OBJECTIVE To explore the mechanism of Yiqi yangyin huazhuo tongluo formula in ameliorating diabetic kidney disease （DKD） based on the gut microbiota-lipopolysaccharide （LPS）/Caspase-11/gasdermin D （GSDMD） pathway.METHODS A DKD mouse model was established by high-fat and high-sugar diet combined with intraperitoneal injection of low-dose streptozotocin. The successfully modeled mice were randomly divided into model group， metformin group （positive control， 200 mg/kg） and Yiqi yangyin huazhuo tongluo formula group （32.4 g/kg， calculated as crude drug dosage）， with 10 mice in each group； another 10 mice were set as the control group. Mice were intragastrically administered with corresponding drug solutions or normal saline once a day for 8 consecutive weeks. After the last administration， serum glycolipid metabolism indicators and urinary renal function indicators of mice were determined； the pathological and morphological changes of renal and colonic tissues were observed； LPS contents in renal tissues， colonic contents and serum were detected. 16S rRNA high-throughput sequencing was performed for gut microbiota analysis of colonic contents. The protein expressions of Occludin and zonula occludens-1 （ZO-1） in colonic tissues as well as Caspase-11 and GSDMD in renal tissues were detected.RESULTS Compared with the control group， the model group exhibited significantly elevated levels of serum fasting blood glucose， triglyceride， total cholesterol， serum creatinine， blood urea nitrogen and microalbumin， LPS contents in each sample， as well as protein expressions of Caspase-11 and GSDMD in renal tissues （ P ＜0.05）. The protein expressions of ZO-1 and Occludin in colonic tissues， together with Chao1 and Ace indices of gut microbiota， were markedly decreased （ P ＜0.05）， and the ratio of Firmicutes to Bacteroidetes was abnormally increased. Obvious histopathological changes were observed in renal and colonic tissues； the percentage of PAS-positive area in kidney was markedly increased （ P ＜0.05）. Compared with the model group， the Yiqi yangyin huazhuo tongluo formula group showed remarkable reductions in glycolipid metabolism and renal function-related indicators（except total cholesterol）， LPS contents in various samples， and renal protein expressions of Caspase-11 and GSDMD （ P ＜0.05）. The protein expression level of ZO-1 in colonic tissues and the Ace index of gut microbiota were significantly increased （ P ＜0.05）， and the relative abundance of beneficial genera including Bifidobacterium ， Faecalibaculum and Akkermansia in the gut microbiota was elevated.CONCLUSIONS The mechanism by which Yiqi yangyin huazhuo tongluo formula ameliorates DKD may be related to reshaping gut microbiota， repairing intestinal mucosal barrier， reducing LPS translocation into blood， and further inhibiting Caspase-11/GSDMD-mediated pyroptosis in kidney.

Systemic scleroderma (SSc) is a fibrotic disease involving the skin and a variety of internal organs, which is currently thought to be mainly caused by abnormal activation of fibroblasts and excessive secretion of extracellular matrix. Growing evidence has shown signaling cascades associated with SSc fibrosis, including transforming growth factor-β/Smads, Notch, Wnt/β-catenin, rat sarcoma/extracellular regulated protein kinases, etc. MicroRNAs participate in the post-transcriptional regulation of different target genes and control the cell state, determining the changes in transcriptomes and proteomes caused by various cellular signaling cascades. This review summarizes recent research progress in the regulatory role of microRNAs in SSc fibrosis-related signaling pathways and potential therapeutic targets.

Objective 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.Conclusion YYHT-medicated sera alleviate high glucose-induced injury in MPC5 cells by regulating miR-21a-5p/FoxO1/PINK1-mediated mitochondrial autophagy.

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

Systemic scleroderma (SSc) is a fibrotic disease involving the skin and a variety of internal organs, which is currently thought to be mainly caused by abnormal activation of fibroblasts and excessive secretion of extracellular matrix. Growing evidence has shown signaling cascades associated with SSc fibrosis, including transforming growth factor-β/Smads, Notch, Wnt/β-catenin, rat sarcoma/extracellular regulated protein kinases, etc. MicroRNAs participate in the post-transcriptional regulation of different target genes and control the cell state, determining the changes in transcriptomes and proteomes caused by various cellular signaling cascades. This review summarizes recent research progress in the regulatory role of microRNAs in SSc fibrosis-related signaling pathways and potential therapeutic targets.

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 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 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.