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.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To explore the influencing factors of post-percutaneous coronary intervention(PCI)positivity in young and middle-aged patients with acute myocardial infarction(AMI)and simultaneously assess its mediating effect in the relationship between illness-related shame and psychosocial adjustment.Methods:A total of 178 patients,who admit-ted in Cangzhou People's Hospital between October 2021 and December 2022 for AMI,underwent PCI,and were subse-quently defined as frailty after PCI,were selected.General demographic information survey forms,Patient Activation Measure(PAM),Social Impact Scale(SIS),and Psychosocial Adjustment to Illness Scale Self-Report(PAIS-SR)were applied to investigate the patients.Clinical data characteristics of the patients were analyzed.Pearson correlation analysis was conducted to investigate the association among PAM score,SIS score and PAIS-SR score.Multivariate linear stepwise regression analysis was employed to identify the influencing factors of positivity.The Bootstrap procedure in the Process plugin was used to validate the mediating effect of positivity between illness-related shame and psychosocial adjustment.Results:In this study,PAM score was(57.87±7.02)points,SIS score was(52.07±12.66)points,and PAIS-SR score was(61.07±10.58)points.Pearson correlation analysis indicated that PAM score was significant negatively correlated with SIS score and PAIS-SR score(r=-0.439,-0.504,P＜0.001 all),and SIS score was significant positively corre-lated with PAIS-SR score(r=0.722,P＜0.001).Multivariate linear stepwise regression analysis indicated that male(B=2.226,P=0.020),educational level(B=2.194,P=0.005)and stigma associated with illness(B=-0.210,P＜0.001)can influence the postoperative positivity of patients.Mediation effect analysis indicated that illness-related shame had a direct effect on psychosocial adjustment,accounting for 85.92％of the total effect,while positivity partially media-ted the relationship between illness-related shame and psychosocial adjustment with an effect size of 14.08％.Conclusion:Illness-related shame not only directly affects the psychosocial adjustment in frailty AMI patients after PCI,but also exerts an indirect influence on it through positivity.Medical staff should implement targeted strategies to enhance patients'positiv-ity,thereby reducing the negative impact of illness-related shame on psychosocial adjustment.

Objective:To explore the influencing factors of post-percutaneous coronary intervention(PCI)positivity in young and middle-aged patients with acute myocardial infarction(AMI)and simultaneously assess its mediating effect in the relationship between illness-related shame and psychosocial adjustment.Methods:A total of 178 patients,who admit-ted in Cangzhou People's Hospital between October 2021 and December 2022 for AMI,underwent PCI,and were subse-quently defined as frailty after PCI,were selected.General demographic information survey forms,Patient Activation Measure(PAM),Social Impact Scale(SIS),and Psychosocial Adjustment to Illness Scale Self-Report(PAIS-SR)were applied to investigate the patients.Clinical data characteristics of the patients were analyzed.Pearson correlation analysis was conducted to investigate the association among PAM score,SIS score and PAIS-SR score.Multivariate linear stepwise regression analysis was employed to identify the influencing factors of positivity.The Bootstrap procedure in the Process plugin was used to validate the mediating effect of positivity between illness-related shame and psychosocial adjustment.Results:In this study,PAM score was(57.87±7.02)points,SIS score was(52.07±12.66)points,and PAIS-SR score was(61.07±10.58)points.Pearson correlation analysis indicated that PAM score was significant negatively correlated with SIS score and PAIS-SR score(r=-0.439,-0.504,P＜0.001 all),and SIS score was significant positively corre-lated with PAIS-SR score(r=0.722,P＜0.001).Multivariate linear stepwise regression analysis indicated that male(B=2.226,P=0.020),educational level(B=2.194,P=0.005)and stigma associated with illness(B=-0.210,P＜0.001)can influence the postoperative positivity of patients.Mediation effect analysis indicated that illness-related shame had a direct effect on psychosocial adjustment,accounting for 85.92％of the total effect,while positivity partially media-ted the relationship between illness-related shame and psychosocial adjustment with an effect size of 14.08％.Conclusion:Illness-related shame not only directly affects the psychosocial adjustment in frailty AMI patients after PCI,but also exerts an indirect influence on it through positivity.Medical staff should implement targeted strategies to enhance patients'positiv-ity,thereby reducing the negative impact of illness-related shame on psychosocial adjustment.

Cancer is the main cause of death,and drug therapy has greatly improved the effectiveness of anti-tumor treatment.However,there are problems such as high adverse reactions and the risk of developing drug resistance after long-term use.There is an urgent need to seek new drug targets.Human antigen R(HuR),as an RNA binding protein,promotes the whole process of tumor occurrence,development and metastasis through post transcriptional regulation of mRNA stability,and HuR is general-ly highly expressed in tumor tissue,making it a new target for an-ti-tumor therapy and a standard for prognosis evaluation.Tradi-tional Chinese medicine formulas and their various chemical components can inhibit tumor proliferation,induce tumor cell ap-optosis,inhibit angiogenesis,suppress immune escape,and re-verse tumor drug resistance by regulating HuR activity.This re-view summarizes the importance of HuR in regulation of tumor progression,as well as analyzes the mechanisms of the antitumor effects through active ingredients of Chinese medicine with the regulation of HuR.It is expected to provide new ideas for tumor therapy and guidance for the development of HuR-targeted anti-tumor drugs.

Objective To analyze the application of in-use laparoscopes in clincal departments to enhance the laparoscope's effectiveness.Methods The effective utilization data of 29 laparoscopes from January 2024 to June 2024 were acquired with an hospital intelligent medical device management platform.Comparisons were carried out in terms of average daily workload,average daily hours of use and average daily efficiency between the laparoscopes from different departments and brands with non-parametric Kruskal-Wallis test and between the conventional and 3D laparoscopes with non-parametric Mann-Whitney U test.Pearson's correlation coefficient was used to analyze the correlation between the number of years of laparoscope use and the average daily workload,the average daily hours of use,and the average daily efficiency and the chi-square test was applied to investigating the relationship between the surgery grade and the type of equipment selected.Results Thoracic sugery department had the highest average daily workload(3.82 person-time),while the general medical department had the highest average daily hours of use(443.76 min)and the highest daily efficiency(92.45％).There were significant differences between the laparoscopes from different departments in average daily workload,average daily hours of use and average daily efficiency(P＜0.05).Brand D laparoscope behaved the best among brands of laparoscopes with the highest average daily workload(3.72 person-time),average daily hours of use(394.41 min)and average daily efficiency(82.17％).There were sig-nificant differences between the brands of laparoscopesin average daily workload,average daily hours of use and average daily efficiency(P＜0.05).3D laparoscopes obviously gained advantages over the conventional ones in average daily workload,average daily hours of use and average daily efficiency(P＜0.05).The number of years of use correlated negatively with average daily workload,average daily hours of use and average daily efficiency,with Pearson correlation coefficients being-0.095,-0.039 and-0.039 respectively.Grade Three and Four surgeries had significant differences in types of selected equipment(P＜0.001),and 3D laparoscopes were preferred for Grade Four surgery.Conclusion Utilization analysis of laparoscopes provides data support for optimized application and setup of laparoscopes.[Chinese Medical Equipment Journal,2025,46(2):87-91]

Cyclic GMP-AMP synthase(cGAS)is a congenital immune sensor that can recognize cytoplasm abnormal dsDNA.By catalyzing the second messenger cyclic GMP-AMP(cGAMP)formation,it activates stimulator of interferon genes(STING),releases type Ⅰ interferon and inflammatory cytokines,activates the host immune response,and participates in cerebral ischemia reperfusion injury(CIRI)cascade reaction.This article reviews the research progress of the mechanism of cGAS-STING signaling pathway participation in CIRI,hoping to provide ideas for its treatment.

Objective To carry out quality control testing of anesthesia ventilators to ensure the reliability and safety during their clinical use.Methods Totally 88 anesthesia ventilators used in some hospital underwent quality control testing in terms of tidal volume,peak airway pressure and positive end-expiratory pressure by using a gas flow analyzer according to JJF(E)61-2020 Calibration Specification of Anesthetic Machines,which included 31 ones,36 ones,12 ones and 9 ones respectively from brand A,B,C and D.The Kruskal-Wallis test was used to analyze the variability of the measured values and errors of the performance indicators between different brands of anesthesia ventilators,the chi-square test was applied to discussing the variability of the accuracy class of the performance indicators between different brands of anesthesia ventilators,and the Pearson correlation coefficient was adopted to investigate the correlation between the years of use and the absolute values of the relative errors of the performance indicators.Results The 88 anesthesia ventilators had the overall pass rate for quality control testing being 42.05%,of which,brand B had the highest pass rate(52.78%)and brand C had the lowest pass rate(8.33%).Brand B gained advantages in tidal volume when compared with brand A,C and D,with the differences being significant(P<0.05);brand A behaved the best in peak airway pressure and positive end-expiratory pressure when compared with brand B,C and D,with the differences being significant(P<0.05).Brand A had the highest proportion(63.08%)of distinction and credit in terms of the three performance indicators.The absolute value of the relative error in tidal volume was positively correlated with the years of use at the 3 measurement points for setting values of 400,600,and 800 mL respectively(P<0.05),and there was a significant correlation between the absolute value of the relative error and the years of use at a peak airway pressure setting of 10 cmH2O(1 cmH2O=98.07 Pa)(P<0.05).Conclusion Quality control testing of anesthesia ventilators contributes to finding the risks during their application,which can be an effective tool to ensure the safety of anesthesia ventilators used in medical institutions.[Chinese Medical Equipment Journal,2025,46(9):75-80]

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.