Objective: To identify the latent classes of acceptance and striving and their associated factors among nursing students, and to examine the mediating role of positive acceptance and striving in the association between self transcendence and subjective well being, so as to provide evidence for targeted interventions to improve subjective well being among nursing students. Methods: From July to October 2025, a convenience sample of 861 nursing students was recruited from five schools in Sichuan and Chongqing, China. Participants were surveyed using the Self transcendence Scale, the Positive Acceptance and Striving Scale, and the General Well being Scale. Latent profile analysis was conducted to identify profiles of positive acceptance and striving. Logistic regression analysis was used to examine associated factors, and relative mediation analysis was performed to assess differences in the mediating effect across latent profiles. Results: Three latent classes of acceptance and striving were identified: the low acceptance-low striving profile (46.34%, n =399), the moderate acceptance-moderate striving profile (40.88%, n =352), and the high acceptance-high striving profile (12.78%, n =110). Multivariable Logistic regression analysis showed that, with the low acceptance-low striving profile as the reference, nursing students with higher self transcendence scores ( OR =151.85) and those who studied nursing because of personal preference ( OR =14.72) or parental expectations ( OR =11.16) were more likely to be classified into the high acceptance-high striving profile (all P <0.05). Male students ( OR =0.19), those perceiving nurses social status as average ( OR =0.35), and those receiving moderate teacher support ( OR =0.23) were less likely to be classified into the high acceptance-high striving profile (all P <0.05). Positive acceptance and striving partially mediated the association between self transcendence and subjective well being, with a total effect of β =0.97 and a mediating effect of β =0.48; the mediating effect accounted for 49.34% of the total effect. Relative mediation analysis showed that the mediating effect was statistically significant only in the low acceptance-low striving profile ( β =0.21), whereas the direct effects were stronger in the moderate acceptance-moderate striving and high acceptance-high striving profiles ( β =0.39, 1.06)(all P <0.05). Conclusions Positive acceptance and striving among nursing students exhibit substantial heterogeneity. Its predictive effect on subjective well being and the underlying mediating mechanism vary across latent profiles. Profile specific interventions should therefore be implemented to improve subjective well being among nursing students.

Objective:To clarify the changes in incidence and mortality of various cancers based on analysis on registration data of malignant tumor incidence and mortality from Dehui City and Yanji City in Jilin Province.Methods:The incidence and mortality data of malignant tumors from 2009 to 2016 in Dehui City and Yanji City in Jilin Province,were collected from the Chinese Cancer Registry Annual Report published by the National Cancer Center.The number of cases,deaths,crude incidence rate,crude mortality rate,age-standardized incidence rate(ASIR),age-standardized mortality rate(ASMR),and annual percentage change(APC)of the malignant tumors were analyzed by cancer sites and genders.Results:From 2009 to 2016,the CIR of malignant tumors in Dehui City(APC=1.2%,P=0.019)and Yanji City(APC=3.6%,P=0.058)showed an increasing trend.After standard population age adjustment,the ASIR in males in Dehui City showed a significant decline(APC=-5.7%,P=0.021),while the ASIR in females exhibited an overall downward trend,but the difference was not significant(APC=-2.2%,P=0.111).In Yanji City,the ASIR in males(APC=-1.4%,P=0.535)and females(APC=0.0%,P=0.988)showed no significant changes.The CMR of malignant tumors in Dehui City(APC=1.9%,P=0.001)and Yanji City(APC=5.9%,P=0.001)showed a continuous upward trend.After age-standardization,the ASMR in males(APC=-3.1%,P=0.100)and females(APC=-4.2%,P=0.053)in Dehui City,as well as in males(APC=-1.3%,P=0.438)in Yanji City,showed a slight downward trend.Although the ASMR in females in Yanji City showed a slight increase,the difference was not statistically significant(APC=0.5%,P=0.838).In 2016,the most common malignant tumor in terms of both incidence and mortality in Dehui City was lung cancer,with a CIR of 60.76/100 000 and a CMR of 46.96/100 000.In Yanji City,the most common malignant tumor was liver cancer,with a CIR of 49.04/100 000 and a CMR of 51.09/100 000.Conclusion:Lung cancer,liver cancer,and gastric cancer are the major malignant tumors threatening residents in Dehui City,Yanji City,and even the entire Jilin Province,and should be prioritized in cancer prevention and control efforts.Early diagnosis and treatment should be strengthened.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Premature ovarian insufficiency(POI)is a disease that seriously affects the health and life of women,which is also one of the main causes of female infertility.The incidence of POI is increasing in recent years.The diagnostic criteria of POI are not uniform,and different diagnostic criteria have inconsistent thresholds for various indicators.Strict diagnostic criteria are more conducive to early detection and treatment of POI.At present,complementary and alternative therapies such as traditional Chinese medicine,acupuncture and moxibustion are widely used in the treatment of POI.This article reviewed the recent studies on the complementary and alternative therapy of traditional Chinese medicine in the treatment of POI,and finds that the dialectical treatment of traditional Chinese medicine is based on the perspective of traditional Chinese medicine theory and puts forward corresponding treatment plans for different dialectical types.For example,treatment from the kidney,tonifying kidney filling essence,regulating chongren;Treatment from the liver,soothing the liver,regulating qi,nourishing blood and softening the liver;Treatment from the heart and spleen,nourishing Yangming,tonifying the spleen and nourishing the heart.In terms of acupuncture treatment,regulating menstruation and promoting pregnancy and regulating the conception vessel and toning the governor vessel and toning the kidney are often used to treat POI.In addition,moxibustion regulates body function by stimulating the bladder meridian and conception vessel and governor vessel acupoints.Other methods,such as ear acupoint bean-pressing,acupoint thread-embedding and acupoint injection,have also shown potential in the treatment of POI.This article summarizes the role and characteristics of traditional Chinese medicine in the treatment of POI,in order to provide ideas and basis for clinical treatment of POI.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

To analyze the epidemiological characteristics of COVID-19 in Fujian Province from the 49th week of 2022 to the 5th week of 2023,after further optimization of China's COVID-19 prevention and control measures on December 7,2022(the 49th week of 2022),this study used multi-dimensional surveillance data to dynamically assess population infection levels and their changing trends.The aim of the study was to provide a scientific basis for early warning of epidemic risk,medical resource allocation,and evalu-ation of socio-economic impact.A multi-source data surveillance system was constructed,encompassing surveillance of fever clinics at medical institutions(weekly collection of visits,positive nucleic acid and antigen test results,inpatients,and severe cases in sec-ondary or above hospitals),population nucleic acid test monitoring(weekly person-times and positivity rates of single-tube tests from the provincial system),sentinel hospital monitoring(weekly proportion of influenza-like illness visits at 18 sentinel hospitals and re-lated viral testing data),and monitoring of novel coronavirus variants(weekly systematic collection of genomic sequences of local and imported cases).Line charts were plotted weekly,and time series analysis,molecular epidemiological methods,and an improved SEIAR model were used to simulate epidemic spread.During the study period,the COVID-19 epidemic in Fujian Province exhibited three distinct stages.In the infection peak stage(52nd week of 2022),the provincial fever clinic visits reached 606 893 person-times,and a 49.2%positivity rate in population single-tube nucleic acid tests and 63.8%positivity rate in sentinel hospital monitoring were observed.In the medical load peak stage(2nd week of 2023),274 460 inpatients and 28 487 severe cases were recorded.In the epidemic decline stage(4th to 5th weeks of 2023),fever clinic visits decreased by 96.3%with respect to the peak,the single-tube nucleic acid test positivity rate decreased to 6.3%,and the sentinel hospital COVID-19 nucleic acid test positivity rate was 6.4%.All 508 sequenced local cases were Omicron variants,predominantly BA.5.2 and its sub-lineages(67.4%).Among 56 imported se-quenced cases,BA.5.2 and its sub-lineages accounted for 50.0%,and 16.1%comprised nine variants of interest including XBB and BQ.The model predicted the infection peak in the 52nd week of 2022,whereas the hospitalization peak lagged by approximately 10.6 days.Multi-source data monitoring revealed a three-stage development of the COVID-19 epidemic in Fujian.The BA.5.2 strain was dominant during the epidemic.The combination of multi-source monitoring data and modeling provides important references for epi-demic prevention and control,and highlights the need to improve the monitoring system in follow-up.

OBJECTIVE To investigate the clinical characteristics of drug-induced liver injury （DILI） induced by glucagon- like peptide-1 receptor agonists （GLP-1RAs）， and to provide a reference for safe clinical medication. METHODS Using search terms such as “GLP-1”“GLP-1RAs”“semaglutide” “drug-induced liver injury”， relevant studies from PubMed， Embase， the Cochrane Library， CNKI， Wanfang Data and VIP were retrieved. Descriptive analysis was performed on cases of DILI induced by GLP-1RAs. RESULTS A total of 11 studies， comprising 11 patients， were included. Among them， 4 were male （36.4%） and 7 were female （63.6%）. Patient ages ranged from 17 to 64 years； 5 patients （45.5%） were between 50 and 65 years old. Six patients were treated for diabetes， and five for weight loss. Ten patients had underlying diseases. The shortest time to the onset of DILI was 5 days after medication， while the longest was approximately 180 days. The DILIs induced by GLP-1RAs were mainly hepatocellular injury type （6 cases）； severity levels included severe （3 cases）， moderate （6 cases）， and mild （2 cases）. Gastrointestinal symptoms and jaundice were the most common clinical manifestations. The association between DILI and GLP- 1RAs was assessed as “probable” in 10 cases and “possible” in 1 case. All 11 patients improved after drug discontinuation and （or） corresponding treatment. CONCLUSIONS DILI induced by GLP-1RAs is relatively concentrated in patients aged 50-65， with a higher incidence in females. The risk may be further increased in patients with underlying diseases. Clinical use of these agents should enhance pharmaceutical care， including identification of high-risk populations and patient education （especially symptom recognition）. When relevant symptoms appear， the drug should be discontinued immediately， with liver-protective therapy initiated when necessary， to ensure patient safety of drug use.