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

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective:To evaluate the clinical efficacy of nasal pedicle tissue flap based on nasal blood supply in the reconstruction of nasal skull base defects.Methods:A retrospective analysis was conducted on 138 clinical cases of skull base tumors and cerebrospinal fluid rhinorrhea treated at the Department of Otolaryngology, Head and Neck Surgery at Xiangya Hospital of Central South University from March 2017 to March 2023. A total of 79 males and 59 females were enrolled, aged from 8 to 82 years, with a median age of 51 years, including 108 patients (78.3%) with skull base tumors and 30 patients (21.7%) with cerebrospinal fluid rhinorrhea (and/or meningoencephalocele). During the surgery, 88 cases (63.8%) were repaired with nasal septal mucosal flaps pedicled with the posterior nasal septal artery, 14 cases (10.1%) with mucosal flaps pedicled with the anterior ethmoidal artery on the lateral wall of the nasal cavity, 6 cases (4.3%) with mucosal flaps pedicled with the posterior lateral nasal artery on the lateral wall and nasal floor, 12 cases (8.7%) with mucosal flaps pedicled with the anterior ethmoidal artery and posterior ethmoidal artery, and 18 cases (13.0%) with nasal septal mucosal extension flaps pedicled with the sphenopalatine artery or internal maxillary artery. Patients were followed up for 12 to 72 months postoperatively. Endoscopic examination or skull base enhanced MRI was performed to assess the growth and tumor recurrence in the skull base repair area. The t-test was used for statistical analysis.Results:Among 138 patients, primary repair was successful in 133 patients (96.4%), while 5 patients (3.6%) experienced postoperative cerebrospinal fluid rhinorrhea. These 5 patients all underwent nasal septal mucosal flap repair with the posterior nasal septal artery as the pedicle. Complications included 1 case of mucosal flap necrosis, 1 case of mucosal flap central perforation, and 3 cases of mucosal flap survival peripheral leakage, of which were all successfully treated with a second repair.Conclusion:The use of nasal pedicle mucosal flap based on nasal blood supply is a reliable, safe, and effective technique for repairing skull base defects.

Objective to establish a combined diagnosis model of scleroderma related genes based on gene expression comprehensive database(GEO)and artificial neural network(ANN)and to evaluate its effect and to predict and analyze targeted traditional Chinese medicine.Methods two scleroderma chips GSE23741 and GSE95065 were obtained from the GEO database as the training group data set.Random forest and lasso regression algorithms were used to screen the key genes of scleroderma and construct the ANN model for the diagnosis of scleroderma.The validation data sets GSE76807,GSE32413 and GSE59785 were used to verify the model,and the area under curve(AUC)analysis was used to evaluate the clinical application value of ANN model.The relative expression of key gene mRNA was verified by RT-qPCR experiment.The CIBERSORT algorithm was used to estimate the bioinformatics association between scleroderma and the screened biomarkers.Finally,the key genes were used to screen the targeted traditional Chinese medicine.Results A total of 167 differential genes were obtained.Furthermore,the five most relevant key genes(SERPINE2,SFRP4,SUGCT,FBLN5,NRXN2)were screened by machine learning,and the artificial neural network diagnosis model was constructed.The model was used to draw the subject operating characteristic(ROC)curves diagnosed by the training group and the verification group,and the AUC value of the training group was 1.000.The AUC of verification group were 0.770,0.795 and 0.872 respectively.The result of RT-qPCR experiment is consistent with that of machine learning algorithm.Immune cell infiltration analysis showed that the relative content of memory CD4+T cells was significantly increased in scleroderma group,while the relative content of γ δ T cells in normal group was significantly increased.Key genes are associated with macrophage M1,T cells,memory activated CD4+T cells,resting mast cells,CD8+T cells and so on.According to the key genes,12 traditional Chinese medicines were screened.Most of the four qi and five flavors belong to warm,cold,flat,sweet,pungent and bitter,and most of them belong to the meridians of liver,spleen and lung.Conclusion the artificial neural network diagnosis model of key genes of scleroderma is constructed,which can be used in clinical diagnosis of scleroderma,and the potential targeted traditional Chinese medicine for the treatment of scleroderma is predicted,which provides a new perspective for exploring the pathogenesis of scleroderma.

Objective To establish a diagnostic model for scleroderma by combining machine learning and artificial neural network based on mitochondria-related genes.Methods The GSE95065 and GSE59785 datasets of scleroderma from GEO database were used for analyzing expressions of mitochondria-related genes,and the differential genes were identified by Random forest,LASSO regression and SVM algorithms.Based on these differential genes,an artificial neural network model was constructed,and its diagnostic accuracy was evaluated by 10-fold crossover verification and ROC curve analysis using the verification dataset GSE76807.The mRNA expressions of the key genes were verified by RT-qPCR in a mouse model of scleroderma.The CIBERSORT algorithm was used to estimate the bioinformatic association between scleroderma and the screened biomarkers.Results A total of 24 differential genes were obtained,including 11 up-regulated and 13 down-regulated genes.Seven most relevant mitochondria-related genes(POLB,GSR,KRAS,NT5DC2,NOX4,IGF1,and TGM2)were screened using 3 machine learning algorithms,and the artificial neural network diagnostic model was constructed.The model showed an area under the ROC curves of 0.984 for scleroderma diagnosis(0.740 for the verification dataset and 0.980 for cross-over validation).RT-qPCR detected significant up-regulation of POLB,GSR,KRAS,NOX4,IGF1 and TGM2 mRNAs and significant down-regulation of NT5DC2 in the mouse models of scleroderma.Immune cell infiltration analysis showed that the differential genes in scleroderma were associated with follicular helper T cells,immature B cells,resting dendritic cells,memory activated CD4+T cells,M0 macrophages,monocytes,resting memory CD4+T cells and mast cell activation.Conclusion The artificial neural network diagnostic model for scleroderma established in this study provides a new perspective for exploring the pathogenesis of scleroderma.

Objective:To investigate the relationship between cancer node status identified after radical resection and patterns of recurrence in stage Ⅱ/Ⅲ gastric cancer patients for developing personalized follow-up plans in node-positive patients.Methods:A retrospective analysis was conducted on 706 stage Ⅱ/Ⅲ gastric cancer patients who underwent curative intent surgery at Henan Cancer Hospital from Sep 2015 to Sep 2018. Patients were categorized into node-positive (TDs +) and node-negative (TDs -) groups based on their cancer node status. Clinical-pathological characteristics and recurrence patterns were compared between the groups to formulate an optimized follow-up plan. Results:Among the patients, there were 112 TDs + and 594 TDs - cases. TDs - patients exhibited significantly better overall survival and disease-free survival rates at 1 and 3 years compared to the TDs + group (92.4%,72.2% vs. 79.4%,38.8%;87.9%,68.6% vs. 66.7%,35.9%, all P<0.05). The cumulative recurrence rates of peritoneal and distant metastases were higher in TDs + patients compared to TDs - patients, with statistical significance (33.0% vs. 14.5%,21.4% vs. 10.8%, χ 2=21.285,8.851 all P<0.05). TDs + patients experienced significantly earlier median time to distant metastasis compared to TDs - patients (9.0 months vs. 15.4 months , Z=-2.294 P=0.022). The risk of peritoneal metastasis recurrence was higher in the TDs + group, showing a bimodal recurrence pattern at 8.5 and 15.0 months post-surgery. TDs + patients also had a higher risk of distant metastasis recurrence, with a single peak at 6 months. Conclusion:Postoperative recurrence patterns differ between TDs + and TDs - patients, and an optimized follow-up plan can enhance early detection of recurrence.

Objective:To establish a nomogram to predict overall survival of patients with stage Ⅰ-Ⅲ gastric cancer (GC) based on preoperative inflammatory markers.Methods:Clinicopathological and follow-up data of 1 035 patients with stage Ⅰ-Ⅲ gastric cancer operated at He'nan Cancer Hospital between May 2015 and Oct 2016 were retrospectively collected. A nomogram was established based on prognostic factors. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA) were used to verify the performance of the model according to differentiation, calibration and clinical utility.Results:A total of 1 035 patients were enrolled . The median follow-up time was 41.9 months; According to the optimal cutoff value, 170 were with elevated neutrophil-to-lymphocyte ratio (NLR) and 865 with a reduced　ratio; 562 in elevated platelet-to-lymphocyte ratio (PLR) vs. 473 in the reduced group; fibrinogen/albumin ratio (FAR) elevated in 108 group vs. 972 in the reduced group; 180 in the prognostic nutritional index score (PNI) elevated group and 855 in the reduced group. Two hundred and sixty-seven patients were categorized at stage Ⅰ, 334 at stage Ⅱ ,434 at stage Ⅲ. Multivariate regression analysis showed tumor location, vascular tumor thrombus, pTNM stage, FAR, PNI and NLR were independent prognostic factors (all P<0.05). The C-index of the nomogram was 0.723 (95% CI: 0.710 -0.736) and had better clinical utility than the American Joint Committee on Cancer (AJCC) 8th TNM staging system 0.693 (95% CI, 0.681 -0.705). The calibration curve of the nomogram showed that the predicted survival rate was consistent with the actual survival rate in GC patients. Compared to AJCC 8th pTNM staging system, the DCA curve indicate that the nomogram has a higher net income. Conclusion:The nomogram predicting overall survival of patients with stage Ⅰ-Ⅲ gastric cancer is established and verified , which provides better individual prediction than TNM staging system.

Objective:To investigate the effect of neoadjuvant chemotherapy on the prognosis of gastric neuroendocrine cancer.Methods:This study included 102 patients with gastric neuroendocrine cancer, the disease-free survival rate (DFS) and overall survival rate (OS) were compared between two groups according whether they were given neoadjuvant chemotherapy before radical resection.Results:Ninteen of the 102 patients received neoadjuvant chemotherapy combined with surgery, while the other 83 patients received upfront surgery . The 1-year survival rate of the direct operation group and the NAC group was 83.0% and 51.8%, respectively, and the 3-year survival rate was 63.0% and 33.3%, respectively ( χ2=9.182, P=0.002). The 1-year disease-free survival rate was 80.4% and 38.5%, respectively, and the 3-year disease-free survival rate was 59.8% and 25.7%, respectively ( χ2=11.142, P=0.001). Subgroup analysis showed that the difference between the two groups was mainly significant between MANEC patients ( χ2=10.742, P=0.001). Multivariate analysis showed that neoadjuvant therapy was an independent risk factor affecting the overall survival rate (all P<0.05). Univariate analysis shows that only adjuvant chemotherapy is the risk factor affecting disease-free survival ( P<0.05). When the neoadjuvant chemotherapy and the direct surgery were matched 1∶1, the OS and DFS of the direct surgery group were better than those of the NAC patients ( χ2=4.014, 3.954; P=0.045, 0.047). Conclusion:Neoadjuvant chemotherapy failed to improve the prognosis of patients with gastric neuroendocrine cancer/MANEC.

Objective:To study the effects of miR-128-3p on the migration and invasion of the gastric cancer cells.Methods:qRT-PCR was used to detect the expression of miR-128-3p in 126 gastric cancer tissues and adjacent tissues from Jan 2014 to Jan 2016 at He'nan Cancer Hospital. The effect of miR-128-3p on the invasion and migration of gastric cancer cell line was detected.The expression of miR-128-3p related proteins was detected by Western blotting, miRNA on-line target prediction tool for the prediction of miR-128-3p directly regulated downstream target genes.Results:the expression of miR-128-3p in gastric cancer was significantly higher than that in adjacent non-tumor tissues ( P<0.05). The expression of miR-128-3p was correlated with the vascular tumor thrombus, pN staging and pTNM staging, the prognosis of patients with high expression of miR-128-3p was poor (all P<0.05). MiR-128-3p expression was significantly higher in gastric cancer cell lines ( P<0.05). Online target prediction tool and double luciferase reporter gene showed that CLDN18 was a downstream target gene directly regulated by mir-128-3p. Conclusion:The high expression of miR-128-3p is related to the poor prognosis of gastric cancer patients.