Driven by the growing practical need to accelerate drug development and the continuous innovation of trial design in recent years， the number of protocol amendments during clinical trials have gradually increased， and the changed contents have become more flexible and complex， which significantly heightens the difficulty of ethical review on amendments. Against this backdrop， it is of great importance to fully leverage the role and responsibilities of ethics committees， effectively control clinical trial risks， and ensure subject safety. This paper analyzed development trends of protocol amendments in recent years， sorted out requirements for protocol amendments in Chinese regulations and guiding principles， and examined difficulties of amendment ethical review in practical work. Based on these， targeted strategies and recommendations were proposed， namely， strengthening the integration with scientific review， enhancing the formal review， adjusting the scope of review according to approval notifications， and adopting appropriate review methods， with a view to providing insights and references for the management of the amendment ethical review in drug clinical trials.

Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

ObjectiveTo systematically assess the public health governance capacity in Zhejiang Province, to conduct an in-depth analysis of its strengths and weaknesses, so as to provide scientific basis and strategic recommendations for further enhancement. MethodsA systematic collection of policy documents, public information reports, and research literature related to public health governance capacity in Zhejiang Province from 2002 to 2023 was conducted (encompassing a total of 1 263 policy documents, 138 pieces of information reports and 631 research articles). Based on the evaluation criteria suitable for public health systems previously developed by the research team, the basic status and magnitude of change in public health governance capacity in Zhejiang Province was evaluated. Additionally, normative gap analyses were employed to identify the strengths and weaknesses. ResultsZhejiang Province ranked 4th nationwide in terms of public health governance capacity with a score of 733.4 points (1 000.0-point maximum). The province has effectively implemented the principle of health first (scoring 698.5 points in the assessment of health-first strategy implementation) and attached sufficient importance to health-related goals (scoring 658.2 points in the scientific rationality of goal setting). However, the implementation of inter-departmental coordination and incentive mechanisms only scored 178.7 points, the feasibility of management and monitoring mechanisms scored even lower at only 144.0 points, and the coverage of incentive mechanisms scored 286.0 points. ConclusionZhejiang Province has effectively implemented its health first strategy and attached great importance to health targets, but still needs to strengthen cross-departmental coordination mechanisms and health-oriented incentives.

Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

BACKGROUND:Fibromyalgia syndrome,as a common rheumatic disease,is related to central sensitization and immune abnormalities.However,the specific mechanism has not been elucidated,and there is a lack of specific diagnostic markers.Exploring the possible pathogenesis of this disease has important clinical significance. OBJECTIVE:To screen the potential diagnostic marker genes of fibromyalgia syndrome and analyze the possible immune infiltration characteristics based on bioinformatics methods,such as weighted gene co-expression network analysis(WGCNA),and machine learning. METHODS:Gene expression profiles in peripheral serum of fibromyalgia syndrome patients and healthy controls were obtained from the gene expression omnibus(GEO)database.The differentially co-expressed genes were screened in the expression profile by differential analysis and WGCNA analysis.Least absolute shrinkage and selection operator(LASSO)and support vector machine-recursive feature elimination(SVM-RFE)machine learning algorithm were further used to identify hub biomarkers,and draw receiver operating characteristic curve(ROC)to evaluate the accuracy of diagnosing fibromyalgia syndrome.Finally,single sample gene set enrichment analysis(ssGSEA)and gene set enrichment analysis(GSEA)were used to evaluate the immune cell infiltration and pathway enrichment in patients with fibromyalgia syndrome. RESULTS AND CONCLUSION:Eight down-regulated differentially expressed genes(DEGs)were obtained after differential analysis of the GSE67311 dataset according to the conditions of log2|(FC)|>0 and P<0.05.After WGCNA analysis,497 genes were included in the module(MEdarkviolet)with the highest positive correlation(r=0.22,P=0.04),and 19 genes were included in the module(MEsalmon2)with the highest negative correlation(r=-0.41,P=6×10-5).After intersecting DEGs and the module genes of WGCNA,seven genes were obtained.Four genes were screened out by LASSO regression algorithm and five genes were screened out by SVM-RFE machine learning algorithm.After the intersection of the two,three core genes were identified,which were germinal center associated signaling and motility like,integrin beta-8,and carboxypeptidase A3.The areas under the ROC curve of the three core genes were 0.744,0.739,and 0.734,respectively,indicating that they have good diagnostic value and can be used as biomarkers for fibromyalgia syndrome.The results of immune infiltration analysis showed that memory B cells,CD56 bright NK cells,and mast cells were significantly down-regulated in patients with fibromyalgia syndrome compared with the control group(P<0.05),and were significantly positively correlated with the above three biomarkers(P<0.05).The enrichment analysis suggested that there were nine fibromyalgia syndrome enrichment pathways,mainly related to olfactory transduction pathway,neuroactive ligand-receptor interaction,and infection pathway.The above results showed that the occurrence and development of fibromyalgia syndrome are related to the involvement of multiple genes,abnormal immune regulation,and multiple pathways imbalance.However,the interactions between these genes and immune cells,as well as their relationships with various pathways need to be further investigated.

BACKGROUND:Rev-erbα is involved in the regulation of inflammation,but pharmacological activation of Rev-erbα increases the risk for cardiovascular diseases.To reduce the relevant risk,an exploration on SR9009,a Rev-erbα agonist,combined with other drugs to relieve inflammation in skeletal myoblasts was conducted,laying the theoretical foundation for the treatment of inflammation-associated skeletal muscle atrophy. OBJECTIVE:To investigate the relationship of SR9009,indolepropionic acid and nuclear factor-κB signaling pathways in lipopolysaccharide-induced C2C12 myoblasts. METHODS:(1)C2C12 myoblasts were induced to differentiate in the presence of lipopolysaccharide(1 μg/mL).RNA-seq and KEGG pathway analysis were used to study signaling pathways.(2)C2C12 myoblast viability was assessed using the cell counting kit-8 assay to determine optimal concentrations of indolepropionic acid.Subsequently,cells were categorized into control group,lipopolysaccharide(1 μg/mL)group,SR9009(10 μmol/L)+lipopolysaccharide group,indolepropionic acid(80μmol/L)+lipopolysaccharide group,and SR9009+indolepropionic acid+lipopolysaccharide group.ELISA was employed to measure protein expression levels of interleukin-6 in the cultured supernatant.Real-time quantitative PCR were employed to measure mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Western blot assay were employed to measure protein expression levels of NF-κB p65 and p-NF-κB p65.(3)After Rev-erbα was knocked down by siRNA,knockdown efficiency was assessed by RT-qPCR.And mRNA levels of interleukin-6 and tumor necrosis factor α were also measured. RESULTS AND CONCLUSION:Compared with the blank control group,lipopolysaccharide time-dependently inhibited myofibroblast fusion to form myotubes,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were elevated,and the level of interleukin-6 in the cell supernatant was significantly increased.The results of KEGG pathway showed that the nuclear factor-κB signaling pathway was activated by lipopolysaccharide.Indolepropionic acid exhibited significant suppression of C2C12 myoblasts viability when its concentration exceeded 80 μmol/L.Indolepropionic acid and SR9009 inhibited the activation of NF-κB signaling pathway,thereby played an anti-inflammatory role,and suppressed the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.Compared with the lipopolysaccharide group,the ratio of p-NF-κB p65/NF-κB p65 protein expression were downregulated.SR9009 combined with indolepropionic acid notably reduced lipopolysaccharide-induced inflammation,further downregulated the mRNA expression levels of interleukin-6,tumor necrosis factor α,TLR4 and CD14.The ratio of p-NF-κB p65/NF-κB p65 protein expression was significantly lower than that in the SR9009+lipopolysaccharide group or indolepropionic acid+lipopolysaccharide group.Rev-erbα increases time-dependently with lipopolysaccharide induction.The knockdown efficiency of Rev-erbα by siRNA reached over 58%,and lipopolysaccharide was added after Rev-erbα was successfully knocked down.Compared with the lipopolysaccharide group,the mRNA expression levels of interleukin-6 and tumor necrosis factor α were significantly up-regulated.These results conclude that Rev-erbα may act as a promising pharmacological target to reduce inflammation.SR9009 targeted activation of Rev-erbα combined with indolepropionic acid significantly inhibits the nuclear factor-κB signaling pathway and attenuates the inflammatory response of C2C12 myofibroblasts.Moreover,the combined anti-inflammatory effect is superior to that of the intervention alone.

BACKGROUND: Lung cancer is the leading malignancy in China in terms of both incidence and mortality. With increased health awareness and the widespread use of low-dose computed tomography (CT), early diagnosis rates have been steadily improving. Surgical intervention remains the primary treatment option for early-stage lung cancer, and video-assisted thoracoscopic surgery (VATS) has become a common approach due to its minimal invasiveness and rapid recovery. However, post-discharge recovery remains incomplete, underscoring the importance of postoperative care. Traditional follow-up methods, lack standardization, consume significant medical resources, and increase the burden of the patients. Artificial intelligence (AI)-driven disease management platforms offer a novel solution to optimize postoperative follow-up. This study followed 463 lung cancer surgery patients using an AI-based platform, aiming to identify common postoperative issues, propose solutions, improve quality of life, reduce recurrence-related costs, and promote AI integration in healthcare. METHODS: Using the AI disease management platform, this study integrated educational videos, collaboration between healthcare teams and AI assistants, daily health logs, health assessment forms, and personalized interventions to monitor postoperative recovery. The postoperative rehabilitation status of the patients was assessed by the Leicester Cough Questionnaire (LCQ-MC). Two independent t-test and one-way ANOVA were used to analyze the causes of postoperative cough in lung cancer. RESULTS: Most issues occurred within 7 d post-discharge, significantly declined on 14 d post-discharge. Factors such as gender, smoking history, and surgical approaches were found to influence cough recovery. The incidence of cough on 7 d post-discharge in females was higher than that in males (P<0.01), while the incidence of cough on 14 d post-discharge in elderly patients was lower than that in young patients (P=0.03). The AI-based platform effectively addressed cough, pain, and sleep disturbances through phased interventions. CONCLUSIONS The AI-based platform significantly enhanced postoperative management efficiency and the self-care capabilities of the patients, particularly in phased cough management. Future integration with wearable devices could enable more precise and personalized postoperative care, further advancing the application of AI technology across multidisciplinary healthcare domains.
Humans ; Lung Neoplasms/rehabilitation* ; Male ; Female ; Middle Aged ; Aged ; Patient Discharge ; Artificial Intelligence ; Adult ; Postoperative Care ; Postoperative Period ; Disease Management ; Quality of Life

Objective To investigate the effects of paeoniflorin(PF)on lipopolysaccharide(LPS)-induced aerobic glycolysis in renal tubular epithelial cell line HK-2 and its underlying mechanism of action.Methods This study consists of a preliminary experiment and a formal experiment.Preliminary experiment:CCK-8 assay and RT-qPCR were used respectively to measure cell viability and mRNA expression levels of inflammatory factors in HK-2 cells after LPS stimulation to determine the optimal LPS concentration for modeling as well as to evaluate the toxicity of PF and screen for its appropriate concentration.Formal experiment:HK-2 cells were divided into control group(CON group),LPS group,LPS+PF group and LPS+PF+740Y-P group.LPS was used to establish a cell model of sepsis associated-acute kidney injury(SA-AKI)in HK-2 cells,and then the cell model was treated with PF and PI3K activator 740Y-P,correspondingly for 24 h.CCK-8 assay was employed to detect cell viability,and Extracellular Acidification Rate(ECAR)Kit was utilized to measure the rate.The contents of IL-1β,IL-18,lactic acid(Lac)and lactate dehydrogenase A(LDHA)were determined with ELISA.Western blotting was applied to detect the expression of p-PI3K,p-AKT,HIF-1α,pyruvate kinase 2(PKM2,a key enzyme in aerobic glycolysis)and NOD-like receptor thermal protein domain associated protein 3(NLRP3),and immunofluorescence assay was performed to observe the expression and distribution of PKM2.Results ① Our preliminary experiment identified that the optimal concentration of LPS for modeling was 20.0 μg/mL,a safe dosage range of PF was 0～100.0 μmol/L,and its optimal therapeutic concentration was 25.0 μmol/L.② Compared with the CON group,LPS stimulation resulted in significantly decreased cell viability(P<0.05),increased ECAR(P<0.05),elevated contents of IL-1β,IL-18,Lac and LDHA(P<0.05),up-regulated protein levels of p-PI3K,p-AKT,HIF-1α,p-PKM2 and NLRP3(P<0.05),and enhanced fluorescence intensity of PKM2 in the nucleus of cells(P<0.05).Compared with the model group,PF treatment reversed all above effects induced by LPS stimulation(all P<0.05).Compared with the LPS+PF group,in the LPS+PF+740Y-P group,ECAR was elevated(P<0.05),the contents of IL-1β,IL-18,Lac and LDHA were increased(P<0.05),and the relative expression levels of p-PI3K,p-AKT,HIF-1α,p-PKM2 and NLRP3 were increased(P<0.05),and the fluorescence intensity of PKM2 was strengthened(P<0.05)and enhanced in the nucleus(P<0.05).Conclusion PF reduces aerobic glycolysis in HK-2 cells and alleviates the inflammatory response by inhibiting the PI3K/AKT/HIF-1α signaling pathway.

ObjectiveTo systematically evaluate the public health governance capacity of 40 cities in Jiangsu, Zhejiang, and Anhui Provinces, providing a scientific evaluation basis for building a "Healthy Yangtze River Delta". MethodsA comprehensive collection of policy documents, public information reports, and research literature related to public health governance capacity in Jiangsu, Zhejiang, and Anhui Provinces was conducted, totaling 6 920 policy documents, 1 720 information reports, and 1 200 literature pieces. Based on the evaluation standards for an appropriate public health system established by the research team, the basic status of public health governance capacity was assessed to identify the strengths and weaknesses of the 40 cities. ResultsIn 2022, the public health governance capacity score for the 40 cities in Jiangsu, Zhejiang, and Anhui Provinces was (562.5±38.0) points. In terms of specific areas, the emergency response field received the highest score of (791.4±49.7) points, while the chronic disease prevention and control field received the lowest score of (368.2±29.6) points. The Jiangsu-Zhejiang-Anhui region has largely achieved the strategic priority of health, gradually improved public health legal regulations, and established a basic organizational framework with a solid foundation for information and data infrastructure. However, challenges still need to be addressed, such as unstable government funding for public health, unclear departmental responsibilities, and barriers to information interoperability. ConclusionThe public health governance capacity of the 40 cities in Jiangsu, Zhejiang, and Anhui Province has been at a moderate level, but disparities have still existed across regions and fields. In the future, while continuing to deepen existing advantages, it is essential to accurately identify the causes of problems, establish a long-term and stable investment mechanism, enhance information connectivity mechanisms, further clarify departmental responsibilities, and promote the achievement of the "Healthy Yangtze River Delta" goal.

Objective:To understand the current status of epidemiological investigation task force construction and the performance of infectious disease epidemic response in county (district) Centers for Disease Control and Prevention (CDCs) in China, analyze the influencing factors and provide scientific evidence to improve the construction of grassroot epidemiological investigation task force.Methods:A survey was conducted in epidemiological investigation staff in county (district) CDCs in 31 provinces (autonomous regions/municipalities) and Xinjiang Production and Construction Corps in China. A self-designed questionnaire was used to collect information based on the epidemiological dynamic data collection platform of China CDC. A descriptive epidemiological analysis was conducted, and multiple linear regression models were used to identify the factors associated with the performance of infectious disease epidemic response.Results:A total of 24 934 epidemiological investigation task force members from 2 897 county (district) CDCs were surveyed in the study. In the epidemiological investigation task force, women, those with bachelor's degree and public health workers accounted for 62.46%, 71.36%, and 49.05% respectively. Up to 91.72% of the task force members had participated in field epidemic response. The average score of awareness of epidemic investigation procedures was 60.00, while the average score of key skill proficiency in the investigation was 42.22. The epidemic response performance showed correlations with area, gender, age, education level, major, and field epidemiology training programs, those who had received longer training showed higher competency scores (all P<0.001). Conclusions:Progress has been made in the construction of epidemiological investigation task force in grass-root CDCs in China, but further improvements are needed, especially in the knowledge awareness and investigation skills of the task force. Field epidemiology training demonstrated substantial impact on the improvement of epidemic response performance, indicating that it is necessary to further strengthen the training in grassroot public health workers for the better response to infectious disease epidemics.