Objective: To elucidate the biological basis of traditional Chinese medicine (TCM) syndromes from the perspective of “same syndrome, different diseases” in patients with chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC), thereby providing a complementary approach for the diagnosis and treatment of chronic liver diseases (CLD). Methods: To investigate the dynamic characteristics of TCM syndromes in CLD, transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) was performed from patients with CHB, LC, or HCC presenting with three TCM syndromes: liver gallbladder dampness heat syndrome (LGDHS), liver depression spleen deficiency syndrome (LDSDS), and liver kidney Yin deficiency syndrome (LKYDS). These participants were recruited at Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine between August 1, 2018 and December 31, 2021. Differentially expressed genes (DEGs) were identified using the random variance model (RVM) F test with false discovery rate (FDR) correction. Principal component analysis (PCA) and unsupervised hierarchical clustering were applied to visualize sample grouping. Dynamic network biomarkers (DNB) analysis was employed to detect critical transition stages during syndrome evolution, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses to characterize the functional roles and pathway involvement of the DNB members. Random forest (RF) analysis and the area under the receiver operating characteristic (ROC) curves (AUC) were used to rank the importance of candidate genes. External validation was performed using microarray data from an independent CLD cohort (GSE89377) and RNA-seq data from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. Additionally, reverse transcription quantitative polymerase chain reaction (RT-qPCR) was performed on an independent cohort of LC patients to validate the expression levels of the candidate genes. Results: The study included a total of 132 participants. DNB analysis identified LDSDS stage as a critical tipping point during TCM syndrome evolution across CHB, LC, and HCC. The phosphoinositide 3-kinase/protein kinase B (PI3K-AKT) signaling pathway was consistently enriched in the DNB analysis across all three types of CLD, suggesting its potential involvement in the critical transition of TCM syndromes. Among the 24 core DNB members of the PI3K-AKT pathway, four genes—integrin subunit beta 1 (ITGB1), collagen type IV alpha 1 chain (COL4A1), collagen type IV alpha 2 chain (COL4A2), and DNA damage inducible transcript 3 (DDIT3)—were identified by RF analysis (Gini score > 1) and ROC analysis. ROC analysis demonstrated high discriminative ability for distinguishing LGDHS from LKYDS in CHB patients, with AUC of 0.7891 for ITGB1, 0.7070 for COL4A1, 0.7148 for COL4A2, and 0.8945 for DDIT3. In the independent CLD cohort (GSE89377), all four genes showed significant stepwise upregulation from normal to CHB, LC, and HCC (all P < 0.05). In the TCGA-LIHC dataset, their expression progressively increased with tumor stage. RT-qPCR validation in an independent LC cohort (30 LGDHS vs. 30 LKYDS) confirmed that ITGB1, COL4A2, and DDIT3 were significantly upregulated in LKYDS compared with LGDHS (P = 0.0152, 0.0186, and 0.0247, respectively), whereas COL4A1 showed a non-significant upward trend (P = 0.1201). Conclusion This study introduces a novel approach to understanding the molecular features underlying TCM syndrome evolution in CLD. The PI3K-AKT pathway and four identified genes (ITGB1, COL4A1, COL4A2, and DDIT3) play crucial roles in the transition from excess (LGDHS) to deficiency (LKYDS) via the critical LDSDS stage. These findings offer potential quantitative biomarkers and therapeutic targets for TCM syndrome differentiation and may help arrest syndrome progression in CLD.

Objectives: . Idiopathic sudden sensorineural hearing loss (ISSNHL) is a significant cause of hearing loss. Intratympanic steroid injection (ITSI) is commonly used as an initial or salvage treatment; however, the lack of a standardized treatment protocol has resulted in variability in clinical practice. In addition, no efficient prediction model currently exists to support personalized management. Therefore, this study aimed to develop tailored management strategies for ISSNHL using a machine-learning model. Methods: . This retrospective multicenter cohort study was conducted between January 2015 and December 2020, with data analysis performed between January 2021 and March 2024. Patients were selected based on the International Classification of Diseases, 10th Revision criteria for ISSNHL, along with relevant medication and procedure codes. Patients with pure-tone audiogram results not meeting ISSNHL criteria, better initial hearing in the affected ear, an identifiable etiology, no post-treatment audiogram, or delayed treatment (>6 weeks) were excluded. We included 770 patients diagnosed with ISSNHL who received ITSI. The primary outcome was the area under the receiver operating characteristic curve for prediction performance. Recovery status was determined using the last pure-tone audiogram. Modeling was conducted on the Quanta for Medical Care AI platform using five machine-learning algorithms and a nested cross-validation framework, in which feature selection and hyperparameter tuning were performed in the inner folds and model performance was evaluated in the outer folds. Results: . A random forest classifier outperformed the other models in predicting hearing outcomes, achieving an area under the receiver operating characteristic curve of 0.788. Time to ITSI was the most influential treatment-related factor, with ITSI administered within 10 days of hearing loss being associated with better outcomes. This model can be used to provide personalized prognostic estimates under different treatment protocols. Conclusion . The machine-learning-based prediction model facilitates personalized treatment strategies and timely treatment adjustments for ISSNHL, thereby optimizing the likelihood of complete recovery.

Objective To gain insights into the biological characteristics of different populations of Culex tritaeniorhynchus within and around the Yellow Sea wetland from the perspective of the occurrence of resistance, we investigated the levels of resistance to deltamethrin and kdr gene mutation in the wetland and its peripheral areas. Methods Specimens were collected from Cx. tritaeniorhynchus populations at two monitoring sites in the Rare Bird National Nature Reserve and Tiaozi Ni Wetland Scenic Area, and also from two populations in Yancheng City and the Liuhe District of Nanjing, and the resistance of these mosquitoes to deltamethrin was determined using the CDC biotest bottle method. For each concentration of deltamethrin assessed, a random subset of exposed specimens was selected for amplification of the kdr gene fragment, followed by Sanger sequencing to identify and analyze resistance-associated mutations. Results The LC50 levels of deltamethrin among mosquitoes from the four populations in Luhe, Yancheng, the Rare Bird National Nature Reserve and the Tiaozi Ni Wetland Scenic Area were 2.048 5, 7.798 2, 3.473 3, and 17.695 5 mg/mL, respectively, with corresponding concentrations of deltamethrin ranging from 0.005 to 5.000,0.050 to 50.000,0.050 to 25.000 and 0.050 to 50.000 mg/mL, respectively. Furthermore, the ranges of the KT50 values were 11.76-107.43, 67.05-216.30,29.77-107.43 and 28.40-329.51 min; the 1-h knockdown rates were 34.58%-99.15%, 9.52%-43.80%, 55.09%-73.01%, and 10.09%-68.07%; and the 24-h mortality rates were 12.15%-67.52%,9.52%-79.56%,13.17%-82.21%, and 11.01%-78.99%, respectively. With respect to kdr gene mutation, we assayed a total of 63,70,59, and 57 mosquitoes for the four populations, for which we detected L1014F mutation frequencies of 14.29%, 35.00%, 20.34%, and 31.58%, respectively, with a majority of these mutations being heterozygous for resistance. In addition, five adult mosquitoes were identified has having synonymous mutations at site 1011[i. e. , AAT(asparagine)mutation to AAC(asparagine)]. Conclusions Our findings revealed the clear resistance of Cx. tritaeniorhynchus to deltamethrin in the Yancheng region of the Yellow Sea wetland, and the resistance phenotype and kdr frequency of Cx. tritaeniorhynchus in the wetland environment were comparable to those of Cx. tritaeniorhynchus in the wetland environment, thereby indicating that the resistance of different populations of Cx. tritaeniorhynchus was homogeneous under the pressure of different insecticide selection within and around the wetland. However, the underlying mechanisms need to be further studied.

Hearing loss is the most prevalent disabling disease. Cochlear implantation（CI） serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system（Favorable, Marginal, Poor）. The consensus focuses on common hereditary non-syndromic hearing loss（such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1） and syndromic hereditary hearing loss（such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome）, which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans ; Cochlear Implantation ; Prognosis ; Hearing Loss/surgery* ; Consensus ; Connexin 26 ; Mutation ; Sulfate Transporters ; Connexins/genetics*

Ovarian tumor (OT) is the most lethal form of gynecologic malignancy, with minimal improvements in patient outcomes over the past several decades. Metastasis is the leading cause of ovarian cancer-related deaths, yet the underlying mechanisms remain poorly understood. Psychological stress is known to activate the glucocorticoid receptor (NR3C1), a factor associated with poor prognosis in OT patients. However, the precise mechanisms linking NR3C1 signaling and metastasis have yet to be fully elucidated. In this study, we demonstrate that chronic restraint stress accelerates epithelial-mesenchymal transition (EMT) and metastasis in OT through an NR3C1-dependent mechanism involving nuclear protein 1 (NUPR1). Mechanistically, NR3C1 directly regulates the transcription of NUPR1, which in turn increases the expression of snail family transcriptional repressor 2 (SNAI2), a key driver of EMT. Clinically, elevated NR3C1 positively correlates with NUPR1 expression in OT patients, and both are positively associated with poorer prognosis. Overall, our study identified the NR3C1/NUPR1 axis as a critical regulatory pathway in psychological stress-induced OT metastasis, suggesting a potential therapeutic target for intervention in OT metastasis.

OBJECTIVES: To investigate the protective effect of Yiqi Yangyin Huazhuo Tongluo Formula (YYHT) against high glucose-induced injury in mouse renal podocytes (MPC5 cells) and the possible mechanism. METHODS: Adult Wistar rats were treated with 19, 38, and 76 g/kg YYHT or saline via gavage for 7 days to prepare YYHT-medicated or blank sera for treatment of MPC5 cells cultured in high glucose (30 mmol/L) prior to transfection with a miR-21a-5p inhibitor or a miR-21a-5p mimic. The changes in miR-21a-5p expressions and the mRNA levels of FoxO1, PINK1, and Parkin in the treated cells were detected with qRT-PCR, and the protein levels of nephrin, podocin, FoxO1, PINK1, and Parkin were detected with Western blotting. Autophagic activity in the cells were evaluated with MDC staining. The effect of miR-21a-5p mimic on FoxO1 transcription and the binding of miR-21a-5p to FoxO1 were examined with luciferase reporter gene assay and radioimmunoprecipitation assay. RESULTS: MPC5 cells exposed to high glucose showed significantly increased miR-21a-5p expression, lowered expressions of FoxO1, PINK1, and Parkin1 mRNAs, and reduced levels of FoxO1, PINK1, parkin, nephrin, and podocin proteins and autophagic activity. Treatment of the exposed cells with YYHT-medicated sera and miR-21a-5p inhibitor both significantly enhanced the protein expressions of nephrin and podocin, inhibited the expression of miR-21a-5p, increased the mRNA and protein expressions of FoxO1, PINK1 and Parkin, and upregulated autophagic activity of the cells. Transfection with miR-21a-5p mimic effectively inhibited the transcription of FoxO1 and promoted the binding of miR-21a-5p to FoxO1 in MPC5 cells, and these effects were obviously attenuated by treatment with YYHT-medicated sera. CONCLUSIONS YYHT-medicated sera alleviate high glucose-induced injury in MPC5 cells by regulating miR-21a-5p/FoxO1/PINK1-mediated mitochondrial autophagy.
Animals ; MicroRNAs/genetics* ; Podocytes/pathology* ; Drugs, Chinese Herbal/pharmacology* ; Autophagy/drug effects* ; Rats, Wistar ; Protein Kinases/metabolism* ; Rats ; Forkhead Box Protein O1 ; Mice ; Mitochondria/drug effects* ; Ubiquitin-Protein Ligases/metabolism* ; Glucose ; Diabetic Nephropathies ; Male ; Membrane Proteins/metabolism* ; Intracellular Signaling Peptides and Proteins

OBJECTIVES: To explore the association of the expression of WW domain-containing ubiquitin E3 ligase 1 (WWP1) with immune infiltration in tumor microenvironment (TME) of ovarian cancer. METHODS: Ovarian cancer patient data from The Cancer Genome Atlas (TCGA) were used to analyze the association of WWP1 expression with patient prognosis. TISCH2 was utilized to analyze the changes in immune cell subtypes in TME of metastatic tumor and after chemotherapy. The impact of WWP1 on immune cell infiltration, somatic copy number alterations of WWP1 and evolution of immune cell subtypes was evaluated using TIMER and TIGER pseudo-time analysis. A deep learning model was used to analyze TCGA pathological images to investigate the effect of WWP1 on TME of ovarian cancer. RNA-seq analysis was conducted to identify the differentially expressed genes in WWP1-overexpressing SKOV3 cells and validate immune infiltration. Multicolor immunofluorescence assay was used to analyze the immune markers in SKOV3 and SKOV3/DDP cell xenografts in nude mice. RESULTS: The patients with high WWP1 expression levels had significantly lower overall survival rate (P=0.0012). High WWP1 expression levels and Stage IV disease were both associated with a poor prognosis (P<0.05). In metastatic ovarian cancer or after chemotherapy, the percentages of malignant tumor cells and tumor-associated fibroblasts increased in the TME, accompanied by elevated WWP1 levels. WWP1 expression level was positively correlated with pro-tumorigenic immunosuppressive cells (r=0.1323-0.3955, P<0.05) and negatively with tumor-inhibiting immune cells (r=-0.1949- -0.1333, P<0.05). Specific copy number alterations of WWP1 also influenced CD8⁺ T cell percentage and neutrophil infiltration levels in the TME. RNA-seq analysis of WWP1-overexpressing SKOV3 cells and immunofluorescence assay of the tumor-bearing mice yielded findings consistent with those of bioinformatics analysis. CONCLUSIONS WWP1 may serve as a prognostic biomarker and a potential target for immune regulation in the TME of ovarian cancer.
Female ; Ovarian Neoplasms/genetics* ; Humans ; Ubiquitin-Protein Ligases/metabolism* ; Tumor Microenvironment/immunology* ; Animals ; Mice ; Cell Line, Tumor ; Mice, Nude ; Prognosis ; Gene Expression Regulation, Neoplastic

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis