Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease mediated by T lymphocytes， and it can progress to liver cirrhosis or even liver failure without timely intervention. As a natural flavonoid compound， naringenin （NAR） shows a potential value in the prevention and treatment of AIH through multiple mechanisms such as remodeling immune homeostasis， targeted inhibition of inflammatory pathways， antioxidation， regulating hepatocyte metabolism and apoptosis， improving mitochondrial function， and regulating intestinal flora. However， the clinical translation and application of NAR is limited by issues such as low bioavailability and insufficient efficiency of liver-targeted delivery. This article systematically reviews the mechanism of action of NAR in the prevention and treatment of AIH， explores the potential signaling pathways involved in this process， and analyzes existing challenges in its translation and application and future research directions， so as to provide a reference for further research on NAR and its application in the prevention and treatment of AIH.

Objective This study aims to develop an early in-hospital temperature management protocol for heat stroke patients and assess its effectiveness,providing guidance for rapid cooling and precise target temperature control.Methods The protocol was developed through a Delphi expert consultation combined with expert panel meetings.A multi-center,non-randomized,historical control study was conducted,utilizing convenience sampling to select heat stroke patients from the emergency departments of 7 tertiary hospitals in Zhejiang Province,China,between June and August 2024 as an experimental group.The protocol was implemented in this group,while the control group consisted of heat stroke patients treated between June and August 2022,prior to protocol implementation.Cooling rates,target temperature attainment rates,and clinical outcomes were compared between the 2 groups.Results The final protocol included 6 primary indicators,23 secondary indicators,and 56 tertiary indicators.After protocol implementation,the experimental group achieved a cooling rate of 0.08(0.05～0.09)℃/min within 0.5 hours,significantly higher than the control group,which had a rate of 0.04(0.02～0.06)℃/min(P＜0.001).The target temperature attainment rates at 0.5 hours and 2.0 hours were 55.93％and 98.31％,respectively,significantly higher than the rates of 15.87％and 61.11％in the control group(P＜0.001).The mechanical ventilation rate,hospitalization rate,ICU admission rate,and mortality rate in the experimental group were 25.42％,61.02％,44.07％,and 8.47％,respectively.Logistic regression analysis revealed that the early in-hospital temperature management protocol significantly reduced the risk of mechanical ventilation and hospitalization in heat stroke patients,with odds ratios(ORs)of 0.294 and 0.300,respectively(both P＜0.05).Conclusion The developed protocol for early in-hospital temperature management in heat stroke patients is scientific,systematic,and practical.It improves cooling rates and target temperature attainment,thereby enhancing the prognosis of heat stroke patients.

Background and purpose:Breast cancer stem cells play an important role in the occurrence and development of cancer.The high mortality of breast cancer patients is closely related to the recurrence and metastasis of cancer.However,the self-renewal and differentiation ability of breast cancer stem cells can lead to chemotherapy resistance,thus affecting the recurrence and metastasis of cancer.This study aimed to explore the impact of miR-193a-3p on the migration and invasion of breast cancer stem cells by targeting the tripartite motif-containing protein 14(TRIM14).Methods:Human breast cancer cell T47D was randomly assigned into control group,NC mimics group(transfected with NC mimics),miR-193a-3p mimics group(transfected with miR-193a-3p mimics),miR-193a-3p mimics+pcDNA-NC group(transfected with miR-193a-3p mimics+pcDNA-NC)and miR-193a-3p mimics+pcDNA-TRIM14 group(transfected with miR-193a-3p mimics+pcDNA-TRIM14).Separation of stem cells using flow cytometry and detection of cell spheroidization ability were carried out.Cell counting kit-8(CCK-8)experiment was used to detect cell proliferation.Transwell experiment was used to measure cell migration and invasion.Flow cytometry was used to detect cell apoptotic rate.Western blot was used to detect the expressions of cyclin D1,matrix metalloproteinase-2(MMP-2),Bcl-2-associated X protein(Bax),and TRIM14 protein in cells.Dual luciferase assay was used to detect the interaction between miR-193a-3p and TRIM14.Results:T47D stem cells had the ability to form spheroids,and with increasing time,the spheroid volume of T47D stem cells gradually increased.Compared with the Control group and NC mimics group,the miR-193a-3p mimics group showed increased miR-193a-3p expression,apoptotic rate,and Bax protein expression(P＜0.05),and decreased TRIM14 mRNA and protein expression,survival rate,clone number,migration number,invasion number,cyclin D1 and MMP-2(P＜0.05).Compared with the miR-193a-3p mimics group and the miR-193a-3p mimics+pcDNA NC group,the miR-193a-3p mimics+pcDNA-TRIM14 group showed decreased cell apoptosis rate and Bax protein(P＜0.05),and increased TRIM14 mRNA and protein expression,survival rate,clone number,migration number,invasion number,cyclin D1 and MMP-2(P＜0.05).There were multiple binding sites between miR-193a-3p and TRIM14.Compared with the miR-NC+TRIM14-WT group,the miR-193a-3p mimics+TRIM14-WT group showed a prominent decrease in dual luciferase activity(P＜0.05).Conclusion:MiR-193a-3p may inhibit the migration and invasion of breast cancer stem cells through inhibiting TRIM14.

Objective To investigate the gene expression profile in rat pancreatic ductal stem cells(PDSCs)when induced to differentiate into insulin-secreting cells(IPCs),with the goal of identifying key genes involved in this differentiation process.Methods The expanded PDSCs were categorized into a normal control(NC)group and an induced(Tre)group.PDSCs continued expansion culture in NC group,and cultured in induction medium for 28 days to facilitate the differentiation of PDSCs into IPCs in Tre group.Dithizone staining was employed to morphologically assess whether the cells exhibited a reddish-brown coloration,indicating a positive result.The immunofluorescence staining method was used to detect the expression of insulin(Ins)and PDX1 in the cells following induction.Additionally,ELISA was conducted to measure the Ins release from IPCs,thereby verifying the responsiveness of the induced cells to glucose-stimulated Ins secretion.Concurrently,cells were collected on induction days 0 and 28 for RNA sequencing(RNA-seq),and differentially expressed genes(DEGs)were analyzed and functionally annotated.The analysis revealed that regulatory factor X3(RFX3)was overexpressed in PDSCs,and the impact of RFX3 upregulation on differentiation induction was subsequently verified.Results Compared with NC group,DTZ staining was positive,PDX1 and Ins proteins were expressed,and an increased release of Ins in response to sugar stimulation was demonstrated in the Tre group.RNA-seq analysis identified 4270 DEGs,and functional enrichment analysis utilizing the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases revealed associations with Ins response,positive regulation of Ins secretion,pancreatic endocrine cell development,and overall pancreatic development.Additionally,functionally related genes such as ALDHA2,CREB5,EIF6,FOXO1,RFX3,WNT5a,OGT,GPR39,SMAD6,and TRPM2 were identified,indicating involvement in the cell cycle,TGF-β1 signaling pathway,FOXO signaling pathway,and Wnt signaling pathway in the regulation of the differentiation of pancreatic ductal stem cells(PDSCs)into insulin-producing cells(IPCs).Furthermore,the upregulation of RFX3 can inhibit the expression of TGF-β1 within 72 hours,thereby promoted the formation and release of Ins from insulin-positive cells.Conclusions Multiple genes and signaling pathways associated with pancreatic β-cell function collectively regulate the differentiation of rat PDSCs into IPCs.Notably,the upregulation of RFX3 enhances this differentiation process.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Purpose To explore the value of contrast-enhanced CT habitat imaging(HI)in preoperative non-invasive visualization for predicting pathological grading of clear cell renal carcinoma(ccRCC).Materials and Methods A retrospective analysis was conducted on enhanced CT images and clinical data from 240 patients with pathologically confirmed ccRCC at Xijing Hospital,the Fourth Military Medical University from January 2020 to December 2023.All patients were randomly divided into training and test sets at a 7:3 ratio and classified into low-grade group(International Society of Urological Pathology Ⅰ-Ⅱ)and high-grade group(International Society of Urological Pathology Ⅲ-Ⅳ)based on postoperative pathology.Using wash-in and wash-out parametric maps,the tumors were segmented into three perfusion-based habitat subregions(low,medium and high)via K-means clustering,and the volume fraction of each subregion was calculated.Predictive factors were selected from habitat features and clinical variables(including sex,age,tumor size,etc.)using Logistic regression.Three models were constructed:a clinical model,a habitat imaging model and a combined clinical-habitat model.Model performance was evaluated using receiver operating characteristic curve,calibration curve and decision curve analysis.Results Habitat 3 exhibited higher wash-in and wash-out gradients compared to Habitats 1 and 2,indicating hyper perfusion.Its proportion was significantly higher in the low-grade group than in the high-grade group(Z=-7.71,-5.11,both P<0.01).Multivariate Logistic regression identified hypertension,maximum tumor diameter and platelet-to-lymphocyte ratio as independent risk factors for high-grade ccRCC,while the proportion of Habitat 3 was a protective factor(OR=0.297,95％CI 0.184-0.479).The combined clinical-habitat model demonstrated the highest predictive performance[area under the curve(AUC)=0.938],significantly outperforming the clinical model(AUC=0.801,Z=-3.832,P<0.01)and the habitat imaging model(AUC=0.895,Z=-2.157,P=0.031).Conclusion The clinical-habitat imaging model achieves the highest predictive performance for ccRCC pathological grading.Contrast-enhanced CT habitat imaging provides significant incremental value in predicting ccRCC pathological grading,showing potential to guide precision medicine in clinical practice.

Objective:To explore the value of non-invasive habitat imaging (HI) multi-parametric MRI (mpMRI) in predicting the risk of prostate cancer (PCa).Methods:In this cross-sectional study, 220 patients with PCa confirmed by radical prostatectomy (RP) who underwent multi-parametric MRI (mpMRI) scanning at Xijing Hospital, Air Force Military Medical University from January 2018 to May 2024 were retrospectively collected. Patients were divided into a training set (154 cases) and a test set (66 cases) by simple random sampling in a 7∶3 ratio. Based on mpMRI imaging, the apparent diffusion coefficient (ADC), perfusion fraction (f), and mean kurtosis (MK) of each voxel were integrated. The K-means clustering algorithm was used to divide the PCa target lesions into habitat subregions, generate habitat maps, and calculate the proportion of each habitat subregion in the entire lesion. According to the 2019 International Society of Urological Pathology (ISUP) guidelines, patients were categorized into a low-risk group (ISUP≤2, 65 cases) and a high-risk group (ISUP≥3, 155 cases). The RP specimens were matched with the habitat map to identify corresponding habitat subregions, and the ISUP grade of each subregion was individually evaluated to calculate the detection rate of high-risk PCa patients. The logistic regression analysis was applied to identify the independent risk factors associated with PCa risk, and the HI-clinical imaging model and clinical imaging model were constructed. The efficacy of the models was assessed using receiver operating characteristic curve.Results:Based on the optimal cluster number, the habitat was divided into three subregions. Habitat 1 had lower ADC and f values and higher MK values, while habitat 2 had the opposite characteristics, and habitat 3 was intermediate. The proportion of habitat 1 in the high-risk group was 28.8%, in the low-risk group was 8.9%. In the training set, the comparison of habitat subregions with pathological results showed that the detection rate of high-risk lesions was 66.9% (103/154) in habitat 1, 25.3% (39/154) in habitat 2, and 47.4% (73/154) in habitat 3. The logistic regression analysis indicated that the proportion of habitat 1 ( OR=3.03, 95% CI 1.77-5.18, P<0.001), prostate-specific antigen ( OR=1.66, 95% CI 1.04-2.66, P=0.034), and the prostate imaging reporting and data system score ( OR=1.65, 95% CI 1.00-2.70, P=0.048) as independent risk factors for high-risk PCa. In the training set, the area under the curve (AUC) for predicting PCa risk was 0.854 (95% CI 0.789-0.920) for the HI-clinical imaging model and 0.779 (95% CI 0.701-0.856) for the clinical imaging model. In the test set, the AUC values were 0.809 (95% CI 0.693-0.895) and 0.738 (95% CI 0.619-0.856), respectively. Conclusion:HI based on mpMRI can effectively predict the risk of PCa.

Objective This study aims to develop an early in-hospital temperature management protocol for heat stroke patients and assess its effectiveness,providing guidance for rapid cooling and precise target temperature control.Methods The protocol was developed through a Delphi expert consultation combined with expert panel meetings.A multi-center,non-randomized,historical control study was conducted,utilizing convenience sampling to select heat stroke patients from the emergency departments of 7 tertiary hospitals in Zhejiang Province,China,between June and August 2024 as an experimental group.The protocol was implemented in this group,while the control group consisted of heat stroke patients treated between June and August 2022,prior to protocol implementation.Cooling rates,target temperature attainment rates,and clinical outcomes were compared between the 2 groups.Results The final protocol included 6 primary indicators,23 secondary indicators,and 56 tertiary indicators.After protocol implementation,the experimental group achieved a cooling rate of 0.08(0.05～0.09)℃/min within 0.5 hours,significantly higher than the control group,which had a rate of 0.04(0.02～0.06)℃/min(P＜0.001).The target temperature attainment rates at 0.5 hours and 2.0 hours were 55.93％and 98.31％,respectively,significantly higher than the rates of 15.87％and 61.11％in the control group(P＜0.001).The mechanical ventilation rate,hospitalization rate,ICU admission rate,and mortality rate in the experimental group were 25.42％,61.02％,44.07％,and 8.47％,respectively.Logistic regression analysis revealed that the early in-hospital temperature management protocol significantly reduced the risk of mechanical ventilation and hospitalization in heat stroke patients,with odds ratios(ORs)of 0.294 and 0.300,respectively(both P＜0.05).Conclusion The developed protocol for early in-hospital temperature management in heat stroke patients is scientific,systematic,and practical.It improves cooling rates and target temperature attainment,thereby enhancing the prognosis of heat stroke patients.

The study aims to explore the herb-drug interaction between Xuefu Zhuyu Decoction(XFZY) and atorvastatin(AT). Reverse transcription polymerase chain reaction(RT-PCR) was used to analyze the transcription levels of proteins related to drug metabolism and transport in LS174T cells, detect the intracellular drug uptake under various substrate concentrations and incubation time, and optimize the model reaction conditions of transporter multidrug resistance protein 1(MDR1)-specific probe Rhodamine 123 and AT to establish a cell model for investigating the human intestinal drug interaction. The cell counting kit-8(CCK-8) method was adopted to evaluate the cytotoxicity of XFZY on LS174T cells. After a single and continuous 48 h culture with XFZY, AT or Rhodamine 123 was added for co-incubation. The effect and mechanism of XFZY on human intestinal absorption of AT were analyzed by measuring the intracellular drug concentrations and transcription levels of related transporters and metabolic enzymes. The results of in vitro experiments show that a single co-culture with a high concentration of XFZY significantly increases the intracellular concentrations of Rhodamine 123 and AT. A high concentration of XFZY co-culture for 48 h increases the AT uptake level, significantly induces the CYP3A4 and UGT1A1 gene expression levels, and inhibits the OATP2B1 gene expression level. To compare with the evaluation results of the in vitro human cell model, the pharmacokinetic experiment of XFZY combined with AT was carried out in rats. Sprague-Dawley(SD) rats were randomly divided into a blank control group and an XFZY group. After 14 days of continuous intragastric administration, AT was given in combination. The liquid chromatography-mass spectrometry(LC-MS)/MS method was used to detect the concentrations of AT and metabolites 2-hydroxyatorvastatin acid(2-HAT), 4-hydroxyatorvastatin acid(4-HAT), atorvastatin lactone(ATL), 2-hydroxyatorvastatin lactone(2-HATL), and 4-hydroxyatorvastatin lactone(4-HATL) in plasma samples, and the pharmacokinetic parameters were calculated. Pharmacokinetic analysis in rats shows that continuous administration of XFZY does not significantly change the pharmacokinetic characteristics of AT in rats, but the AUC_(0-6 h) values of AT and metabolites 2-HAT, 4-HAT, and 2-HATL increase by 21.37%, 14.94%, 12.42%, and 6.68%, respectively. The metabolic rate of the main metabolites shows a downward trend. The study indicates that administration combined with XFZY can significantly increase the uptake level of AT in human intestinal cells and increase the exposure level of AT and main metabolites in rats to varying degrees. The mechanism may be mainly due to the inhibition of intestinal MDR1 transport activity.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Atorvastatin/administration & dosage* ; Humans ; Rats ; Rats, Sprague-Dawley ; Male ; Intestines/cytology* ; Intestinal Mucosa/metabolism* ; Herb-Drug Interactions ; Cytochrome P-450 CYP3A/metabolism* ; Intestinal Absorption/drug effects*

Mesangial cell proliferation is an early pathological indicator of diabetic nephropathy (DN). Growing evidence highlights the pivotal role of paired-related homeobox 1 (Prrx1), a key regulator of cellular proliferation and tissue differentiation, in various disease pathogenesis. Notably, Prrx1 is highly expressed in mesangial cells under DN conditions. Both in vitro and in vivo studies have demonstrated that Prrx1 overexpression promotes mesangial cell proliferation and contributes to renal fibrosis in db/m mice. Conversely, Prrx1 knockdown markedly suppresses hyperglycemia-induced mesangial cell proliferation and mitigates renal fibrosis in db/db mice. Mechanistically, Prrx1 directly interacts with the Yes-associated protein 1 (YAP) promoter, leading to the upregulation of YAP expression. This upregulation promotes mesangial cell proliferation and exacerbates renal fibrosis. These findings emphasize the crucial role of Prrx1 upregulation in high glucose-induced mesangial cell proliferation, ultimately leading to renal fibrosis in DN. Therefore, targeting Prrx1 to downregulate its expression presents a promising therapeutic strategy for treating renal fibrosis associated with DN.