitochondrial oxidative respiratory chain pathways. In stria vascularis cells, the expression patterns of genes related to ion homeostasis and epithelial development were markedly altered, with abnormal expression of the key ion transport genes Slc12a2 and Kcnj10. Proteomic analysis further revealed marked abnormalities in endoplasmic reticulum-Golgi vesicular transport and mitochondrial translation pathways in the organ of Corti of Otoferlin-knockout mice compared with WT mice, and such abnormalities were most prominent in stria vascularis cells and some glial cells.Conclusion·Although the overall composition of cochlear cell subsets did not change significantly in deaf mice with Otoferlin-knockout, ion transport dysfunction in the stria vascularis and a marked reduction in EP can be detected. Deaf mice present functional abnormalities in non-neuronal cells, including those of the stria vascularis.
Objective·To compare the diagnostic performance of the cardiac magnetic resonance (CMR)-based radiomic model and the extracellular volume fraction (ECV) model in three groups, patients with coronavirus disease 2019 (COVID-19) accompanied by elevated troponin, patients with COVID-19 accompanied by normal troponin, and healthy controls, thereby providing imaging biomarkers for precise clinical stratification.Methods·This single-center prospective cohort study, conducted from January 2022 to December 2024, enrolled 70 patients with COVID-19 from Shanghai Sixth People's Hospital, Shanghai Jiao Tong University School of Medicine. These patients were stratified into the elevated troponin group (n=24) and the normal troponin group (n=46). Meanwhile, 70 healthy participants were recruited as the healthy control group. The 140 participants were randomly divided into a training set (n=98) and a test set (n=42) at a 7∶3 ratio. All participants underwent 3.0 T CMR scanning. Radiomic features, including first-order, shape, and texture features, were extracted from short-axis late gadolinium enhancement (LGE) images. After feature dimensionality reduction, the most discriminative core features were selected to construct the CMR radiomic model. A control model based on myocardial ECV was also constructed. The diagnostic performance of the two models was validated in the test set. Model performance was comprehensively evaluated using the area under the receiver operator characteristic curve (AUC), accuracy, precision, sensitivity, specificity, and F1 score. The DeLong test was used to compare the AUCs between the two models.Results·The CMR radiomic model demonstrated significantly superior performance, as measured by AUC, to the ECV control model in both the training and test sets. Specifically, in the training set, the AUC values for the CMR radiomic model versus the ECV control model were 0.944 vs. 0.741 for the elevated troponin group, 0.903 vs. 0.552 for the normal troponin group, and 0.929 vs. 0.684 for the healthy control group. In the test set, the corresponding values were 0.865 vs. 0.708, 0.691 vs. 0.557, and 0.873 vs. 0.667, respectively.Conclusion·The CMR-based radiomic model can effectively identify COVID-19-associated myocardial injury and provide imaging evidence for the early and precise assessment of such myocardial injury.
Objective·To identify independent risk factors for venous thromboembolism (VTE) in patients with metastatic bone tumors and to develop and validate a machine learning-based prediction model.Methods·This retrospective cohort study included 439 patients with metastatic bone tumors treated at the Clinical Diagnosis and Treatment Center for Metastatic Bone Tumors, Shanghai Sixth People's Hospital, from January 2012 to December 2022 for model training and internal validation. Collected data included demographic characteristics (sex and age at diagnosis of metastatic bone tumors), primary tumor sites, Karnofsky performance status, treatment modalities (radiotherapy and surgery), spinal cord compression, admission complete blood count parameters (red blood cell count, white blood cell count, hemoglobin, and platelet count), coagulation indices (D-dimer, fibrinogen, and prothrombin time), and sites of bone metastases. Patients were divided into the VTE group (n=153) and the non-VTE group (n=286) based on VTE outcomes. Multivariate Logistic regression was used to identify risk factors. Five machine learning models—CatBoost, LightGBM, XGBoost, Gaussian process, and Logistic regression—were trained and evaluated using ten-fold cross-validation to predict VTE risk and identify the optimal model for clinical risk stratification. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. A prospective cohort including 65 patients with metastatic bone tumors admitted between January 2023 and December 2024 was used to validate the performance of the model with the highest AUC. Shapley additive explanations (SHAP) was employed for clinical interpretation of model features.Results·There were no significant differences in age, sex distribution, or Karnofsky performance status between the VTE group and the non-VTE group (all P>0.05). The most common primary tumors were lung cancer (40.3%), breast cancer (12.3%), and prostate cancer (7.3%). The most common sites of bone metastases were the spine (64.7%), pelvis (53.5%), ribs and clavicle (33.9%), and lower limbs (28.7%). Three independent risk factors were identified: lower limb bone metastases (OR=1.89, 95%CI 1.17‒3.07, P=0.010), elevated D-dimer levels (OR=1.06, 95%CI 1.02‒1.09, P<0.001), and prolonged prothrombin time (OR=1.09, 95%CI 1.01‒1.17, P=0.034). CatBoost demonstrated the best performance, with an AUC of 0.82 (95%CI 0.73‒0.90) in the internal test set and 0.80 (95%CI 0.67‒0.93) in the prospective validation set. SHAP analysis confirmed D-dimer as the most important predictor (mean |SHAP|=1.41).Conclusion·Lower limb bone metastases, elevated D-dimer levels, and prolonged prothrombin time are independent risk factors for VTE in patients with metastatic bone tumors. The CatBoost-based prediction model demonstrated robust performance in prospective validation, showing potential for clinical application in predicting VTE risk in patients with metastatic bone tumors.
Objective·To investigate the biological mechanisms and molecular targets of high glucose-induced apoptosis in peritoneal mesothelial cells (PMCs) using proteomics.Methods·The human peritoneal mesothelial cell line HMrSV5 was employed in this study. Cells were divided into a control group (untreated) and a high glucose group (treated with 138 mmol/L glucose). Cellular proteins were collected after 24 h of stimulation. Label-free quantitative proteomics was utilized to analyze changes in the protein expression profile of HMrSV5 cells under high glucose stimulation. Differentially expressed proteins (DEPs) were subjected to pathway enrichment analysis and protein-protein interaction (PPI) network construction. Cell proliferation viability was measured using the CCK-8 assay, and the apoptosis rate was detected by flow cytometry. Western blotting was performed to verify the expression and phosphorylation levels of the key protein checkpoint kinase 2 (CHEK2).Results·A total of 7 366 proteins were identified. Principal component analysis (PCA) revealed significant differences between the control and glucose-treated groups. Compared with the control group, 417 DEPs were identified in the high glucose group, comprising 237 upregulated and 180 downregulated proteins. Subcellular localization analysis showed that upregulated DEPs were primarily distributed in the cytoplasm, nucleoplasm, and mitochondria, while downregulated DEPs were mainly located in the nucleoplasm and cytoplasm. Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses indicated that DEPs were significantly enriched in cell cycle-related pathways, including the mitotic cell cycle, P53 signaling pathway, and cellular senescence. Gene Set Enrichment Analysis (GSEA) further suggested that the P53 signaling pathway was significantly positively enriched in the high glucose group, whereas the E2F target gene pathway and G2/M checkpoint pathway were negatively enriched. PPI network analysis revealed that CHEK2 interacted with multiple cell cycle-related DEPs, suggesting it may be a potential key protein. CCK-8 and flow cytometry assays showed that high glucose stimulation reduced HMrSV5 cell viability and induced apoptosis. Western blotting results confirmed that high glucose stimulation significantly upregulated CHEK2 expression and increased its phosphorylation levels.Conclusion·High glucose stimulation may promote apoptosis in PMCs by affecting cell cycle regulation, and CHEK2 may be a key regulatory protein.
Objective·To analyze the molecular mechanism by which AT-rich interaction domain 1A (ARID1A) deletion regulates lipid metabolism reprogramming in non-small cell lung cancer (NSCLC), and to explore the targeted therapeutic potential and mode of action of the SCAP/SREBP pathway inhibitor fatostatin.Methods·ARID1A wild-type (WT) and knockout (KO) A549 cell lines were constructed using CRISPR-Cas9 technology. Transcriptomic and proteomic analyses were combined to screen for differentially expressed genes and core pathways, and Western blotting was performed to verify the expression of key proteins, including HSP90B1 and SREBP1/2. Oil Red O staining was used to observe intracellular lipid droplet accumulation, and cholesterol and triglyceride quantification kits were used to assess lipid synthesis capacity. CCK-8, scratch wound healing, and Transwell invasion assays were used to evaluate the effects of different concentrations of fatostatin on the proliferation, migration, and invasion of cells in the two groups. JC-1 fluorescent probe was used to detect changes in mitochondrial membrane potential, and Western blotting was used to detect the expression of ferroptosis markers, including ACSL4, GPX4, and SLC7A11.Results·Western blotting showed that, compared with the WT group, the expression of HSP90B1, SREBP1, and SREBP2 proteins was upregulated in KO cells, whereas INSIG1 expression showed no significant change. Oil Red O staining and lipid quantification showed that lipid droplet accumulation and the levels of total cholesterol and triglycerides were higher in KO cells than in WT cells (all P<0.05). The CCK-8 assay showed that fatostatin inhibited the proliferation of cells in both groups in a concentration-dependent manner, and the half-maximal inhibitory concentration (IC50) in the KO group was significantly lower than that in the WT group (P<0.001). Scratch wound healing and Transwell assays showed that, after treatment with the same concentration of fatostatin, the reductions in wound closure rate and in the numbers of migrated and invaded cells were greater in the KO group than in the WT group(all P<0.05). JC-1 staining showed that fatostatin decreased the mitochondrial membrane potential in KO cells but had no significant effect in WT cells. Western blotting showed that ACSL4 expression was upregulated and GPX4 and SLC7A11 expression were downregulated in KO cells.Conclusion·The ARID1A/HSP90B1/SREBP axis is a key pathway regulating lipid metabolism reprogramming in ARID1A-deficient NSCLC. Fatostatin exerts selective anti-tumor effects by targeting this pathway to inhibit lipid synthesis and specifically induce ferroptosis in tumor cells.
