ObjectiveTo investigate the inhibitory effect of gingerol， an active component of ginger， on Staphylococcus aureus （S. aureus） infection， and to preliminarily explore its mechanism related to extracellular vesicles （EVs）. MethodsS.aureus infection models were established in human umbilical vein endothelial cell （HUVECs）， Vero E6 cells， and C57BL/6 mice. Experimental groups included control， infection， and gingerol-treated groups. Bacterial load and VE-cadherin protein expression were detected using immunofluorescence and Western blot. EVs were isolated by size exclusion chromatography and characterized by transmission electron microscopy and nanoparticle tracking analysis. miRNA sequencing was performed on EVs. ResultsGingerol treatment significantly reduced the bacterial load in both in vitro and in vivo infection models and upregulated VE-cadherin expression. miRNA sequencing of EVs revealed that S. aureus infection upregulated the expression of hsa-miR-320c， while gingerol treatment reversed this abnormal expression. Bioinformatic analysis further predicted that the target genes of hsa-miR-320c were significantly enriched in cell junction-related pathways. ConclusionGingerol exhibits clear antibacterial and host-protective effects， by regulating hsa-miR-320c in EVs to maintain endothelial barrier integrity.

Methodological quality assessment is a pivotal link between primary studies and reliable evidence-based practice,and an essential pathway for operationalizing the core principles of the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition).A prevalent challenge in practice,however,is the conflation of appraising methodological robustness(risk of bias assessment)with verifying reporting transparency(adherence to reporting guidelines).This paper systematically addresses this fundamental challenge,beginning with a clear distinction between the essence and boundaries of these two concepts.On this basis,the article provides a comprehensive review of mainstream quality assessment tools,covering the methodological features and evolutionary trajectory of numerous instruments for interventional(e.g.,RoB 2,ROBINS-I),observational(e.g.,NOS,the JBI/SIGN/NIH series),secondary(e.g.,AMSTAR 2),and other specific types of studies such as health economic evaluations.Furthermore,a complete case study is used to illustrate the practical application of the ROBINS-I tool.The paper's central thesis advocates for an"appraisal-informed design"philosophy,urging a conceptual shift from the retrospective critique of existing literature to the prospective quality control of new research by internalizing appraisal standards as design principles,while also exploring the emerging paradigm of artificial intelligence in assisting assessment.This paper provides a comprehensive methodological reference for researchers and practitioners to prudently select appropriate assessment tools and to conduct rigorous critical appraisals of pharmacoepidemiological evidence.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective To determine the diagnostic criteria of quantitative syndrome differentiation of toxin syndrome of diabetic kidney disease.Methods The questionnaire scale was developed through literature research and expert consultation.Points were assigned for the 5 major symptoms in 294 patients with DKD,and according to the TCM syndrome differentiation standard of toxic syndrome syndrome formulated by experts,it is divided into toxic syndrome group and non-toxic syndrome group.The symptom items were screened from the aspects of sensitivity,differentiation and representativeness by statistical method,and the weight value of the items was given by factor analysis.The threshold and the best diagnosis model were determined under the ROC curve.Finally,through the verification group data to verify the scale model,evaluate the diagnostic ability of the scale,and finally construct the diagnostic standard scale model of DKD toxin syndrome.Results 14 symptom items were selected as TCM related symptoms of DKD toxin syndrome,and the diagnostic threshold was determined to be 140.The diagnostic criteria of quantitative syndrome differentiation of DKD toxin syndrome were as follows:total score=fatigue * 10+edema * 10+turbid urine * 10+sore waist and knees * 10+dizziness * 10+tongue purple * 10+dark complexion * 9+limb numbness * 8+loose stools * 7+dry mouth * 4+dry eyes * 4+frequent urination at night * 3+abdominal distension * 3+greasy moss * 3.The degree of each item without this symptom should be multiplied by weight value by 0,mild by weight by 1,moderate by weight by 2,severe by weight by 3,and the total score≥140 could be diagnosed as toxin syndrome.The verification results showed that the sensitivity of the study group was 92.24%,the specificity was 96.19%,the Kappa value was 0.882,and the sensitivity,specificity and Kappa value of the verification group were 87.50%,96.97%and 0.836,respectively.Conclusion The standard scale of DKD toxin syndrome differentiation and diagnosis is constructed,and it has good diagnostic ability,which provides certain application value for clinical and scientific research.

Objective To determine the diagnostic criteria of quantitative syndrome differentiation of toxin syndrome of diabetic kidney disease.Methods The questionnaire scale was developed through literature research and expert consultation.Points were assigned for the 5 major symptoms in 294 patients with DKD,and according to the TCM syndrome differentiation standard of toxic syndrome syndrome formulated by experts,it is divided into toxic syndrome group and non-toxic syndrome group.The symptom items were screened from the aspects of sensitivity,differentiation and representativeness by statistical method,and the weight value of the items was given by factor analysis.The threshold and the best diagnosis model were determined under the ROC curve.Finally,through the verification group data to verify the scale model,evaluate the diagnostic ability of the scale,and finally construct the diagnostic standard scale model of DKD toxin syndrome.Results 14 symptom items were selected as TCM related symptoms of DKD toxin syndrome,and the diagnostic threshold was determined to be 140.The diagnostic criteria of quantitative syndrome differentiation of DKD toxin syndrome were as follows:total score=fatigue * 10+edema * 10+turbid urine * 10+sore waist and knees * 10+dizziness * 10+tongue purple * 10+dark complexion * 9+limb numbness * 8+loose stools * 7+dry mouth * 4+dry eyes * 4+frequent urination at night * 3+abdominal distension * 3+greasy moss * 3.The degree of each item without this symptom should be multiplied by weight value by 0,mild by weight by 1,moderate by weight by 2,severe by weight by 3,and the total score≥140 could be diagnosed as toxin syndrome.The verification results showed that the sensitivity of the study group was 92.24%,the specificity was 96.19%,the Kappa value was 0.882,and the sensitivity,specificity and Kappa value of the verification group were 87.50%,96.97%and 0.836,respectively.Conclusion The standard scale of DKD toxin syndrome differentiation and diagnosis is constructed,and it has good diagnostic ability,which provides certain application value for clinical and scientific research.

Objective:To explore the the possibility and potential mechanism of Coptis chinensis in treating caries based on network pharmacology and molecular docking technology.Methods:The active ingredients of Coptis chinensis and the targets of the active in-gredients and caries were obtained through a variety of databases.The intersection targets of Coptis chinensis and caries were obtained by VENNY.Based on the target of the intersection,the protein-protein interaction(PPI)networks relationship diagram was formed on the STRING platform.The core target diagram was formed through the Cytoscape software,and the Coptis chinensis-active ingre-dient-target network diagram was constructed.The intersection targets are analyzed by GO and KEGG.The core targets of Coptis chinensis active ingredients in treating caries was analyzed by molecular docking.Results:The 11 Coptis chinensis active ingredi-ents,465 targets of Coptis chinensis active ingredients and 1 160 targets of caries were obtained from the database.After analysis,71 targets of Coptis chinensis-caries intersection and 12 core targets were obtained.The potential therapeutic effect of Coptis chinensis on caries involved relaxin,phosphatidylinositol 3-kinase-protein kinase B(PI3K-Akt),mitogen activated protein kinase(MAPK),ras-re-lated protein 1(RAP1)and other signaling pathways.Berberine,one of the main active components of Coptis chinense,had strong binding activity on epidermal growth factor receptor(EGFR),matrix metalloproteinase 9(MMP9)and other core targets.Coptis chinen-sis and its active components can play a role in the treatment of caries through EGFR,MMP9 and PI3K-AKT,MAPK and other path-ways.Conclusion:Coptis chinensis and its active components can regulate several targets and signaling pathways such as EGFR,MMP9,PI3K-AKT and MAPK.Coptis chinensis may play a role in the prevention and treatment of caries through multiple pathways.

Prostate cancer is one of the most common male urological malignancies,in which bone metastasis of desmo-plasia-resistant prostate cancer is an important stage in the progression of the disease,which seriously affects the quality of life and survival of patients.With the development of nuclide therapy technology in recent years,223-Ra,as a new type of alpha-targeted therapy,has shown good efficacy in the treatment of desmoplasia-resistant prostate cancer bone metastasis.The purpose of this pa-per is to review the characteristics,mechanism of action,treatment,and the main research results of its treatment of desmoplasia-resistant prostate cancer bone metastasis,and provide a comprehensive review of the clinical application of 223-Ra in the treatment of desmoplasia-resistant prostate cancer bone metastasis for the clinical application of 223-Ra in prostate cancer bone metastasis.

Methodological quality assessment is a pivotal link between primary studies and reliable evidence-based practice,and an essential pathway for operationalizing the core principles of the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition).A prevalent challenge in practice,however,is the conflation of appraising methodological robustness(risk of bias assessment)with verifying reporting transparency(adherence to reporting guidelines).This paper systematically addresses this fundamental challenge,beginning with a clear distinction between the essence and boundaries of these two concepts.On this basis,the article provides a comprehensive review of mainstream quality assessment tools,covering the methodological features and evolutionary trajectory of numerous instruments for interventional(e.g.,RoB 2,ROBINS-I),observational(e.g.,NOS,the JBI/SIGN/NIH series),secondary(e.g.,AMSTAR 2),and other specific types of studies such as health economic evaluations.Furthermore,a complete case study is used to illustrate the practical application of the ROBINS-I tool.The paper's central thesis advocates for an"appraisal-informed design"philosophy,urging a conceptual shift from the retrospective critique of existing literature to the prospective quality control of new research by internalizing appraisal standards as design principles,while also exploring the emerging paradigm of artificial intelligence in assisting assessment.This paper provides a comprehensive methodological reference for researchers and practitioners to prudently select appropriate assessment tools and to conduct rigorous critical appraisals of pharmacoepidemiological evidence.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To investigate diagnostic value of serum heart type fatty acid-binding protein(H-FABP),cardiac troponin Ⅰ(cTnⅠ)and electrocardiogram(ECG)for acute myocardial infarction(AMI).Methods:A total of 120 patients with chest pain suspected of AMI admitted in Hefei Eighth People's Hospital between March 2018 and March 2020 were enrolled.All patients received ECG and coronary angiography(CAG)examination.According to diagnostic criteria,they were divided into AMI group(n=75)and non-AMI group(n=45);according to Gensini score,AMI patients were divided into mild group(n=34),medium-severe group(n=41);another 120 healthy subjects undergoing physical examination simultaneously were treated as control group.Serum H-FABP and cTnⅠlevels were measured in all groups.Receiver operating characteristic(ROC)curve was drawn to assess diagnostic value of H-FABP,cTnⅠ and ECG and their combination for AMI.Results:With CAG as the gold standard,ECG examination showed that 62 cases were finally diagnosed among the 120 patients with chest pain suspected of AMI,the accuracy,sensitivity and specificity was 69.2％,82.7％,46.7％respectively.Compared with participants in control group,those in non-AMI group and AMI group had significant higher serum H-FABP and cTnⅠ levels,and those of AMI group were significantly higher than those of non-AMI group(P＜0.001 all).Serum levels of in medium-severe group H-FABP[(9.15±1.39)μg/L vs.(7.63±1.25)μg/L]and cTnⅠ[(0.72±0.13)ng/ml vs.(0.41±0.08)ng/ml]were significantly higher than those of mild group(P＜0.001 all).ROC curve analysis indicated that cut-off point of H-FABP and cTnⅠ diagnosing AMI was 7.850μg/L,0.35ng/ml respectively,com-bined detection of ECG(AUC=0.680,95％CI 0.589～0.762),H-FABP(AUC=0.781,95％CI 0.696～0.851)and cTnⅠ(AUC=0.912,95％CI 0.847～0.956)had significant higher diagnostic value(AUC=0.966,95％CI 0.916～0.991)than single diagnosis(Z=6.783,4.499,2.954,P＜0.01 all).Conclusion:Serum H-FABP and cTnⅠ were associated with the degree of coronary lesions in AMI patients,and the combination of serum H-FABP,cTnⅠ and ECG had good diagnostic value for AMI.