The Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines （hereinafter referred to as the Guidelines） is first specialized in the field of drug safety for oral Chinese patent medicines （OCPMs） in China. Rooted in China's healthcare context， the Guidelines address the unique usage patterns and risk characteristics of OCPMs， filling a regulatory gap in the pharmacovigilance framework specific to this category. To facilitate accurate understanding and effective implementation of the Guidelines， and to promote the standardized development of pharmacovigilance practices for OCPMs， this study offered a systematic interpretation based on its three core components. In the domain of risk monitoring and reporting， the paper analyzed the rationale for multi-source information integration and clarified the criteria for identifying key products and target populations for intensive monitoring. Regarding risk assessment， the Guidelines were examined from three dimensions of formulation components， medication behaviors， and population to address complex safety issues arising from medicinal constituents， irrational use， and individual susceptibility. In the area of risk control， the analysis focused on context-based interventions and dynamic closed-loop management strategies， exploring practical pathways to shift from passive response to proactive risk mitigation. Furthermore， this paper evaluated the applied value of the Guidelines and identified implementation challenges， such as insufficient capacity at the primary-care level and limited digital infrastructure. In response， the study proposed optimization strategies including establishing a dynamic updating mechanism， strengthening training at the grassroots level， and incorporating artificial intelligence to enhance pharmacovigilance capacity. This interpretation aims to provide actionable insights for marketing authorization holders （including manufacturers）， pharmaceutical distributors， healthcare institutions， and research organizations， ultimately supporting the establishment and refinement of a full lifecycle pharmacovigilance system for OCPMs.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

ObjectiveTo investigate the mechanism of Zuogui Wan （ZGW） in improving ovarian inflammatory microenvironment and stemness of ovarian germline stem cells （OSCs） for treating ovarian aging via the cyclic guanosine monophosphate/adenosine monophosphate synthase （cGAS）/stimulator of interferon genes （STING） signaling pathway. MethodsForty C57BL/6 female mice were randomly divided into a blank group， a model group， a low-dose ZGW group （2.7 g·kg^-1）， a high-dose ZGW group （5.4 g·kg^-1）， and an estradiol valerate group （0.15 mg·kg^-1）， with 8 mice in each group. Except the blank group， all other groups received a single intraperitoneal injection of cyclophosphamide at 120 mg·kg^-1 to establish an ovarian aging mouse model. After successful modeling， each group was continuously administered for 4 weeks， once daily. The physiological status of the mice was observed， and the ovarian index was calculated. The estrus cycle of the mice was monitored. Hematoxylin-eosin （HE） staining was used to observe pathological changes in ovarian tissue. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum sex hormone levels. Serum inflammatory factors interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and mouse interleukin-6 （IL-6） levels were detected using kits. Western blot was used to detect the protein expression of ovarian cGAS， STING， p-STING， TANK-binding kinase 1 （TBK1）， p-TBK1， interferon-induced transmembrane protein 3 （Fragilis）， and Vasa homolog protein （MVH）. Quantitative real-time polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors in ovarian tissue. Immunofluorescence double labeling was performed to locate OSCs in ovarian tissues， and fluorescence intensities of OSCs markers MVH and octamer binding transcription factor 4 （Oct4） were calculated. ResultsCompared with the blank group， the model group showed reduced body weight， ovarian wet weight， and ovarian index （P<0.01） and a disordered estrus cycle （P<0.01）. In addition， the levels of serum follicle-stimulating hormone （FSH）， TNF-α， IL-6， and IL-1β were increased （P<0.01）， while anti-Müllerian hormone （AMH） and estradiol （E₂） levels were decreased （P<0.01）. The protein expression of cGAS， p-STING/STING， and p-TBK1/TBK1 in ovarian tissue was increased （P<0.05， P<0.01）， while that of OSCs stemness factors MVH and Fragilis was reduced （P<0.01）. Immunofluorescence indicated a reduction in MVH and Oct4 expression in OSCs （P<0.01）. The mRNA expression of inflammatory factors TNF-α， IL-6， and IL-1β in ovarian tissue was increased （P<0.05， P<0.01）. Compared with the model group， the treatment groups exhibited improved body weight， ovarian wet weight， and ovarian index （P<0.05） and a reduced rate of estrus cycle disorder （P<0.05， P<0.01）. The levels of serum FSH， TNF-α， IL-6， and IL-1β were decreased （P<0.05， P<0.01）， while AMH and E₂ levels were increased （P<0.01）. The protein expression levels of cGAS， p-STING/STING， and p-TBK1/TBK1 in ovarian tissue were decreased （P<0.05）， while the protein expression of MVH and Fragilis was increased （P<0.05）， and the fluorescence intensities of MVH and Oct4 were increased （P<0.05， P<0.01）. The mRNA expression of inflammatory factors in ovarian tissue was decreased （P<0.05）. ConclusionZGW alleviate ovarian inflammatory response， regulate ovarian microenvironment homeostasis， and maintain stemness of OSCs in ovarian aging mice probably by modulating the cGAS-STING signaling pathway， thereby improving ovarian function and delaying ovarian aging.

Objective: To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine (TCM) through quantitative topic evolution analysis, we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field. Methods: A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM. Publications were retrieved from the China National Knowledge Infrastructure (CNKI), Wanfang Data, and China Science and Technology Journal Database (VIP), covering the period from database inception to July 3, 2025. A hybrid segmentation approach, based on cumulative publication growth trends and inflection point detection, was applied to divide the research timeline into distinct stages. Subsequently, the latent Dirichlet allocation (LDA) model was used to extract research topics, followed by alignment and evolutionary analysis of topics across different stages. Results: A total of 3 919 publications published between 2003 and 2025 were included, and the research trajectory was divided into five stages based on data-driven breakpoint detection. The field exhibited a clear evolutionary shift from early rule-based systems and tongue-pulse image and signal analysis (2006 – 2010), to machine-learning-based syndrome and prescription modeling (2011 – 2015), followed by deep-learning-driven pattern recognition and formula association (2016 – 2020). Since 2021, research has increasingly emphasized knowledge-graph construction, multimodal integration, and intelligent clinical decision-support systems, with recent studies (2024 – 2025) showing the emergence of large language models and agent-based diagnostic frameworks. Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis, alongside the progressive consolidation of integrated intelligent diagnostic platforms. Conclusion By identifying key technological transitions and persistent core research themes, our findings offer a structured reference framework for the design of intelligent diagnostic systems, the construction of knowledge-driven clinical decision-support tools, and the alignment of AI models with TCM diagnostic logic. Importantly, the stage-based evolutionary insights derived from this analysis can inform future methodological choices, improve model interpretability and clinical applicability, and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.

Objective: To revise and validate the reliability and validity of Chinese version of the Benevolent Childhood Experiences (BCEs) Scale among college students, so as to provide a scientific and reliable assessment tool for related research. Methods: From April to June 2025, a stratified cluster random sampling method was used to select 1 677 freshmen from a university in Xuzhou City as participants. The survey was conducted by using the revised Benevolent Childhood Experiences (BCEs) Scale, Childhood Trauma Questionnaire (CTQ) and Brief Suicidal Behavior Scale. Reliability analysis, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), Spearman correlation analysis, and hierarchical linear regression analysis were employed to evaluate the scale s reliability, validity, and relationships among variables. Results: The mean scores of the 10 items on the BCEs Scale ranged from 3.97 to 4.46, with standard deviations ranging from 0.88 to 1.07. The Cronbach α coefficient was 0.96. Exploratory factor analysis extracted a single factor, explaining 71.21% of the total variance. Confirmatory factor analysis indicated good model fit ( χ 2/df =4.81, goodness of fit index=0.99, comparative fit index=0.99, normed fit index=0.99, root mean square error of approximation=0.05, standardized root mean square residual=0.01). BCEs total scores were negatively correlated with CTQ total scores and all its dimensions among college students ( r =-0.53 to -0.13, all P < 0.01). Hierarchical regression analysis showed that BCEs moderated the effect of CTQ on suicidal behavior, with a statistically significant interaction ( β=-0.11, t=-4.01, P <0.01). Conclusion The Chinese revised version of the BCEs Scale demonstrates good reliability and validity, and it is suitable for assessing BCEs among Chinese college students.

Objective: To explore the relationship of screen time and sleep duration with screening myopia among junior and senior high school students, so as to provide evidence for the prevention and control of myopia among students. Methods: From March to October 2024, 429 junior and senior high school students from a district of Guangzhou were selected using stratified cluster random sampling method. Standardized logarithmic visual acuity chart was used for vision assessment, while Questionnaire for the Physical Health Monitoring System of Students in Guangzhou was employed to collect students screen time and sleep duration. The Chi square test was used to compare differences across different groups, and binary Logistic regression analysis was employed to analyze the association of screen time and sleep duration with screening myopia. Results: The overall prevalence of screening myopia was 79.5%, with significant differences across educational stage, sex, screen time and sleep duration groups( χ 2=41.64, 9.75, 23.89 , 8.17, all P <0.05).Binary Logistic regression analysis revealed that, compared to the high screen time & insufficient sleep group, the low screen & sufficient sleep group ( OR=0.25, 95%CI =0.09-0.68), the low screen & insufficient sleep group ( OR= 0.27 , 95%CI =0.13-0.56), and the high screen & sufficient sleep group ( OR=0.26, 95%CI =0.10-0.70) exhibited significantly lower screening myopia risks (all P <0.05). After adjusting for sex and educational stage, low screen time & insufficient sleep was significantly associated with screening myopia ( OR=0.48, 95%CI =0.23-0.98); the multiplicative interaction term was statistically significant ( OR=0.99,95%CI =0.98-1.00)(both P <0.05). Conclusion The interaction effect between screen time and sleep duration in relation to screening myopia suggests a need to focus on daily routines and screen use habits among junior and senior high school students for ensuring sufficient sleep and limiting screen exposure.

OBJECTIVE To analyze the impact of the diagnosis-related groups （DRG） payment reform on the length of stay and medical costs in patients with chronic obstructive pulmonary disease （COPD） in Kashgar region， aiming to provide localized empirical evidence for the optimization of regional medical insurance payment methods. METHODS Based on the inpatient settlement database of the Xinjiang Uygur Autonomous Region Healthcare Security Administration， settlement data of COPD inpatients from 17 medical institutions in Kashgar region between January 1， 2022， and December 31， 2024， were extracted. The overall changes in patients’ length of stay and costs were compared before and after the reform. Subsequently， interrupted time series analysis （ITSA） was employed to explore the impact of the DRG payment reform on these variables. RESULTS Following the reform， both the average length of stay and various cost decreased significantly compared to the pre-reform period （ P ＜0.001）. At the overall sample level， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission all demonstrated significant long-term downward trends after the reform （ P ＜0.05）. However， the decrease in average out-of-pocket costs and the increase in average consumable costs per admission were not statistically significant （ P ＞0.05）. In tertiary medical institutions， the average length of stay and all categories of costs （except average consumable costs per admission） exhibited significant long-term upward trends after the reform （ P ＜0.05）； conversely， in secondary and lower-level medical institutions， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission showed significant long-term downward trends （ P ＜0.05）. CONCLUSIONS The DRG payment reform has achieved an overall effect of reducing the length of stay and controlling costs in COPD patients from Kashgar region. However， the effects vary across different levels of medical institutions： secondary and lower-level institutions show a long-term downward trend in length of stay and costs， whereas tertiary institutions exhibit a long-term upward trend. Furthermore， patients’ out-of-pocket financial burden does not show significant improvement.

It is believed that the occurrence and development of squamous cell carcinoma （SCC） is closely associated with inflammatory responses. The theory of fire and heat， advocated by LIU Wansu， provides significant clinical guidance for understanding the pathogenesis and treatment of SCC. Based on this theory， the pathological mechanisms and clinical characteristics of SCC at different stages were analyzed. In the precancerous and early stages， the primary pathogenesis is qi stagnation leading to internal generation of constrained heat； in post-surgery， the condition shifts to qi deficiency with latent yin fire； during the treatment phase， the pathogenesis involves accumulation of pathogenic factors， excess toxins， and severe heat toxicity； in the late stage， the main pathology is yin deficiency with toxic heat， and phlegm-stasis obstruction of the internal organs. Corresponding stage-based treatment strategies are proposed. In the early stage， regulating qi movement to dissipate constrained heat； for post-surgery， tonifying qi and raising yang to dispel latent fire； during treatment stage， clearing heat and detoxifying to eliminate cancerous toxins； and in the late stage， nourishing yin and unblocking the bowels to clear deficiency heat.

[Objective] To explore the relationship between neutrophil activation under cardiopulmonary bypass (CPB) and the incidence of cardiac surgery-associated acute kidney injury (CS-AKI). [Methods] This prospective cohort study enrolled adult patients who scheduled for cardiac surgery under CPB at West China Hospital between May 1, 2022 and March 31, 2023. The primary outcome was acute kidney injury (AKI). Blood samples (5 mL) were obtained from the central vein before surgery, at rewarming, at the end of CPB, and 24 hours after surgery. Neutrophils were labeled with CD11b, CD54 and other markers. To assess the effect of neutrophils activation on AKI, propensity score matching (PSM) was employed to equilibrate covariates between the groups. [Results] A total of 120 patients included into the study, and 17 (14.2%) developed AKI. Both CD11b⁺ and CD54⁺ neutrophils significantly increased during the rewarming phase and the increases were kept until 24 hours after surgery. During rewarming, the numbers of CD11b⁺ neutrophils were significantly higher in AKI compared to non-AKI (4.71×10⁹/L vs 3.31×10⁹/L, Z=-2.14, P<0.05). Similarly, the CD54⁺ neutrophils counts were also significantly higher in AKI than in non-AKI before surgery (2.75×10⁹/L vs 1.79×10⁹/L, Z=-2.99, P<0.05), during rewarming (3.12×10⁹/L vs 1.62×10⁹/L, Z=-4.34, P<0.05), and at the end of CPB (4.28×10⁹/L vs 2.14×10⁹/L, Z=-3.91, P<0.05). An analysis of 32 matched patients (16 in each group) revealed that CD11b⁺ and CD54⁺ neutrophil levels of AKI were 1.74 folds (4.83×10⁹/L vs 2.77×10⁹/L, Z=-2.72, P<0.05) and 2.34 folds (3.32×10⁹/L vs 1.42×10⁹/L, Z=-4.12, P<0.05), respectively, of non-AKI at rewarming phase. [Conclusion] Neutrophils are activated during CPB, and they can be identified by CD11b/CD54 markers. The activated neutrophils of AKI patients are approximately 2 folds of non-AKI during the rewarming phase, with disparity reached peak between groups during rewarming. These findings suggest the removal of 50% of activated neutrophils during the rewarming phase may be effective to reduce the risk of AKI.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.