ObjectiveTo observe the clinical efficacy of Sanren Runchang formula in treating constipation-predominant irritable bowel syndrome （IBS-C） by regulating the brain-gut axis and the effects of the formula on serum levels of 5-hydroxytryptamine （5-HT）， vasoactive intestinal peptide （VIP）， and substance P （SP）. MethodsA randomized controlled design was adopted， and 72 IBS-C patients meeting Rome Ⅳ criteria were randomized into observation and control groups （36 cases）.The observation group received Sanren Runchang formula granules twice daily， and the control group received lactulose oral solution daily for 4 weeks. IBS Symptom Severity Scale （IBS-SSS）， IBS Quality of Life Scale （IBS-QOL）， and Bristol Stool Form Scale （BSFS） were used to assess clinical symptoms， and bowel movement frequency was recorded. The Self-Rating Anxiety Scale （SAS） and Self-Rating Depression Scale （SDS） were employed to evaluate psychological status. ELISA was employed to measure the serum levels of 5-HT， VIP， and SP. ResultsThe total response rate in the observation group was 91.67% （33/36）， which was higher than that （77.78%， 28/36） in the control group （χ²=4.50， P<0.05）. After treatment， both groups showed increased defecation frequency and BSFS scores， decreased IBS-SSS total score， abdominal pain and bloating scores， IBS-QOL health anxiety， anxiety， food avoidance， and behavioral disorders scores， SAS and SDS scores， serum 5-HT and VIP levels， and increased SP levels （P<0.05， P<0.01）. Moreover， the observation group showed more significant changes in the indicators above than the control group （P<0.05， P<0.01）. The SP level showed no significant difference between the two groups. During the 4-week follow-up， the recurrence rate was 5.88% in the observation group and 31.25% in the control group. No adverse events occurred in observation group， and 2 cases of mild diarrhea occurred in the control group. ConclusionSanren Runchang formula demonstrated definitive efficacy in alleviating gastrointestinal symptoms and improving the psychological status and quality of life in IBS-C patients， with a low recurrence rate. The formula can regulate serum levels of neurotransmitters such as 5-HT and VIP， suggesting its potential regulatory effect on the brain-gut axis through modulating neurotransmitters and neuropeptides. However， its complete mechanism of action requires further investigation through detection of additional brain-gut axis-related biomarkers.

ObjectiveTo explore the sequential effects of hypoxic exercising on miR-27/PPARγ and lipid metabolism target gene and protein expression levels in the obesity rats’ liver. Methods13-week-old male diet-induced obesity rats were randomly divided into three groups (n＝10): normal oxygen concentration quiet group (N), hypoxia quiet group (H), hypoxic exercise group (HE). Exercise training on the horizontal animal treadmill for 1 h/d, 5 d/week for a total of 4 week, and the intensity of horizontal treadmill training was 20 m/min (hypoxic concentration was 13.6%). Comparison of the weights of perirenal fat and epididymal fat in rats across different groups and calculation of Lee’s index based on body weight and body length of rats in each group were done. And the serum concentrations of total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) levels were detected. RT-PCR and Western Blot were used to detect the levels of miR-27, PPARγ, CYP7A1 and CD36. ResultsHypoxic exercise decreased the expression levels of miR-27 in the obese rats’ liver, however, the expression level of PPARγ was gradually increased. The expression levels of miR-27 in HE group were significantly lower than N group (P<0.05). The expression levels of PPARγ mRNA in N group were significantly lower than H group (P<0.05), especially lower than HE group (P<0.01). The protein expression of PPARγ protein in N group was significantly lower than that other groups (P<0.01). The expression of lipid metabolism-related genes and proteins increased in the obese rats’ liver. The expression of CYP7A1 mRNA in N group was significantly lower than H group (P<0.05), especially lower than HE group (P<0.01). The expression of CYP7A1 protein in the obese rats’ liver in N group was extremely lower than H group and HE group (P<0.01). The protein expression of CD36 in N group was significantly lower than that in HE group (P<0.05). Hypoxia exercise improved the related physiological and biochemical indexes of lipid metabolism disorder. The perirenal fat weight of obese rats in HE group was extremely lower than N group and H group (P<0.01), and the perirenal fat weight in N group was significantly higher than H group (P<0.05). The epididymal fat weight in N group was significantly higher than H group (P<0.05), and extremely higher than HE group (P<0.01). The Lee’s index in HE group was extremely lower than N group and H group (P<0.01). The serum concentration of TC in obese rats in HE group was extremely lower than N group and H group (P<0.01). The serum concentration of TG in HE group was extremely lower than N group and H group (P<0.01). The serum concentration of LDL-C in N group was extremely higher than HE group (P<0.01). The serum concentration of HDL-C in N group was extremely lower than H group (P<0.01). ConclusionHypoxia and hypoxia exercise may negatively regulate the levels of PPARγ by inhibiting miR-27 in the obese rats’ liver, thereby affecting the expression of downstream target genes CYP7A1 and CD36, and promoting cholesterol, fatty acid oxidation and HDL-C transport in the liver, and ultimately the lipid levels in obese rats were improved. The effect of hypoxia exercise on improving blood lipid is better than simple hypoxia intervention.

Aim To investigate the regulatory mecha-nisms of donepezil on the expression and enzymatic ac-tivity of cytochrome P450 3A4(CYP3A4),elucidate the synergistic impact of hypoxia on CYP3A4 function,and reveal its potential association with drug-induced cardiotoxicity,particularly QT interval prolongation.Methods Western blot,co-immunoprecipitation,and gene knockdown techniques were employed to evaluate the effects of donepezil and hypoxia on CYP3A4 pro-tein expression.CYP3A4 enzymatic activity was as-sessed using an in vitro incubation system with rat liver microsomes combined with high-performance liquid chromatography(HPLC),and the half-maximal inhib-itory concentration(IC50)was determined.Results Donepezil(10 μmol·L-1)and hypoxia reduced CYP3A4 protein expression to 31.75％and 45.90％of the control levels,respectively.Both interventions activated the gp78-mediated ubiquitin-proteasome path-way,significantly increasing CYP3A4 ubiquitination levels by 2.1-fold compared to the control group,thereby promoting proteasomal degradation.Donepezil inhibited CYP3A4 enzyme activity with an IC50 of 83.4μmol·L-1,and hypoxia synergistically enhanced this inhibitory effect,reducing the IC50 to 20.79 μmol·L-1.Conclusion Donepezil downregulates CYP3A4 function through dual mechanisms involving ubiquitin-mediated proteasomal degradation and direct enzymatic inhibition.Hypoxia potentiates this effect,leading to impaired metabolism of CYP3A4 substrate drugs,ele-vated plasma drug concentrations(1.6-2.3-fold in-crease compared to normal metabolic conditions),and an increased risk of QT interval prolongation and other forms of cardiotoxicity.

The high incidence of peristoma moisture-related skin injury in patients with enterostomies seriously reduces patients′ quality of life. This paper reviewed the risk factors and risk prediction models for peristoma moisture-related skin injury, with the aim of providing an important basis for early identification and intervention in the high-risk group of peristoma moisture-related skin injury after clinical stoma surgery, and then providing a reference for the personalised health management of patients with intestinal stoma.

Objective:To analyze the clinical and ultrasonographic characteristics of papillary thyroid carcinoma(PTC)and explore their correlation with cervical lymph node metastasis(CLNM),thereby constructing a nomogram pre-diction model for assessing the risk of CLNM in PTC.Methods:A total of 553 patients(corresponding to 553 nod-ules)with papillary thyroid carcinoma(PTC),confirmed by postoperative pathology,who underwent ultrasonography and had complete clinical data at the Second Hospital of Shandong University between December 2019 and December 2022,were included.228 patients(228 nodules)hadcervical lymph node metastasis,and 325 patients(325 nodules)were without cervical lymph node metastasis.All patients were categorized into metastasis and non-metastasis groups based on the presence or absence of cervical lymph node metastasis.These groups were then randomly di-vided into training and validation sets in a 7:3 ratio.Differences in clinical and ultrasonographic characteristics between the two groups were compared,and a nomogram was constructed.Results:Univariate analysis revealed statistically significant differences between the metastasis group and the non-metastasis group in terms of age,presence of Hashimoto's thyroiditis,multifocality,taller-than-wide shape,calcification,capsular contact,and blood flow(P<0.05).Logistic regression analysis in the training set indicated that age,presence of Hashimoto's thyroiditis,multifocality,taller-than-wide shape,calcification,and blood flow were associated with lymph node metastasis in papillary thyroid carcinoma(PTC)(P<0.05).These indicators were incorporated into a nomogram model,which demonstrated high predictive performance,good calibration,and significant clinical utility in both the training and validation sets.Conclu-sion:The nomogram prediction model,constructed based on clinical and ultrasonographic features,effectively predicts the risk of cervical lymph node metastasis(CLNM)in patients with papillary thyroid carcinoma(PTC).Patients who were older,had concomitant Hashimoto's thyroiditis,or exhibited a nodule aspect ratio≥1 were less likely to have concurrent CLNM.Conversely,patients presenting with multiple nodules,nodules with microcalcifications,or nodules demonstrating central or rich/peripheral vascularity were more likely to have concurrent CLNM.

Objective To develop and validate a machine learning-based predictive model to assess the in-hospital mortality risk of patients with myocardial infarction(MI)complicated by heart failure(HF)undergoing percutaneous coronary intervention(PCI).Methods This retrospective study analyzed MI patients with HF who underwent PCI at The First Affiliated Hospital of Xinjiang Medical University from January 2019 to January 2023.Patient data,including demographic characteristics,vital signs,laboratory test results,imaging parameters and medication use,were collected and randomly divided into a training set(70％)and a validation set(30％).The extreme gradient boosting(XGBoost)model was used to identify variables significantly associated with in-hospital mortality,and the Shapley additive explanations(SHAP)model was applied to assess feature importance.A predictive model was then constructed using univariate and multivariate Logistic regression analyses.Model performance was evaluated using receiver operating characteristic(ROC)curves,area under the curve(AUC)values,calibration curves,and decision curve analysis.Finally,a nomogram was developed for intuitive risk assessment.Results A total of 1 214 MI patients with HF were included in the study,with a median age of 64 years.The in-hospital mortality rate was 7.41％(90 deaths).XGBoost feature selection identified ten key predictive variables:age,myoglobin,albumin,fasting blood glucose,N-terminal pro-B-type natriuretic peptide(NT-proBNP),diabetes mellitus,creatinine,cystatin C,procalcitonin,and left ventricular ejection fraction.Based on these variables,a Logistic regression model was developed,with seven final predictors:age,diabetes mellitus,creatinine,fasting blood glucose,cystatin C,NT-proBNP,and albumin.The model demonstrated high predictive accuracy,with AUC value of 0.869(95％CI:0.84-0.89)in the training set and 0.827(95％CI:0.79-0.85)in the validation set.The calibration curve indicated that the predicted probabilities were consistent with the actual observed outcomes,and decision curve analysis showed that the model had a high net benefit across various decision thresholds.Conclusion This study developed a machine learning-based predictive model incorporating Logistic regression to assess the in-hospital mortality risk of MI patients with HF undergoing PCI.The model demonstrated high predictive performance and clinical utility.The nomogram derived from this model provides an intuitive tool for individualized risk assessment,aiding clinicians in the early identification of high-risk patients,optimizing intervention strategies,and improving patient outcomes.

Objective To construct and validate machine learning-based models to predict the risk of acute kidney injury(AKI)following percutaneous coronary intervention(PCI)in patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 2 315 STEMI patients who underwent PCI between January 2020 and June 2023 were included;306(13.2％)of them developed AKI.Baseline variables were screened using LASSO regression,with the optimal λ value selected via 10-fold cross-validation to identify AKI-associated features.Subsequently,eight distinct machine learning models were constructed and evaluated for their predictive performance.SHAP value analysis was employed to assess the impact of key variables on model predictions.Results LASSO regression identified seven variables significantly associated with AKI,including age,multivessel disease,preoperative creatinine,heart failure,white blood cell count,hemoglobin,and albumin levels.Among all the models,the light gradient boosting machine(LGBM)and extreme gradient boosting(XGB)demonstrated the best predictive performance,with training set AUCs being 0.899(95％CI:0.877-0.921)and 0.893(95％CI:0.868-0.918),and validation set AUCs being 0.809(95％CI:0.763-0.856)and 0.871(95％CI:0.833-0.909),respectively.SHAP analysis revealed that albumin,age,preoperative creatinine,and white blood cell count were the primary contributors to AKI risk.Conclusion This study successfully developed and validated machine learning-based predictive models capable of effectively identifying the risk of AKI following PCI in STEMI patients,thus providing valuable support for clinical decision-making.

Objective This study aimed to examine the risk factors and prognostic factors of brucellar spondylitis for early prevention and treatment of the disease,and improving the outcomes of patients.Methods A retrospective case-control study was conducted on the patients with brucellosis who were hospitalized in the Third Hospital of Hebei Medical University from June 2020 to June 2022.Patients were assigned to brucellosis without spondylitis group or brucellar spondylitis group according to the presence of spondylitis.The patients in brucellar spondylitis group were followed for 1 year.Then they were stratified into a subgroup of good or poor prognosis according to clinical outcomes.The dataset for the demographic and clinical variables of patients were analyzed using SPSS 26.0 software.Results A total of 300 patients with brucellosis were enrolled,including 113 cases of brucellosis without spondylitis and 187 cases of brucellar spondylitis.Multivariate analysis showed that age,time from onset to diagnosis,low back pain,and erythrocyte sedimentation rate were independent risk factors for brucellar spondylitis(P＜0.05).Of the 154 cases of brucellar spondylitis with known outcomes,121 cases showed good prognosis and 33 cases had poor prognosis.COX regression analysis showed that the time from onset to diagnosis,diabetes mellitus,paravertebral abscess,and neurological impairment were independent risk factors for poor prognosis in patients with brucellar spondylitis(P＜0.05).Conclusions Old age,prolonged time from onset to diagnosis,low back pain,and increased erythrocyte sedimentation rate are independent risk factors for spondylitis in patients with brucellosis.Prolonged time from onset to diagnosis,diabetes mellitus,paravertebral abscess,and neurological impairment are independent risk factors for poor prognosis of brucellar spondylitis.

Objective:To analyze the key factors in quality control for clinical laboratory instrument by constructing an analysis framework of the model that entropy weight method(EWM)combines with decision laboratory analysis(DEMATEL),so as to obtain the key factors of quality control for clinical laboratory instrument,and provide a basis in formulating targeted quality control strategies for clinical laboratory instruments.Methods:Based on EWM,the entropy weight values of various factors of quality control for clinical laboratory instruments that produced influence on quality control for clinical laboratory instruments were obtained,and the DEMATEL was combined to determine the value of influence degree among different factors.The combined weight values of each factor were calculated to construct the analysis framework of the model that EWM combined with DEMATEL.Then,the main influencing factors were determined to formulate the model of management system of quality control for clinical laboratory instruments.Results:The management system of quality control for clinical laboratory instruments included 23 key factors of 5 aspects:performance and design of instruments,operators'training and skills,environmental factors,maintenance management,and mechanism of quality feedback.The combined weights of 10 factors,which included maintenance for instrument,operators'experience and proficiency,repair for instrument,operators'understanding for instrument performance,accuracy of instrument,mechanism of quality control and continuous feedback,stability of instrument,data security,suggestions of analyzing and optimizing data,and calibration for instrument,has a relatively high weight,and they were extremely key factors in the quality control for clinical laboratory instruments.Conclusion:The analysis framework of EWM combined with DEMATEL model can improve the accuracy and reliability of analyzing key factors of quality control for clinical laboratory instrument,and provide scientific basis in formulating targeted quality control strategies for clinical laboratory instrument,and help to promote continuous improvement and enhancement of quality control for clinical laboratory instrument.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.