1.Compilation Instruction for Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use
Xin CUI ; Dingquan YANG ; Zhennian XIE ; Yuanyuan LI ; Zhifei WANG ; Xu WEI ; Jinghua GAO ; Lianxin WANG ; Yanming XIE
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):252-259
The Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use (T/CACM 1563.5—2024), the first guideline in China specializing for the clinical safety of Chinese patent medicines for external use, was led by the Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences,and jointly developed by more than 30 research institutions of medical sciences across the country. Aiming to standardize the pharmacovigilance activities in the clinical application of Chinese patent medicines for external use,the guideline systematically categorizes potential risks and proposes prevention and control measures that cover 11 core sections of risk monitoring and reporting, signal identification,as well as assessment and control, addressing the gap in domestic and international standardization of this field. The compilation of this guideline strictly adhered to international norms and domestic regulations, involving multiple rounds of expert consultations,hybrid interviews, and evidence integration (covering literature,medical insurance,essential medicine,pharmacopoeia data, and regulatory information). With the scope of application defined to include medical institutions, pharmaceutical manufacturers and distribution enterprises,as well as regulatory authorities, the guideline focuses on key issues such as inherent medicine risks,quality risks,off-label use,risks of combination therapy,and the safety in special populations. During the compilation,core discrepancies such as the definition of application scope and quality risk control were addressed to ensure alignment with regulations such as the Drug Administration Law of the People's Republic of China and the Good Pharmacovigilance Practice. The guideline is registered internationally (PREPARE—2022CN463). In the future,the implementation of the guideline will be promoted through hierarchical dissemination,dynamic revision,and post-effectiveness evaluation, contributing to rational clinical use and improved patient safety.
2.Compilation Instruction for Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use
Xin CUI ; Dingquan YANG ; Zhennian XIE ; Yuanyuan LI ; Zhifei WANG ; Xu WEI ; Jinghua GAO ; Lianxin WANG ; Yanming XIE
Chinese Journal of Experimental Traditional Medical Formulae 2026;32(8):252-259
The Pharmacovigilance Guideline for Clinical Application of Chinese Patent Medicine for External Use (T/CACM 1563.5—2024), the first guideline in China specializing for the clinical safety of Chinese patent medicines for external use, was led by the Institute of Basic Research in Clinical Medicine,China Academy of Chinese Medical Sciences,and jointly developed by more than 30 research institutions of medical sciences across the country. Aiming to standardize the pharmacovigilance activities in the clinical application of Chinese patent medicines for external use,the guideline systematically categorizes potential risks and proposes prevention and control measures that cover 11 core sections of risk monitoring and reporting, signal identification,as well as assessment and control, addressing the gap in domestic and international standardization of this field. The compilation of this guideline strictly adhered to international norms and domestic regulations, involving multiple rounds of expert consultations,hybrid interviews, and evidence integration (covering literature,medical insurance,essential medicine,pharmacopoeia data, and regulatory information). With the scope of application defined to include medical institutions, pharmaceutical manufacturers and distribution enterprises,as well as regulatory authorities, the guideline focuses on key issues such as inherent medicine risks,quality risks,off-label use,risks of combination therapy,and the safety in special populations. During the compilation,core discrepancies such as the definition of application scope and quality risk control were addressed to ensure alignment with regulations such as the Drug Administration Law of the People's Republic of China and the Good Pharmacovigilance Practice. The guideline is registered internationally (PREPARE—2022CN463). In the future,the implementation of the guideline will be promoted through hierarchical dissemination,dynamic revision,and post-effectiveness evaluation, contributing to rational clinical use and improved patient safety.
3.Analysis of undernutrition and associated factors among left behind and nonleftbehind primary and secondary school students in the Nutrition Improvement Program areas in central and western China
Chinese Journal of School Health 2026;47(3):327-331
Objective:
To investigate the prevalence of undernutrition and its associated factors among left behind and non left behind primary and secondary school students in the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) areas of central and western China, so as to provide evidence for improving the nutritional status of children and adolescents.
Methods:
A survey was conducted among 123 782 students selected by random cluster sampling method in grades 3-9 from NIPRCES in central (Hebei, Shanxi, Heilongjiang, Jilin, Anhui, Jiangxi, Henan, Hunan, Hubei, and Hainan) and western (Gansu, Guangxi, Inner Mongolia, Ningxia, Tibet, Shaanxi, Guizhou, Sichuan, Xinjiang, the Xinjiang Production and Construction Corps, Yunnan, Qinghai, and Chongqing) China in 2023. Anthropometric measurements and questionnaires were used to assess nutritional and dietary status. The prevalence of undernutrition was compared between left behind and non left behind students by Chi square test, and associated factors were analyzed by three level Logistic mixed effects model.
Results:
The prevalence of undernutrition was 8.5% (4 326) in left behind students and 8.1% (5 905) in non left behind students. Three level Logistic mixed effect model analysis showed that whether left behind or non left behind, the undernutrition rates of primary and secondary students in western regions were higher than those of students in central regions [ OR (95% CI )=1.72(1.57-1.87),2.25(2.07- 2.43 )]; the undernutrition risk was lower for those whose fathers had a cultural level of high school or above [ OR (95% CI )=0.69(0.62-0.77),0.90(0.82-0.98)] or junior high school [ OR (95% CI )=0.72(0.66-0.79),0.92(0.85-0.99)] compared to those with primary school or below; picky eating or selective eating increased the risk of undernutrition [ OR (95% CI )=2.36(2.07-2.68),2.28(2.04-2.55)], and primary and secondary school students without nutritional content in health education classes had higher rates of undernutrition [ OR (95% CI )=1.12(1.03-1.23),1.09(1.01-1.17)](all P <0.05).
Conclusion
The prevalence of undernutrition is slightly higher in left behind primary and secondary students than in non left behind primary and secondary students in central and western NIPRCES areas, with variations across different characteristics.
4.Temporal trends in the frequency of meat, egg and milk consumption among primary and secondary school students in rural central and western China, 2015-2023
Chinese Journal of School Health 2026;47(3):332-336
Objective:
To analyze the trends of the frequency of meat, egg, and milk consumption among rural primary and junior high school students in central and western China covered by the Nutrition Improvement Program for Rural Compulsory Education Students (NIPRCES) from 2015 to 2023, so as to provide basis for formulating more targeted nutrition intervention policies and health education strategies.
Methods:
Using data from six rounds of monitoring and evaluation (2015-2021 and 2023), the study included 323 870 students from grade 3 to 9 across 22 provinces (autonomous regions and municipalities) in central and western China. The consumption frequencies of meat, egg, and milk over the past week were collected via questionnaires. The Cochran-Armitage trend test was used to analyze temporal trends, and multivariable Logistic regression models were employed to analyze factors associated with the frequency of meat, egg and milk consumption and to test for interaction effects between the year and gender, region, and grade level.
Results:
From 2015 to 2023, the proportion of students consuming meat, egg, and milk ≥1 time/day increased from 23.20 %, 10.71%, and 0.74% to 35.53%, 22.09%, and 26.63%, respectively. Trend tests indicated a significant upward trend for the daily intake of all three food categories for meat, egg and milk over the years ( Z =67.18, 64.90, 93.14, all P <0.01). Multivariable Logistic regression analysis showed that the daily meat intake was lower in the central region than in the western region ( OR=0.77, 95%CI =0.76-0.78), whereas the daily intake of eggs ( OR=1.19, 95%CI =1.17-1.22) and milk ( OR= 1.27 , 95%CI =1.24-1.29) was higher in the central region (all P <0.05). Compared with grade 3-4 students, junior high school students had lower daily intake of meat, eggs, and milk≥1 time/day ( OR =0.95, 0.77, 0.77, all P <0.05), with a declining trend as grade increased. Girls also had lower daily intake of meat, eggs, and milk ≥1 time/day than boys ( OR =0.95,0.93,0.91, all P < 0.05). Significant interactions were observed between year and region, as well as between year and grade (all P <0.05).
Conclusion
From 2015 to 2023, the NIPRCES improved the intake level of among rural students, but the situation of relatively insufficient intake of egg and milk among females, junior high school students and those in the western region still exists.
5.Development of A Prognostic Prediction Model for Primary Membranous Nephropathy in the Elderly Based on Machine Learning
Yuzhu XU ; Shuqin LIU ; Dingding WANG ; Wei CHEN ; Xin WANG
Medical Journal of Peking Union Medical College Hospital 2026;17(2):370-381
Elderly patients with primary membranous nephropathy (PMN) exhibit significant prognostic heterogeneity and poor tolerance to immunotherapy. However, there is a lack of early prognostic prediction tools specifically for this population. This study aimed to develop a prognostic prediction model applicable to elderly PMN patients. This study retrospectively included elderly patients with PMN confirmed by renal biopsy. The primary endpoint was a adverse composite outcome including end-stage renal disease (ESRD), a ≥50% decline in estimated glomerular filtration rate (eGFR), or all-cause death. Patients were randomly divided into a training cohort and a validation cohort at a ratio of 7∶3. Key prognostic features were identified using least absolute shrinkage and selection operator (LASSO) regression combined with random survival forest, and a predictive model was constructed based on penalized Cox regression. Model performance was evaluated using the concordance index (C-index), time-dependent area under the receiver operating characteristic curve (AUROC), calibration curves, and decision curve analysis. The SurvSHAP (t) method was employed for interpretability analysis of the model. A total of 309 elderly patients with PMN were included in this study, with a median age of 65.00 years (IQR, 62.00-68.00) and a male predominance 61.2%(189/309).During a median follow-up of 47.00 months (IQR, 25.00-89.00), 38.2%(118/309) reached the endpoint event. The final model included nine key features, including eGFR, total protein (TP), glomerular capsular adhesion, urine glucose, segmental glomerulosclerosis proportion, fibrinogen, urea, age, and activated partial thromboplastin time (APTT). In the validation cohort, the model demonstrated good discrimination, with a C-index of 0.731(95% CI: 0.652-0.797). The time-dependent AUROCs for predicting adverse outcomes at 3, 5, and 10 years were 0.758(95% CI: 0.614-0.901), 0.781(95% CI: 0.646-0.916), and 0.866(95% CI: 0.740-0.993), respectively. Calibration curves demonstrated a high degree of concordance between predicted probabilities and actual event rates. Decision curve analysis confirmed the net clinical benefit of the model.SurvSHAP (t) analysis showed that eGFR, TP, glomerular capsular adhesion, urine glucose, and the proportion of segmental glomerular sclerosis were the top five variables contributing to the model. This prognostic model effectively predicts the risk of adverse outcomes in elderly patients with PMN in the internal validation cohort, offering a potential scientific basis for individualized risk stratification and treatment decision-making in this population.
6.Relationship Between Gastroesophageal Reflux Disease-Related Symptoms and Clinicopathologic Characteristics and Long-Term Survival of Patients with Esophageal Adenocarcinoma in China
Kan ZHONG ; Xin SONG ; Ran WANG ; Mengxia WEI ; Xueke ZHAO ; Lei MA ; Quanxiao XU ; Jianwei KU ; Lingling LEI ; Wenli HAN ; Ruihua XU ; Jin HUANG ; Zongmin FAN ; Xuena HAN ; Wei GUO ; Xianzeng WANG ; Fuqiang QIN ; Aili LI ; Hong LUO ; Bei LI ; Lidong WANG
Cancer Research on Prevention and Treatment 2025;52(8):661-665
Objective To investigatethe relationship between gastroesophageal reflux disease (GERD) symptoms and clinicopathological characteristics, p53 expression, and survival of Chinese patients with esophageal adenocarcinoma. Methods A total of
7.CpG/OX40 in situ vaccine combined with anti-angiogenic drugs enhances the systemic anti-tumor effects against mouse ovarian cancer
WEI Xiaofang1 ; XU Shuhua1 ; XIN Ce2 ; ZHAO Peng3 ; SUN Weihong3
Chinese Journal of Cancer Biotherapy 2025;31(8):806-813
[摘 要] 目的:探究CpG寡核苷酸和OX40激动剂抗体原位疫苗(CpG + OX40)联合抗血管生成药物安罗替尼(anlotinib)治疗小鼠卵巢癌的全身抗肿瘤效应及免疫机制。方法:建立双侧(原发侧和转移侧)ID8细胞小鼠卵巢癌模型,分组给予安罗替尼、CpG + OX40或CpG + OX40 + 安罗替尼(三联疗法)治疗。通过监测肿瘤体积和记录生存期评估各治疗组的抗肿瘤效果。采用流式细胞术和ELISA法检测肿瘤微环境中的免疫细胞和细胞因子变化,qRT-PCR法检测移植瘤组织中反映血管密度和成熟度的分子的相对表达量。结果:与其他治疗组相比,三联疗法显著抑制治疗侧(原发侧)和未治疗侧(转移侧)肿瘤的生长(P < 0.01),延长荷瘤鼠生存期(P < 0.05)。流式术检测结果显示,三联疗法显著提高原发侧和转移侧肿瘤内CD4+ T和CD8+ T细胞浸润比例(P < 0.05)。免疫细胞耗竭实验表明,单独耗竭CD4+ T、CD8+ T或NK细胞时,三联疗法对原发侧肿瘤的抑制作用无明显变化,而转移侧的抗肿瘤作用显著减弱但仍强于PBS组(P < 0.01)。仅当3种免疫细胞同时耗竭时,肿瘤抑制效应与PBS组差异无统计学意义(P > 0.05 )。ELISA法检测结果显示,与各治疗组相比,三联疗法组原发侧和转移侧肿瘤内Th1细胞相关细胞因子明显增加(P < 0.05),Th2细胞相关细胞因子的表达显著降低(P < 0.05)。qRT-PCR法结果显示,与对照组相比,三联疗法组双侧移植瘤组织内的CD31表达显著降低(P < 0.000 1),血管生成素(Ang)-1/Ang-2的比值显著升高(P < 0.001)。结论: CpG + OX40原位疫苗联合安罗替尼具有更强的全身抗肿瘤效应,适应性免疫和固有免疫及血管密度调控在其中发挥关键作用,为晚期肿瘤患者提供潜在治疗选择。
8.Comparative study of SARIMA and seasonal index model in predicting non-occupational carbon monoxide poisoning
Wantong HAN ; Yongqiang ZHANG ; Shichang DU ; Wei WANG ; Kai QU ; Xin HE ; Cixian XU ; Xiumei SUN ; Qiran SUN ; Jinyao ZHANG ; Fan BU ; Xingui SUN
Journal of Public Health and Preventive Medicine 2025;36(6):12-16
Objective To establish a prediction model for the occurrence of non-occupational carbon monoxide poisoning events in Beijing, and to provide scientific basis and theoretical support for the prevention and warning of poisoning events. Methods Based on the monitoring data of non-occupational carbon monoxide poisoning events in Beijing from 2016 to 2024, the seasonal ARIMA model and seasonal index model were established to analyze the data and predict the occurrence of events. Results Between 2016 and 2024, a total of 436 cases of non-occupational carbon monoxide poisoning were reported in Beijing, showing a downward trend. The established SARIMA model and seasonal index model were SARIMA (1,0,0) (1,1,0) 12, Yt = (-0.0339t+5.8863) × St, and the average relative errors were 65.42% and 29.19%, respectively. In terms of months, the SARIMA model had better predictive performance during April and summer (June to August), while the seasonal index model was superior in other months. By combining the two models, the predicted number of events in 2025 was as follows: 3, 2, 2, 3, 1, 5, 2, 7, 1, 1, 1, and 2. Conclusion The seasonal index model has the best prediction effect on the non-occupational carbon monoxide poisoning events in Beijing throughout the year, and the number of summer events predicted by SARIMA model is closer to the actual values. The two models can be combined to predict the trend of non-occupational carbon monoxide poisoning, which provides a scientific basis for the prevention and control of carbon monoxide poisoning in the future.
9.Robotic-assisted radical colorectal cancer surgery with the KangDuo surgical robotic system vs . the da Vinci Xi surgical system in elderly patients: A multicenter randomized controlled trial.
Hao ZHANG ; Yuliuming WANG ; Chunlin WANG ; Yunxiao LIU ; Xin WANG ; Xin ZHANG ; Yihaoran YANG ; Junyang LU ; Lai XU ; Zhen SUN ; Zhengqiang WEI ; Yi XIAO ; Guiyu WANG
Chinese Medical Journal 2025;138(11):1384-1386
10.Risk prediction of Reduning Injection batches by near-infrared spectroscopy combined with multiple machine learning algorithms.
Wen-Yu JIA ; Feng TONG ; Heng-Xu LIU ; Shu-Qin JIN ; Yong-Chao ZHANG ; Chen-Feng ZHANG ; Zhen-Zhong WANG ; Xin ZHANG ; Wei XIAO
China Journal of Chinese Materia Medica 2025;50(2):430-438
In this paper, near-infrared spectroscopy(NIRS) was employed to analyze 129 batches of commercial products of Reduning Injection. The batch reporting rate was estimated according to the report of Reduning Injection in the direct adverse drug reaction(ADR) reporting system of the drug marketing authorization holder of the Center for Drug Reevaluation of the National Medical Products Administration(National Center for ADR Monitoring) from August 2021 to August 2022. According to the batch reporting rate, the samples of Reduning Injection were classified into those with potential risks and those being safe. No processing, random oversampling(ROS), random undersampling(RUS), and synthetic minority over-sampling technique(SMOTE) were then employed to balance the unbalanced data. After the samples were classified according to appropriate sampling methods, competitive adaptive reweighted sampling(CARS), successive projections algorithm(SPA), uninformative variables elimination(UVE), and genetic algorithm(GA) were respectively adopted to screen the features of spectral data. Then, support vector machine(SVM), logistic regression(LR), k-nearest neighbors(KNN), naive bayes(NB), random forest(RF), and artificial neural network(ANN) were adopted to establish the risk prediction models. The effects of the four feature extraction methods on the accuracy of the models were compared. The optimal method was selected, and bayesian optimization was performned to optimize the model parameters to improve the accuracy and robustness of model prediction. To explore the correlations between potential risks of clinical use and quality test data, TreeNet was employed to identify potential quality parameters affecting the clinical safety of Reduning Injection. The results showed that the models established with the SVM, LR, KNN, NB, RF, and ANN algorithms had the F1 scores of 0.85, 0.85, 0.86, 0.80, 0.88, and 0.85 and the accuracy of 88%, 88%, 88%, 85%, 91%, and 88%, respectively, and the prediction time was less than 5 s. The results indicated that the established models were accurate and efficient. Therefore, near infrared spectroscopy combined with machine learning algorithms can quickly predict the potential risks of clinical use of Reduning Injection in batches. Three key quality parameters that may affect clinical safety were identified by TreeNet, which provided a scientific basis for improving the safety standards of Reduning Injection.
Spectroscopy, Near-Infrared/methods*
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Drugs, Chinese Herbal/administration & dosage*
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Machine Learning
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Algorithms
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Humans
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Quality Control


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