ObjectiveTo understand the development stages and use of policy tools of general practitioner policies in China since it was first proposed, to summarize the experience and explore the shortcomings, so as to provide references for the adjustment and optimization of China’s general practitioner policies. MethodsContent analysis and mathematical statistics analysis were used to conduct a quantitative research on 111 policy documents with 422 policy items involving general practitioners at the national level from 1997 to 2023, through a three-dimensional analysis framework integrating policy tools, human capital process and policy development stages. ResultsCapacity‑building policy tools were most frequently used in general practitioner policies, and the policy tools gradually shifted from mandate to inducement. The general practitioner policies paid less attention to the career selection link, but paid full attention to every segment of human capital links, with a comprehensive application of policy tools observed in the integrated development stage, despite the existence of unbalanced internal distribution. ConclusionIt is suggested to promote the use of incentive policy tools and to explore multiple approaches based on incentive theory; pay attention to the career selection link for guiding the employment of general practitioners; take the appropriateness between the policy tools and human capital process into comprehensive consideration, striking a dynamic balance of the internal structure of general practitioner policies.

ObjectiveTo analyze the characteristics of policy texts related to the physician periodic assessment system in China, providing references for the improvement of the system. MethodsContent analysis was employed, examining 116 policy documents from three dimensions: policy process, policy themes, and policy tools. ResultsA total of 298 codes were obtained. The number of policies related to the periodic assessment of physicians showed an overall trend of increasing first and then decreasing, with the peak annual issuance period between 2011 and 2021, and the average number of policy texts showing a downward trend. Policy documents were summarized into 3 levels: physician periodic assessment work, individual behavior, and institutional systems, encompassing a total of 8 categories of themes. The proportion of supply-oriented, environmental-oriented, and demand-oriented policy tools were 4.03%, 60.40%, and 35.57%, respectively. Moreover, environmental-oriented tools continued to dominate over time, followed by demand-oriented tools, with supply-oriented tools being the least. ConclusionThe policy themes are relatively broad and difficult to implement, focusing on establishing regulations while neglecting resource provision, and failing to continuously improve the construction of the system. It is recommended to clearly define the scope of the periodic assessment management, improve supporting systems, increase resource supply, and continuously promote the execution of assessments and policy revisions.

OBJECTIVE To analyze and identify the metabolites of pirtobrutinib （PTN） in rats， and clarify the possible metabolic pathways of PTN in rats. METHODS Six rats were intragastrically administered with 10 mg/kg PTN suspension. Blood samples were collected from the rats 30 minutes before administration and at 0.25， 0.5， 1， 2， 4， 6， 8， 12， 24 hours after administration. Urine and feces samples were collected 12 hours before administration and 24 hours after administration. UHPLC- Orbitrap Exploris 240 system combined with Compound Discoverer 3.0 and Xcalibur 2.0 software were adopted for structural identification and metabolic pathway analysis of PTN metabolites in rat plasma， urine， and feces. RESULTS A total of 29 PTN metabolites were identified， including 17， 19 and 22 metabolites in plasma， urine and feces， respectively. The metabolic pathways of PTN mainly included oxidation， sulfation， glucuronidation， etc.， and its metabolites were mostly combination products of two or more different metabolic forms. In detail， a total of 26 metabolites were associated with phase Ⅰ metabolic reactions （14 oxidation metabolites， 9 reduction/dehydrogenation metabolites， 8 demethylation metabolites， and 5 hydrolysis metabolites）. Meanwhile， a total of 20 products were involved in phase Ⅱ metabolites （14 sulfation metabolites and 8 glucuronic acid binding metabolites）. CONCLUSIONS PTN exhibits a diverse range of metabolites in rat fecal samples， with the primary metabolic pathways being oxidation， sulfation， glucuronidation， and others.

Polycystic ovary syndrome （PCOS） is a common gynecological endocrine and reproductive disorder，with the main clinical manifestations including ovulation failure，insulin resistance，hyperandrogenism，and obesity. Its occurrence and development are closely related to cellular regulatory mechanisms such as apoptosis，autophagy，oxidative stress，and inflammatory response. Autophagy，as a clearance mechanism that maintains cellular homeostasis，plays a crucial role in maintaining the growth，development，and maturation of oocytes. Exploring the mechanism of autophagy during the occurrence and development of diseases can help develop treatment methods for PCOS by regulating autophagy. Studies have shown that autophagy plays an important role in the pathogenesis of PCOS，and it can affect the occurrence and development of PCOS through multiple pathways，levels，and targets. Traditional Chinese medicine （TCM） regulates autophagy in ovarian granulosa cells or endometrium of patients with PCOS by targeting the expression of autophagy signaling pathways，regulatory factors，and non-coding single-stranded RNA molecules，thereby alleviating inflammation，regulating metabolism disorders，and balancing hormone levels in PCOS. Accordingly，TCM can ameliorate pathological conditions such as insulin resistance，hyperandrogenism，and ovulation failure in PCOS. This article summarizes the TCM formulas and extracts for the treatment of PCOS，as well as the main autophagy pathways and regulatory factors involved，aiming to provide reference and suggestions for the future treatment of PCOS with TCM by regulating autophagy.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Objective To investigate the correlation between total oxidation state(TOS),superoxide dis-mutase(SOD),glutathione reductase(GR)and androgen receptor(AR)expression,as well as their predictive value for castration-resistant prostate cancer(CRPC).Methods A retrospective analysis was conducted on the clinical data of 382 patients with prostate cancer who received endocrine therapy in our hospital from Janu-ary 2021 to March 2023.These patients were divided into a CRPC group(91 cases)and a non-CRPC group(291 cases)based on whether they progressed to CRPC within one year.The clinical data of the two groups were compared,and the levels of TOS,SOD,GR,and AR expression before and after treatment were com-pared between the two groups.The correlation between TOS,SOD,GR,and AR expression was analyzed using the Spearman method.The relationship between TOS,SOD,GR,and AR expression in the CRPC group was analyzed using partial correlation analysis.Logistic regression analysis was used to investigate the impact of TOS,SOD,and GR on the occurrence of CRPC after 1 month of treatment,and receiver operating charac-teristic(ROC)curve analysis was used to evaluate the predictive efficacy of TOS,SOD,and GR on CRPC af-ter 1 month of treatment.Results Gleason score ≥8 and T4 in clinical stage in CRPC group were higher than those in non-CRPC group,and the difference was statistically significant(P＜0.05).After 1 month and 1 year of treatment,the positive expression rates of TOS and AR in both groups were higher than before treatment,while the levels of SOD and GR were lower than before treatment,with a statistically significant difference(P＜0.05).After 1 month and 1 year of treatment,the TOS level and AR positive expression rate in the CRPC group were higher than those in the non-CRPC group,while the SOD and GR levels were lower than those in the non-CRPC group,with statistical significance(P＜0.05).Spearman correlation analysis showed that TOS was positively correlated with AR expression in the CRPC group after 1 month and 1 year of treat-ment(P＜0.05),while SOD and GR were negatively correlated with AR expression(P＜0.05).Logistic re-gression analysis showed that,Gleason score ≥8,T4 in clinical stage,and TOS,SOD,and GR after 1 month of treatment were all associated with the occurrence of CRPC(P＜0.05).It was found that after adjusting for Gleason score and clinical stage,TOS,SOD,and GR were still independent factors for CRPC after 1 month of treatment(P＜0.05).The ROC curve analysis results showed that the area under the curve of TOS,SOD,and GR combined to predict CRPC after 1 month of treatment was 0.938(95％CI:0.908-0.960),which was higher than that of each indicator alone.Conclusion The expression of TOS,SOD,GR,and AR is correlated to some extent,and combined detection has certain predictive value for CRPC.It can be used as an auxiliary indicator for clinical prediction of CRPC and has certain guiding value for subsequent clinical decisions for patients.

In order to realize the quantitative assessment of muscle strength in hand function rehabilitation and then formulate scientific and effective rehabilitation training strategies, this paper constructs a multi-scale convolutional neural network (MSCNN) - convolutional block attention module (CBAM) - bidirectional long short-term memory network (BiLSTM) muscle strength prediction model to fully explore the spatial and temporal features of the data and simultaneously suppress useless features, and finally achieve the improvement of the accuracy of the muscle strength prediction model. To verify the effectiveness of the model proposed in this paper, the model in this paper is compared with traditional models such as support vector machine (SVM), random forest (RF), convolutional neural network (CNN), CNN - squeeze excitation network (SENet), MSCNN-CBAM and MSCNN-BiLSTM, and the effect of muscle strength prediction by each model is investigated when the hand force application changes from 40% of the maximum voluntary contraction force (MVC) to 60% of the MVC. The research results show that as the hand force application increases, the effect of the muscle strength prediction model becomes worse. Then the ablation experiment is used to analyze the influence degree of each module on the muscle strength prediction result, and it is found that the CBAM module plays a key role in the model. Therefore, by using the model in this article, the accuracy of muscle strength prediction can be effectively improved, and the characteristics and laws of hand muscle activities can be deeply understood, providing assistance for further exploring the mechanism of hand functions .
Neural Networks, Computer ; Humans ; Hand Strength/physiology* ; Support Vector Machine ; Muscle Strength/physiology* ; Hand/physiology* ; Convolutional Neural Networks

Objective To investigate the learning curve of CT-guided percutaneous lung biopsy.Methods Using cumulative sum(CUSUM)analysis method,the clinical data from 110 patients,who underwent CT-guided percutaneous lung biopsy performed by the same physician at the First Affiliated Hospital of Zhengzhou University of China between May 2024 and October 2024,were retrospectively analyzed.The CUSUM learning curve was fitted,and R2 was used to assess the goodness of fit.The baseline and perioperative data were compared between different stages of the learning curve so as to determine the number of accomplished surgical cases that was required for a physician to reach the proficiency stage from the learning stage in performing CT-guided percutaneous lung biopsy.Results Successful CT-guided percutaneous lung biopsy was accomplished in all patients,with a mean operation time of(20.2+3.4)minutes(range of 15-29 minutes).With the accumulation of surgical cases,the operation time showed a gradual downward trend.The learning curve was best fitted with a cubic equation,the equation was as follows:CUSUM(110)=0.000 3x3-0.081 3x2+5.597 9x+0.774 3(where x representing the number of cases),with a goodness-of-fit coefficient R2=0.991.The fitted curve reached its peak at the performance of the 46th case,which was used as the cutoff point to divide the learning curve into two phases.Compared with the learning phase,in the proficiency phase the incidence of complications was significantly lower(pneumothorax:18.8％vs 37.0％,P=0.033)and the mean operation time was obviously shorter[(18.33+2.31)min vs(22.80±3.02)min,P＜0.001].Conclusion Through precise CUSUM analysis of the learning curves obtained from 110 patients receiving CT-guided percutaneous lung biopsy,the results of this study indicates that it requires to accomplish 46 operations before a physician can skillfully master the technique of CT-guided percutaneous lung biopsy.

OBJECTIVE To evaluate the cost-effectiveness of finerenone combined with standard of care （SoC） in the treatment of heart failure with mildly reduced ejection fraction （HFmrEF） or preserved ejection fraction （HFpEF）. METHODS Based on a phase Ⅲ clinical trial， a Markov model was constructed from the perspective of China’s healthcare system to compare the treatment outcomes of finerenone combined with SoC regimen versus SoC regimen alone in the treatment of different cardiac functional statuses of HFmrEF/HFpEF. Using quality-adjusted life year （QALY） as the health output index， 3 times China’s per capita GDP in 2023 as the willingness-to-pay （WTP） threshold， a simulation was conducted with a 3-month cycle length and a 10- year time horizon， incorporating an annual discount rate of 5%. The dynamic changes across various stages of HFmrEF/HFpEF treated with finerenone combined with SoC versus SoC alone were simulated to evaluate the long-term effectiveness and costs of the two treatment strategies. Additionally， one-way sensitivity analysis and probabilistic sensitivity analysis were performed， to test the robustness of the results. RESULTS The incremental cost-effectiveness ratio （ICER） of the finerenone combined with SoC regimen versus SoC regimen alone was 179 504.75 yuan/QALY， which was below the WTP threshold set in this study， indicating that the finerenone combined with SoC regimen possessed certain economic advantages. The results of one-way sensitivity analysis showed that the utility value of NYHA Ⅱ status， the drug price of finerenone， the discount rate， and the probability of hospital transfer for both groups had a great influence on ICER， but did not affect the robustness of the model. The probabilistic sensitivity analysis also confirmed the robustness of the model. CONCLUSIONS Under the WTP threshold set in this study， finerenone combined with SoC is cost-effective in the treatment of HFmrEF/HFpEF， compared with the SoC regimen.

OBJECTIVE To analyze the correlation of the peak blood concentration （cmax） of compound sulfamethoxazole （TMP/SMZ） and its metabolite N-acetyl sulfamethoxazole （NSMZ） with clinical efficacy and adverse reactions in critically ill patients. METHODS The data of critically ill patients treated with TMP/SMZ in various ICU of Hainan General Hospital from December 2023 to January 2025 were retrospectively collected. The patients were divided into success group and failure group based on the treatment outcome. Simple linear regression and Spearman correlation analysis were used to analyze the correlation of TMP cmax， SMZ cmax， and NSMZ cmax with clinical efficacy and adverse reactions. The receiver operating characteristic curve （ROC） was used to determine the cutoff values of cmax for predicting the occurrence of adverse reactions. RESULTS Among critically ill patients with an acute physiology and chronic health evaluation Ⅱ （APACHE-Ⅱ） ≥15 points 24 h of check-in at ICU， SMZ cmax of success group was significantly higher than failure group （P＜0.05）. The daily total dose of TMP/SMZ was positively correlated with TMP cmax and SMZ cmax（ P＜0.05）. TMP cmax was significantly correlated with hepatotoxicity and nephrotoxicity， SMZ cmax with hepatotoxicity， and NSMZ cmax with nephrotoxicity （P＜0.05）. The cutoff values of TMP cmax for predicting nephrotoxicity and hepatotoxicity were 7.25 μg/mL and 6.63 μg/mL， respectively. The cutoff value of SMZ cmax for predicting hepatotoxicity was 138.00 μg/mL， and that of NSMZ cmax for predicting nephrotoxicity was 60.76 μg/mL. CONCLUSIONS Among critically ill patients with an APACHE-Ⅱ ≥15 points 24 h of check-in at ICU， SMZ cmax is associated with treatment success. Hepatotoxicity risk significantly increases when TMP cmax ≥6.63 μg/mL or SMZ cmax ≥138.00 μg/mL； nephrotoxicity risk significantly increases when TMP cmax ≥7.25 μg/mL or NSMZ cmax ≥60.76 μg/mL.