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.

In the era of evidence-based medicine， the progress of medical science and technology has enriched medical diagnostic tools and treatment methods， but it has also led to the loss of medical warmth and the alienation of the doctor-patient relationships. William Osler emphasized that while medical technology advances， attention should also be paid to the practice of narrative medicine and the development of physician’s narrative literacy. The view of the physician he advocated reminds us that the core of medicine still lies in the narrative connection between doctors and patients， as well as a deep understanding of human nature. By exploring the relationship between Osler’s view of the physician and narrative medicine as well as physician’s narrative literacy， this paper analyzed the methods of cultivating physician’s narrative literacy， providing references for modern medical education and practice， and assisting in the harmony and unity of science and technology and humanity.

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.

OBJECTIVE To investigate the reversal effect of Qingfei huayu jiedu formula （QFHYJDF） on drug resistance in non-small cell lung cancer （NSCLC） cells based on the microRNA-641 （miR-641）/extracellular signal-regulated kinase （ERK） signaling pathway. METHODS The human parental NSCLC cell line A549 was used to establish gefitinib-resistant cells A549/GR by combining concentration gradient increment with high-concentration pulse strategy. After screening for optimal intervention concentration and duration， the resistant cells were divided into a control serum group （treated with 20% blank serum for 48 h）， QFHYJDF-containing serum group （treated with 20% QFHYJDF-containing serum for 48 h）， and the normally cultured group （normally cultured for 48 h）. The cell relative viability， total apoptosis rate， as well as the expression levels of miR-641， neurofibromin 1 （NF1）， ERK1/2， and phosphorylated ERK1/2 （p-ERK1/2）， were assessed in each group. RESULTS Compared with the normally cultured group and the control serum group， the QFHYJDF-containing serum group exhibited significantly decreased cell relative viability and significantly increased total apoptosis rate （ P ＜0.05）. Moreover， the expression of NF1 protein was significantly up-regulated， while the expression levels of miR-641 and p-ERK1， p-ERK2 proteins were significantly down-regulated in the QFHYJDF-containing serum group （ P ＜0.05）. CONCLUSIONS QFHYJDF can inhibit proliferation and promote apoptosis of gefitinib-resistant lung cancer cells， which may be associated with up-regulating NF1 protein expression， down-regulating miR-641 expression， and inhibiting the activity of the ERK signaling pathway.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

The detection of coagulation function is helpful for the diagnosis of blood diseases,the assess-ment of bleeding and thrombus risks in patients,and the treatment of hemostasis and anticoagulation.It plays an important role in the diagnosis,treatment,and prevention of diseases.Solidification curve waveform analy-sis is a newly developed method for assessing coagulation function.It obtains more sensitive parameters for e-valuating the coagulation function of the body by taking the order derivative of the waveform reflecting the co-agulation process in routine coagulation experiments.Compared with traditional coagulation function tests,co-agulation cuvre waveform analysis curves is more comprehensive and effective in assessing the risk of bleeding and thrombosis.

AIM:To explore the mechanism of berberine on breast cancer cells based on network pharmacology and in vitro cell experiments.METH-ODS:Firstly,berberine and breast cancer were tak-en as the research objects,the intersection targets of the two were screened by VEEN diagram,GO function and KEGG enrichment analysis were per-formed by R language,and molecular docking and visualization were carried out by Autodock Vina and Pymol software.Then,berberine treated breast cancer MCF-7 cells for 24 h,and then in vi-tro cell experiments were performed.CCK-8 was used to detect cell viability,Edu and plate cloning were used to detect cell proliferation and cloning,and apoptosis was detected by An-nexin V-FITC/PI double staining and Western blot.Laser confocal and CETSA were used to verify the binding effect of berberine and AKT1 protein.RESULTS:The results of network pharmacology showed that berberine had a good binding to the core targets AKT1,AKT2 and MAPK3.Berberine(20,40,80 μmol/L)signifi-cantly inhibited the proliferation and cloning ability of MCF-7 cells in a concentration-dependent man-ner(P＜0.05,P＜0.01).The results of laser confocal and CETSA experiments showed that berberine and AKT1 had a binding effect,and the stability of the two was enhanced after the combination.CONCLU-SION:Berberine inhibits MCF-7 cell proliferation and induces apoptosis in human breast cancer cells by targeting binding to AKT1 protein.

Objective To analyze the differences and correlations of imaging parameters in patients with Parkinson's disease(PD)combined with cerebral small vessel disease(CSVD)with different cognitive functions based on MRI.Methods A retrospective selection was conducted on 192 PD patients combined with CSVD.According to the Montreal cognitive assessment(MoCA)and mini-mental state examination(MMSE)scores,they were divided into cognitive impairment PD group(n=69)and cognitive normal PD group(n=123),and the clinical data and MRI imaging parameters of the two groups were compared.Results The age and drinking history of the cog-nitive impairment PD group were higher than those of the cognitive normal PD group(P<0.05);the lacune of presumed vascular origin(LPVO)score,periventricular white matter hyperintensity(PVWMH)score,basal ganglia-perivascular space(BG-PVS)score,brain atrophy(BA)score,and CSVD total score in the cognitive impairment PD group were higher than those in the cognitive normal PD group(P<0.05),while there was no statistically significant difference in deep white matter hyperintensity(DWMH)score,cen-trum semiovale perivascular space(CS-PVS)score,and cerebral microbleed(CMB)score between the two groups(P>0.05);Multi-variate logistic analysis showed that age,LPVO score,BG-PVS score,BA score,and CSVD total score were independent influencing factors of cognitive impairment(P<0.05).Conclusion There are differences in imaging parameters such as LPVO score,PVWMH score,BG-PVS score,BA score,and CSVD total score among PD patients combined with CSVD with different cognitive functions,and they are correlated with MMSE and MoCA scores.