Background: and Purpose Live cell-based assays (LCBA) are increasingly used for serological antibody detection due to their ability to preserve antigen conformation, offering moderately higher sensitivity than fixed cell-based assays. However, the clinical necessity of prioritizing LCBA for the detection of aquaporin-4 immunoglobulin G (AQP4-IgG) in neuromyelitis optica spectrum disorder (NMOSD) remains unclear, especially when compared to its established role in diagnosing myelin oligodendrocyte glycoprotein antibody-associated disease. Methods: We compared the performance of live cell-based assays using immunofluorescence (LCBA-IF) and fixed cell-based assays using immunofluorescence (FCBA-IF) in detecting AQP4-IgG in 90 cases of NMOSD meeting 2015 International Panel for Neuromyelitis Optica Diagnosis criteria, alongside 40 controls. Additionally, we further investigated the relationship between AQP4-IgG titers as measured by LCBA-IF and FCBA-IF and clinical parameters in NMOSD patients. Results: Results showed 96.9% agreement between LCBA-IF and FCBA-IF (Cohen’s κ=0.935), with a strong Spearman correlation (0.977, p<0.001). Both methods demonstrated 100% specificity, with LCBA-IF showing slightly higher sensitivity compared to FCBA-IF. Within LCBAIF-tested groups, statistically significant differences in annualized relapse rates were observed across all pairwise comparisons (low-titer vs. moderate-titer, low-titer vs. high-titer, and moderate-titer vs. high-titer; all p<0.050). However, this association reached statistical significance in some FCBA-IF-tested groups. Conclusions Overall, there is a strong concordance between LCBA-IF and FCBA-IF in detecting AQP4-IgG, where LCBA-IF shows slightly higher sensitivity. Furthermore, there is a potential link between elevated AQP4-IgG titers and an increased risk of relapse, and this correlation may appear more pronounced when using LCBA-IF.

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.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The therapeutic concept of amblyopia has gradually shifted from improving the visual acuity of the amblyopic eye to restoring binocular visual function.Conventional occlusion therapy and routine visual training have issues such as long treatment cycles, insufficient entertainment value and poor patient compliance, which limits the stability of therapeutic effects. Virtual reality(VR)technology, characterized by immersion, interactivity, and adjustable stimulus parameters, has been increasingly applied to visual training for amblyopia.Current evidence suggests that VR-based training can improve visual acuity and binocular visual function in amblyopia patients to a certain extent.Moreover, its gamified interactions and feedback-driven design may also enhance patient motivation and treatment adherence. This review begins with the mechanisms and theoretical basis of VR training for amblyopia, proceeds to summarizeits advantages over conventional methods, current systems, training modes, clinical efficacy, commonly used outcome measures, as well as safety and acceptability, aiming to provide a reference for its standardization, clinical translation, and widespread adoption.

Objective To prepare in-house coagulation factor Ⅷ(F Ⅷ)inhibitor-positive control material and evaluate its perform-ance.Methods Frozen plasma samples from hemophilia A patients with positive factor Ⅷ inhibitors were pooled,and diluted with Owren's Veronal Buffer(OVB)to 1 BU/mL of the inhibitor concentration in the mixture,then aliquoted and freeze-stored.The homo-geneity and stability of the in-house quality control material were verified,and its suitability was further assessed through intra-laborato-ry reproducibility among different technologists and inter-laboratory comparisons.Results Twenty-one aliquots were randomly tested for homogeneity assessment,yielding an average of 1.05 BU/mL(range 0.9-1.15 BU/mL),with a standard deviation(SD)of 0.083 and coefficient of variation(CV)of 7.90％.The freshly prepared inhibitor-positive control samples contained a concentration of 1.03 BU/mL.After storage at-80℃ for 24 hours,1 week,1 month,2 months,3 months,4 months,5 months,6 months,7 months,8 months,and 9 months,thawed the samples showed relative deviations of 9％,0％,10％,9％,14％,15％,6％,0％,-10％,-5％,and 2％,respectively.The intra-laboratory CV value from different technologists at this center was 7.28％,and the inter-labora-tory CV across different centers was 18.75％.Conclusion The prepared in-house positive control material of Factor Ⅷ inhibitor ex-hibited adequate uniformity and stability.

OBJECTIVE To observe the influence of carbapenem-resistant Klebsiella pneumoniae(CRKP)infec-tion/colonization on mortality risk of the intensive care unit(ICU)patients.METHODS The patients who were hospitalized in ICUs of West China Hospital of Sichuan University from Jan.1,2016 to Dec.31,2018 were recrui-ted as the research subjects.By means of retrospective cohort study,the enrolled patients were divided into the CRKP infection/colonization group and the non-CRKP infection/colonization group according to the status of isola-tion of CRKP strains from the clinical specimens of the ICU patients.The 30-day mortality risk of the CRKP in-fection/colonization group and the non-CRKP infection/colonization group was analyzed by Kaplan-Meier.The in-fluencing factors for the 30-day mortality risk of the ICU patients were analyzed by means of Cox proportional haz-ard model.RESULTS A total of 2229 patients were enrolled in the study,of which 89 were assigned as the CRKP infection/colonization group,and 2140 were assigned as the non-CRKP infection/colonization group.The sputum was the major specimen source from the patients with CRKP infection/colonization,and the lower respira-tory tract was the major infection site.The 30-day survival rate was 66.49％in the CRKP infection/colonization group,78.49％in the non-CRKP infection/colonization group,and there was significant difference(x2=7.200,P=0.007).The Cox proportional hazard model analysis showed that the CRKP infection/colonization could in-crease the 30-day mortality risk of the ICU patients(HR=1.839,95％CI:1.126 to 3.002,P=0.015);the age(HR=1.014,95％CI:1.006 to 1.022,P＜0.001),APACHE Ⅱ(HR=1.035,95％CI:1.018 to 1.053,P＜0.001),use of caspofungin(HR=1.398,95％CI:1.038 to 1.882,P=0.028),central venous catheter indwelling(HR=3.752,95％CI:1.808 to 7.790,P＜0.001)and blood purification(HR=2.061,95％CI:1.518 to 2.797,P＜0.001)may also increase the 30-day mortality risk of the ICU patients.CONCLUSIONS The CRKP infection/colonization patients are at higher 30-day mortality risk than the non-CRKP infection/colonization patients.It is necessary to formulate and implement the prevention and control measures to reduce the incidence of CRKP infection/colonization and take measures to reduce the mortality rate of the patients so as to improve the prognosis.

Objective:To construct patient-derived xenograft (PDX) models from head and neck squamous cell carcinoma (HNSCC) patients, to explore the effect of immune reconstitution timing on the PDX modeling and immune microenvironment in humanized immune system mice (huHSC-NCG-hIL15), and to provide a reliable animal model for research on the mechanisms of head and neck squamous carcinoma and for studies on immune therapy drug interventions.Methods:This study enrolled 28 HNSCC patients (25 laryngeal carcinomas, 3 hypopharyngeal carcinomas). PDX models were established in Balb/c nude (nu) mice, NSG mice, and humanized immune system-reconstituted huHSC-NCG-hIL15 mice. Fresh HNSCC samples were transplanted into Balb/c nu and NSG mice to generate PDX models, with subsequent analysis of success-associated factors. One successfully established PDX tumor was subsequently implanted into humanized immune system-reconstituted huHSC-NCG-hIL15 mice. Tumor transplantation was performed at distinct immune reconstruction timepoints (2 vs. 7 weeks post-reconstitution), and tumor growth patterns were monitored. Flow cytometry and multiplex immunohistochemical staining were utilized to characterize immunological profiles in peripheral lymphoid organs and tumor microenvironments. Hematoxylin-eosin (HE) staining was employed to assess histomorphological concordance between primary patient tumors and PDX model tissues. Results:HNSCC PDX models were successfully established. NSG mice exhibited a higher and more stable tumor take rate compared to Balb/c nu mice (pilot study: 4/10 vs. 3/10 cases; mean take rate 60%-80% vs. 20%-60 %). The PDX success rate in NSG mice was 46.4% (13/28). In the huHSC-NCG-hIL15 mice model with immune reconstitution at 7 weeks, tumors grew significantly faster, and the PDX modeling process was shorter (617 mm3 at day 70 in 7-week cohort vs.280 mm3 in 2-week cohort). Flow cytometry analysis of the immune microenvironment showed that at 7 weeks of immune reconstitution, the proportions of B cells in the spleen and tumor tissues(2-week vs. 7-week: spleen 16.2% vs. 61.7%, tumor 26.0% vs. 38.8%) and myeloid cells in the spleen (2-week vs. 7-week: spleen 47.2% vs. 88.1 %) were significantly higher, while mice at 2 weeks post-reconstitution showed a higher proportion of T cells (2-week vs. 7-week: spleen 13.2% vs. 9.3%, tumor 4.8% vs. 2.5%). HE results demonstrated that the tumor tissues in PDX models maintained a high degree of morphological similarity to the primary tumors in both NSG and huHSC-NCG-hIL15 mouse models. Conclusion:The HNSCC PDX modeling protocol demonstrates operational feasibility and high reproducibility, establishing this model as a robust platform for mechanistic and immunotherapeutic studies.

Objective To construct a machine learning prediction model for diabetic kidney disease(DKD)in type 2 diabetes mellitus(T2DM)patients in the plain-sand and loess hilly areas of Gansu Province,and analyze the interpretability of the model.Methods A multi-stage stratified random sampling method was used to collect the data of T2DM patients in the two areas.After key feature screening,eight ML prediction models were constructed for the risk of DKD in the two areas.The receiver operating characteristic(ROC)curve,accuracy and F1 index were used to evaluate the model,and Shapley additive explanation(SHAP)algorithm was used for model interpretation.Results A total of 1599 patients with T2DM were enrolled in this study.After feature screening,ten variables were selected for model construction in the plain-sand areas.Among the eight models,the gradient boosting decision tree(GBDT)model had the highest prediction efficiency.The area under the curve(AUC)of the test dataset was 0.972,the accuracy was 0.949,and the F1 index was 0.884.In the loess hilly region,12 variables were included in the model,and the best model was the random forest(RF).The AUC of the test set was 0.966,the accuracy was 0.951,and the F1 index was 0.861.SHAP analysis showed that in addition to serum creatinine,age,LDL-C,HbA1c,DM duration,serum uric acid and urinary microalbumin were also closely related to the high risk of DKD.Conclusions The GBDT and RF models have good predictive efficiency for the occurrence of DKD in the two areas,which can be used for the screening of DKD high-risk populations and the in-depth exploration of potential risk factors in the two areas.

Epilepsy is a chronic neurological disorder caused by an imbalance between excitation and inhibition in the central nervous system.Recently,the role of the orexin system in the pathogenesis of epilepsy has garnered significant attention.Orex-in primarily regulates arousal states and enhances neuronal excit-ability through activation of OX1-R/OX2-R receptors.Studies have shown that elevated orexin levels lower the seizure thresh-old,while orexin receptor antagonists(ORAs)exhibit potential antiepileptic effects.ORAs suppress epileptiform discharges by reducing glutamate release,enhancing GABAergic inhibitory effects,and modulating the thalamocortical circuit.Animal ex-periments and preliminary clinical studies demonstrate that OX1R antagonists decrease excitatory synaptic transmission,whereas OX2 R antagonists primarily strengthen GABA-mediated inhibition.With the widespread application of ORAs in sleep disorders,exploring their clinical value as antiepileptic drugs will become a key focus for future research.This review summa-rizes the role of the orexin system in epileptogenesis and discus-ses the research progress and future directions of ORAs as poten-tial antiepileptic agents.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.