Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

Objective To establish,evaluate and validate the Nomogram prediction model of radiation pneumonitis(RP)in intensity modulated radiotherapy(IMRT)with TCM syndrome elements.Methods 257 patients with locally advanved non-small cell lung cancer receiving IMRT were analyzed retrospectively.The total population was randomly divided into a training set and a validation set by 7:3.A prediction model was established by Lasso-Logistic regression analysis,and then visualized by Nomogram to evaluate and validate the model.Results Independent risk factors included in the prediction model included tumor stage(OR=6.576;P=0.003),position(OR=2.935;P=0.016),MLD of the affected lung(OR=1.001;P<0.001)and Yin deficiency(OR=3.861;P=0.003).Based on the above factors,the prediction model was constructed and visualized.The C-index of the training set and the validation set were 0.865 and 0.867,respectively.The calibration curves of the two sets had a good fit and had certain clinical usefulness.Conclusion Based on the clinical elements of Chinese and Western medicine,tumor stage,position,lung MLD and Yin deficiency,the model can accurately predict the occurrence of≥grade 2 RP,and provide a reference for clinical screening of high-risk patients and further improvement of treatment plan.

Objective:To construct an indicator system for a nursing science and technology innovation curriculum guided by innovation competence, in order to provide a reference for cultivating innovation ability in nursing students.Methods:The overall research period was from March to December 2024. A nursing innovation curriculum indicator framework was initially developed through literature analysis and brainstorming. From October to December 2024, 19 experts from nine hospitals or universities across five provinces and cities were selected via purposive sampling to participate in two rounds of Delphi consultation. Revisions were made based on expert feedback.Results:Both rounds of expert consultation achieved a 100% response rate. The authority coefficient of the experts was 0.92. The final indicator system included four curriculum elements: course content, course objectives, teaching methods, and assessment, encompassing 14 first-level indicators and 40 second-level indicators.Conclusions:The innovation-oriented indicator system for nursing science and technology education demonstrates good scientific validity and reliability. It offers a foundational framework for advancing innovation-focused nursing education and curriculum design.

Objective:To determine the epidemic characteristics of polymyxin resistance ( mcr) genes of Enterobacteriales colonized in patients admitted to hospitals in Zhejiang, Henan, Gansu and Shandong provinces in China in 2023. Methods:A comprehensive collection of 667 fecal specimens from patients admitted to five medical facilities across the provinces of Zhejiang, Henan, Gansu, and Shandong in 2023 was collected. Epidemiological characteristics of Enterobacteriales bacteria positive for the mcr gene were examined, employing techniques such as microbial culturing, using agarose gel electrophoresis, PCR, whole-genome sequencing, bioinformatics analysis, and the induction of antimicrobial resistance. Statistical analysis was subsequently applied to the gathered data. Results:Among 667 fecal samples from admitted patients, five samples were positive for mcr gene, with a carrier rate of 0.75%(5/667), and from two of the samples, two different strains carrying the mcr gene were isolated, respectively. A total of seven strains of Enterobacteriales carrying the mcr gene were detected, of which four strains carried mcr-1 gene and three strains carried mcr-9 gene. The positive isolates included three strains of Escherichia coli, one strain of Citrobacter braakii, Citrobacter freundii, one strain of Klebsiella pneumoniae, and one strain of Enterobacter hormaechei. The seven mcr positive strains were isolated from two distinct geographical locations within China, with four from Zhejiang Province and three from Henan Province. After whole-genome sequencing, it was found that the 16S rRNA sequences of the three strains of mcr-1 positive Escherichia coli had high homology. The three isolates of mcr-9 positive strains preserved a significant degree of homology within the mcr-9 and wbuC regions. Following polymyxin exposure, there was a marked difference in the growth kinetics of the ZJ-307, HN-11-1, and HN-135 strains post-induction compared to their pre-induction growth rates, and their motility capacity was reduced. Conclusions:The prevalence of Enterobacteriales harboring the mcr gene is minimal among hospitalized patients. However, it is noteworthy that these genes are prone to horizontal transfer. They can move into drug-resistant strains, which may have elevate minimum inhibitory concentration(MIC). Resistance to polymyxin can alter the bacterial growth rate and motility, potentially impacting the MIC of other antibiotics, thereby complicating clinical management. Consequently, it is imperative to focus on the proactive screening of susceptible populations to prevent the further dissemination of plasmid-mediated polymyxin resistance among clinically significant gram-negative bacterial pathogens.

Objective To develop and validate a deep learning-based segmentation model for low-dose cervical spine X-ray,aiming to address the insufficient segmentation accuracy in low-dose protocols while balancing radiation protection and diagnostic accuracy.Methods A total of 1 363 patients cervical spine X-ray images data were collected.A dose-attenuation mathematical simulation sys-tem was constructed to generate 14 122 dynamic low-dose cervical spine images incorporating quantum noise,contrast degradation,and blur artifacts.A neural network model was developed for automated segmentation of low-dose cervical spine X-ray using this dataset.Results Within the dose range of 50%to 7.5%,the average reults of automatic segmentation by the neural network model and manual segmentation for each group were as follows:50%dose group,intersection over union(IoU)=0.98 vs 0.93(P=0.707)and Dice coefficient(Dice)=0.99 vs 0.96(P=0.749);10%dose group,IoU=0.97 vs 0.87(P=0.201)and Dice=0.99 vs 0.93(P=0.219);7.5%dose group,IoU=0.97 vs 0.67(P<0.01)and Dice=0.98 vs 0.80(P<0.01).Conclusion The developed deep learning model achieved robust cervical spine segmentation(IoU>0.96,Dice>0.98)below diagnostic dose thresholds[peak signal-to-noise ratio(PSNR)<38 dB,structural similarity index(SSIM)<0.65].Under ultra-low-dose conditions(PSNR=27.710 dB,SSIM=0.274),it demonstrated a 44.78%IoU improvement and 22.5%Dice improvement over manual segmentation.This model enables minimal radia-tion exposure while preserving diagnostic performance,confirming its theoretical feasibility for low-dose X-ray image analysis and clinical research potential.

Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, has been recently identified as a key role in Parkinson's disease (PD) pathogenesis. In particular, lipid peroxidation-mediated ferroptosis is considered a key event leading to the death of dopaminergic neurons. This article reviews the role of lipid peroxidation-mediated ferroptosis in PD and its involved key signaling pathways, and explores the related targeted therapeutic strategies, with the aim of providing new ideas for targeted treatment of PD.

A 36-year-old male patient presented with repeated myocardial infarction. Despite regular dual-antiplatelet therapy and intensive lipid-lowering therapy, he still experienced restenosis after coronary stent implantation. He then transferred to the Zhongshan Hospital, Fudan University. According to the disease history, combined with coronary artery inflammation observed by PET/CT and effective anti-inflammatory treatment, he was finally diagnosed with Behçet’s disease (BD) combined with isolated coronary arteritis. BD has been included in the Chinese Second Catalog of Rare Diseases, and the disease that only involves the coronary arteries is even rarer, which makes it very easy to misdiagnose and underdiagnosis in clinical practice. Strengthening the understanding of the complex clinical phenotypes of various vasculitis, attaching importance to multidisciplinary consultation, and dynamically following up are of great value for the early diagnosis of this disease.

BACKGROUND:In recent years,improving the health of skeletal muscles through exercise has become an important research concern for scholars.Appropriate exercise has a positive effect on skeletal muscles.Among them,how to activate the sphingosine kinase1(SphK1)/sphingosine-1-phase(S1P)/sphingosine-1-phase receptor2(S1PR2)signaling pathway during exercise so as to improve the health of skeletal muscles is receiving attention from researchers. OBJECTIVE:To investigate how exercise improves the health of skeletal muscles through the SphK1/S1P/S1PR2 signaling pathway,and to explore new methods for treating related muscle diseases in order to improve human skeletal muscle health. METHODS:The first author searched for relevant literature from the establishment of the database to the present in the Web of Science,PubMed,CNKI,WanFang,and VIP databases.The search terms were"signaling pathway,SphK1,S1P,S1PR2,skeletal muscle,satellite cell,myogenesis,exercise"in Chinese and English.Finally,69 articles were included for review and analysis. RESULTS AND CONCLUSION:The SphK1/S1P/S1PR2 signaling pathway is a complex regulatory network that triggers downstream signal transduction processes by SphK1 to catalyze the interaction between S1P and receptors such as S1PR2,thereby regulating multiple biological functions of cells,tissues,organs,and systems.The SphK1/S1P/S1PR2 signaling pathway can regulate satellite cell proliferation and myoblast differentiation,improving myogenesis.The physiological basis of the SphK1/S1P/S1PR2 signaling pathway and the potential impact of exercise on it were analyzed through literature research.Acute aerobic exercise can increase the expression of SphK1 in skeletal muscle.Both human and animal studies have confirmed that acute and long-term exercise can increase the expression of S1P in skeletal muscle.In addition,studies have shown that long-term resistance exercise can increase the expression of S1PR2 in skeletal muscle.Some experimental results indicate that acute and long-term exercise have no significant effect on muscle or blood S1P levels,and the reason for different results may be due to different research subjects,methods,intensities,and frequencies selected,while the specific mechanism is not yet clear.Research suggests that exercise can promote the expression of the SphK1/S1P/S1PR2 signaling pathway in skeletal muscle and regulate downstream related signaling pathways.Research on this signaling pathway may provide new strategies and methods for the treatment of skeletal muscle diseases,thereby improving skeletal muscle health.In the future,we should deepen the research on the association between SphK1/S1P/S1PR2 signaling pathway and skeletal muscle health,further reveal its regulatory relationship with satellite cells and myoblasts as well as its interactions with the upstream and downstream pathways,explore its clinical application value,take into account the changes of this pathway when formulating the rehabilitation program,explore the specific mechanisms by which different types of exercise affect the SphK1/S1P/S1PR2 signaling pathway in skeletal muscles,and use the SphK1/S1P/S1PR2 signaling pathway as a potential therapeutic target for diseases.Further development and application of human muscle models should be developed to improve research depth and accuracy.

As a novel long-acting glucagon-like peptide-1 （GLP-1） receptor agonist， semaglutide plays a pivotal role in the treatment of obesity and related metabolic diseases. This article systematically reviews the research progress of semaglutide in the treatment of obesity and related metabolic diseases from three aspects： mechanism of action， clinical applications， and existing challenges. It is found that its mechanism of action involves multi-organ synergistic regulation and metabolic intervention. Its clinical applications encompass the treatment of obesity， diabetes， polycystic ovary syndrome， and liver-related metabolic syndromes， and it demonstrates groundbreaking value in cardiovascular and renal protection. However， it still faces multiple challenges in terms of adverse reactions， individualized treatment， economic accessibility， ethical controversies， and risks. In the future， it is essential to further accumulate long-term safety data on semaglutide， optimize combination treatment regimens， and address key issues such as individualized medication for special populations， in order to fully realize its clinical application value.