Objective:To summarize the practical experience of constructing an intelligent quality control system for electronic medical record (EMR) in clinical trials, providing reference for continuously improving the quality of clinical trials.Methods:Quality control rules for clinical trial EMR were established, and an intelligent quality control platform was developed to enable dynamic monitoring, interception, early warning, and evaluation. A hybrid quality control system integrating real-time and terminal quality control was constructed, alongside a three-dimensional linkage mechanism encompassing training, quality control, and evaluation.Results:Through the extensive application of information technology and the implementation of a multi-level quality control network, a quality control loop characterized by ″Efficient machine screening and precise human decision-making″ was achieved to enhance management quality and efficiency. However, challenges such as the standardization of quality control rules, data security and privacy protection, and system interface heterogeneity were persistent.Conclusions:The development of an intelligent quality control system for clinical trial EMR represents a critical step in advancing clinical trial quality management. Nevertheless, ongoing optimization of technical solutions is essential to address existing challenges and further improve system performance.

Objective To construct and validate a predictive model for gastric precancerous le-sions based on urea breath test,serum pepsinogen(PG)and gastrin-17(G-17).Methods Partici-pants who underwent endoscopic screening for upper gastrointestinal tumors were retrospectively en-rolled as study subjects.Using random function,all participants were divided into training cohort of 2,788 cases(comprising 1,290 cases in precancerous lesion group and 1,498 cases in control group)and validation cohort of 1,194 cases(comprising 581 cases in precancerous lesion group and 613 cases in control group)at a ratio of 7 to 3.A simple model was established based on urea breath test,PG and G-17.Clinical data between the precancerous lesion group and the control group in the training cohort were compared.A predictive model for gastric precancerous lesions was constructed u-sing multifactorial Logistic regression analysis,and a scoring model for gastric precancerous lesions(the complete model)was developed based on this predictive model.The complete model,the simple model,the new ABC method,and the Li's score were all included in the validation cohort to compare the predictive performance of the four models.Results Multifactorial Logistic regression analysis indicated that male,smoking,positive Helicobacter pylori(Hp)infection,PG Ⅱ ≥10.19 μg/L,the ratio of PG Ⅰ to PG Ⅱ(PGR)≤11.87,and G-17 ≥3.82 pmol/L were independent risk factors for gastric precancerous lesions(P＜0.05).A predictive model for gastric precancerous lesions was constructed based on these risk factors,and the complete model was established based on the predic-tive model.The total score ranged from 0 to 12(with 6 to 12 indicating a high-risk population for gastric precancerous lesions and 0 to 5 indicating a low-risk population).When the complete model,the simple model,the new ABC method,and the Li's score were included in the validation cohort for comparison,the predictive values of the complete model and the simple model were similar.Both models demonstrated higher sensitivity,specificity,positive predictive value,negative predictive value,and accuracy compared to the new ABC method and the Li's score.Furthermore,the diag-nostic value of the simple model in the high-sensitivity region was slightly superior to that of the com-plete model.Conclusion The simple model constructed based on the urea breath test,PG and G-17 exhibits favorable predictive efficacy,calibration,and clinical utility,and is of positive signifi-cance for the early identification of patients with gastric precancerous lesions.

Ubiquitination is a crucial post-translational modification that is extensively involved in the regulation of protein activity,signal transduction,and the maintenance of genomic stability.As an important member of the deubiquitinating enzyme(DUB)family,ubiquitin-specific protease 11(USP11)dynamically regulates the stability and function of key tumor proteins by targeting specific substrates for deubiquitination.This,in turn,influences various biological behaviors of tumor cells,including proliferation,apoptosis,migration,invasion,metastasis,and drug resistance,ultimately exhibiting a dual role in either promoting or inhibiting cancer.This article systematically reviewed the relevant research progress on the role of USP11 in tumorigenesis and development and provided an in-depth analysis of the specific mechanisms by which USP11 participates in cellular biological behav-iors,aiming to offer a theoretical basis for the future development of small-molecule inhibitors targeting USP11,the formulation of combination drug strategies,and the identification of effective biomarkers.

Objective:To summarize the practical experience of constructing an intelligent quality control system for electronic medical record (EMR) in clinical trials, providing reference for continuously improving the quality of clinical trials.Methods:Quality control rules for clinical trial EMR were established, and an intelligent quality control platform was developed to enable dynamic monitoring, interception, early warning, and evaluation. A hybrid quality control system integrating real-time and terminal quality control was constructed, alongside a three-dimensional linkage mechanism encompassing training, quality control, and evaluation.Results:Through the extensive application of information technology and the implementation of a multi-level quality control network, a quality control loop characterized by ″Efficient machine screening and precise human decision-making″ was achieved to enhance management quality and efficiency. However, challenges such as the standardization of quality control rules, data security and privacy protection, and system interface heterogeneity were persistent.Conclusions:The development of an intelligent quality control system for clinical trial EMR represents a critical step in advancing clinical trial quality management. Nevertheless, ongoing optimization of technical solutions is essential to address existing challenges and further improve system performance.

The widespread application of next generation sequencing (NGS) in clinical settings has enabled testing, diagnosis, treatment and prevention of genetic diseases. However, many issues have arisen in the meanwhile. One of the most pressing issues is the lack of standards for reporting genetic test results across different service providers. The First Forum on Standards and Specifications for Clinical Genetic Testing was held to address the issue in Shenzhen, China, on October 28, 2017. Participants, including geneticists, clinicians, and representatives of genetic testing service providers, discussed problems of clinical genetic testing services across in China and shared opinions on principles, challenges, and standards for reporting clinical genetic test results. Here we summarize expert opinions presented at the seminar and report the consensus, which will serve as a basis for the development of standards and guidelines for reporting of clinical genetic testing results, in order to promote the standardization and regulation of genetic testing services in China.