[摘 要] 目的：探究纺锤体蛋白1（SPIN1）促进胃腺癌细胞迁移与侵袭的分子机制。方法: 通过TCGA数据库数据分析胃腺癌组织中SPIN1 mRNA表达与上皮间质转化（EMT）评分、血管生成评分间的相关性。收集2018年8月至2021年11月期间山东第一医科大学附属省立医院手术切除的52例胃腺癌患者的癌组织制成组织芯片，每例均包含胃腺癌组织、对应癌旁组织及淋巴结转移灶，通过免疫组织化学法检测胃腺癌组织中SPIN1与STAT3的蛋白表达水平及相关性。通过Transwell实验研究干扰SPIN1对胃腺癌细胞侵袭与迁移的影响。使用GEPIA2网站分析SPIN1基因与Janus-激酶/信号转导和转录激活因子（JAK/STAT）通路相关因子在胃腺癌中的表达相关性。通过qPCR法、WB法检测干扰SPIN1后JAK/STAT通路相关mRNA和蛋白的表达变化。结果: TCGA数据库数据分析结果显示，SPIN1表达与EMT评分和血管生成评分呈正相关（均P < 0.05）。SPIN1与STAT3在胃腺癌组织和淋巴结转移灶中表达升高（均P < 0.05），在癌旁胃黏膜组织中阴性表达。SPIN1与STAT3的表达显著正相关（P < 0.05）。干扰SPIN1后胃腺癌细胞的迁移、侵袭能力明显降低（P < 0.05或P < 0.01）。GEPIA2网站分析结果显示，SPIN1基因与JAK1、JAK2、STAT1、STAT2及STAT3表达均呈显著正相关（均P < 0.05）。干扰SPIN1后JAK2、STAT3的mRNA水平下降，而JAK1、STAT1、STAT2的mRNA水平变化不明显。WB法实验结果表明，干扰SPIN1后JAK2、STAT3、p-JAK2及p-STAT3的蛋白表达均显著降低（均P < 0.01），过表达SPIN1后JAK2、STAT3、p-JAK2及p-STAT3的蛋白表达均显著升高（均P < 0.01）。结论: SPIN1可通过参与JAK2/STAT3信号通路促进胃腺癌细胞迁移与侵袭。

OBJECTIVE To study the clinical characteristics and potential risk factors for infection in patients with multiple myeloma （MM） following treatment with bortezomib. METHODS Clinical data were retrospectively collected from MM patients who received bortezomib-based treatment regimens at the Department of Hematology， the Second Affiliated Hospital of Soochow University， from October 2021 to February 2025. The collected data primarily included demographic characteristics， disease characteristics of MM， treatment regimens， occurrence of infections and corresponding management measures， and prophylactic medication use. Univariate and multivariate Logistic regression analyses were conducted to identify potential risk factors for MM complicated with infection. RESULTS Among the 284 MM patients treated with bortezomib， 132 patients （46.5%） experienced at least one infection. The predominant types of infections were respiratory tract infections and gastrointestinal infections. Univariate analysis showed that age at initial diagnosis， pathological classification， and grade of myelosuppression were influencing factors for infection in MM patients （ P ＜0.05）. Further analysis of influencing factors for the two main types of infections revealed that sex， age at initial diagnosis， pathological classification， treatment regimen， and smoking history were influencing factor s for respiratory tract infections in MM patients （ P ＜0.05）； BMI， pathological classification， treatment regimen， and grade of myelosuppression were influencing factors for gastrointestinal infections in MM patients （ P ＜0.05）. Multivariate Logistic regression analysis indicated that age≥70 years and the presence of grade Ⅳ myelosuppression before treatment were risk factors for infection in MM patients， while the IgG-λ type was a protective factor against infection （ P ＜0.05）. CONCLUSIONS The incidence of infection is relatively high in MM patients receiving bortezomib-based treatment regimens， with respiratory and gastrointestinal infections being the most common. Age at initial diagnosis， grade of myelosuppression， and pathological classification are influencing factors for infection in MM patients.

Objective To explore the research hotspots and developmental trends in urological education through a bibliometric analysis. Methods Relevant literature on urological education was retrieved from the Web of Science Core Collection and the China National Knowledge Infrastructure (CNKI) databases, covering all records up to Sep.16, 2025.A comprehensive bibliometric analysis was performed on the retrieved publications. Results A total of 303 Chinese and 290 English articles were collected.The annual number of publications demonstrated an overall upward trend.Harvard University in the United States was the most productive institution in this field. Conclusion Urological clinical education has attracted increasing attention from clinicians and medical trainees.Highly cited studies consistently highlight three actionable priorities for urological education:firstly, improving long-term knowledge retention through structured, spaced, and feedback-rich learning designs; secondly, standardizing simulation-based skills training with validated assessment and staged credentialing; thirdly, strengthening training system resilience while expanding non-technical skills training.These directions provide implementable pathways for optimizing urological teaching practices and the standardized residency training programs.

OBJECTIVE To develop a pharmacist-led intervention model for reducing drug-related medical insurance claim denial risks， so as to provide practical references for healthcare institutions in fulfilling their primary responsibility for medical insurance fund supervision. METHODS A risk matrix method was employed by the pharmacists to assess the risks associated with drug‑related medical insurance claim rejections in our hospital during 2024. Intervention measures were developed targeting high‑risk factors (including inappropriate indications for medical insurance coverage, exceeding the covered treatment course, and inappropriateness of gender and age) from three dimensions, namely organizational structure, technical prevention and control, and closed‑loop management. Changes in drug‑related claim rejection data were compared between 2024 (pre‑intervention) and 2025 (post‑intervention), and the interception effect of the pre‑prescription review system was evaluated after the intervention. RESULTS After the intervention, the total amount of drug‑related medical insurance claim rejections in our hospital was reduced by 57.24% compared with that before the intervention, and the number of rejected items decreased from 10 108 to 2 892. Specifically, the number of rejected items due to inappropriate indications, exceeded treatment course, inappropriate gender, and inappropriate age was reduced by 70.94%, 74.26%, 83.86%, and 96.70%, respectively. Throughout the year following the intervention, a total of 5.605 yuan million in outpatient prescription drug amounts and 4.683 million yuan in inpatient medication order amounts that did not meet the insurance‑limited payment requirements were intercepted by the pre‑prescription review system. The proportion of drug‑related claim rejection amount to the total medical service claim rejection amount of our hospital decreased to 19.7%. CONCLUSIONS The pharmacist-led multi-department collaborative， technical prevention and control， and dynamic optimization integrated full-process intervention model is highly operable and has significant practical effects. It has important promotion value in reducing drug-related medical insurance claim denial risks.

OBJECTIVE To investigate the incidence and outcomes of vancomycin-associated acute kidney injury （VA-AKI） in critically ill patients， to analyze the independent risk factors for the development of VA-AKI and renal function outcomes in VA-AKI patients， and to evaluate the predictive performance of vancomycin treatment duration for VA-AKI occurrence， so as to provide reference for the rational and safe use of this drug.METHODS Clinical data of critically ill patients who received vancomycin during hospitalization in the intensive care unit of Zhongshan Hospital， Fudan University，from January 2022 to December 2024 were retrospectively collected. Patients were divided into the VA‑AKI group and the non‑AKI group according to the occurrence of VA‑AKI. Multivariate Logistic regression analysis was performed to screen for independent risk factors for VA‑AKI development and renal function outcomes in patients with VA‑AKI. The receiver operating characteristic （ROC） curve was used to analyze the predictive performance of vancomycin treatment duration for VA‑AKI.RESULTS A total of 1 484 patients were enrolled， among whom 287 developed VA‑AKI， with an incidence of 19.3%. The overall median time to onset was 2.5 days after vancomycin administration. Complicated hypertension， cardiac or renal insufficiency， hospital‑acquired sepsis/bacteremia， multiple organ failure， invasive mechanical ventilation during hospitalization， vancomycin treatment duration ≥10 days， and concomitant use of carbapenems or tacrolimus were independent risk factors for VA‑AKI （ P ＜0.05）. Concomitant use of vasopressors was an independent risk factor for renal function outcomes in patients with VA‑AKI （ P ＜0.05）. The area under the ROC curve （AUC） of the model using vancomycin treatment duration of predict the occurrence of VA-AKI was 0.624. At the optimal cut‑off value of 9.7 days， the sensitivity and specificity were 47.4% and 74.9%， respectively.CONCLUSIONS Critically ill patients have a relatively high incidence of VA-AKI， which mostly occurs in the early stage of vancomycin therapy. Patients with underlying cardiac-renal diseases， severe infection， requirement for mechanical ventilation， prolonged vancomycin therapy， and concomitant administration of carbapenems or tacrolimus are at high risk for VA-AKI. Concomitant vasopressor use affects renal function recovery in patients with VA-AKI. The predicted risk of acute kidney injury is higher when vancomycin treatment duration is ≥10 days.

OBJECTIVE To compare the predictive accuracy and clinical applicability of four vancomycin individualized dosing tools （SmartDose， ClinCalc， Gulou， Pharmado） and provide a basis for rational clinical medication use. METHODS A retrospective cohort study was conducted， enrolling 479 adult patients who received vancomycin therapy and underwent steady-state trough concentration monitoring in Zhongshan Hospital， Fudan University （Xiamen Branch） from January 1， 2022， to June 30， 2024. The predictive accuracy of each tool was evaluated using indicators， such as mean error （ME）, mean absolute error （MAE）， mean percentage error （MPE）， mean absolute percentage error （MAPE）， the proportion of patients with an absolute percentage error （APE） of less than 30%， the 95% limits of agreement， and the overall relative percentage difference between predicted and measured values. Using indicators such as accessibility， patient management， and recommendation of multiple treatment options， the clinical panxso@163.com applicability of the tools for all patients was evaluated； using the discrepancy in accuracy between the predicted and actual measured blood drug concentrations as an indicator， the clinical applicability was assessed for patients in different renal function subgroups （hyperfunction， normal， mild impairment， moderate impairment， and severe impairment）. RESULTS In terms of accuracy， SmartDose demonstrated the best overall performance with an MAPE of 46.40% and a proportion of APE ＜30% （46.56%）. Bland-Altman analysis indicated that SmartDose had the smallest overall relative percentage difference （－7.25%）， although the 95% limits of agreement were broad for all tools， with differences between the upper and lower limits exceeding 200%. In terms of applicability， all four dosing tools were freely accessible and demonstrated good availability； SmartDose and Pharmado provided the most comprehensive solutions， offering features such as patient management， multiple regimen recommendations， and drug concentration-time curve plotting. Stratified analysis based on renal function revealed that Pharmado showed optimal prediction for hyperfiltration patients （mean difference： 0.11 mg/L）. SmartDose and ClinCalc showed relatively better performance in normal and mild renal impaiment （mean difference： 0.37， 0.51 mg/L and －1.13， －1.33 mg/L，respectively）. SmartDose performed best in moderate renal impairment （mean difference： －2.60 mg/L）. Pharmado and Gulou had smaller prediction biases in severe renal impairment （mean differences： 1.52 mg/L and －0.23 mg/L， respectively）. CONCLUSIONS The four individualized dosing tools demonstrated limited accuracy in the initial prediction of vancomycin concentrations. Among them， SmartDose demonstrates the highest overall prediction accuracy and possesses comprehensive clinical management features. It is recommended that Pharmado be preferred for patients with renal hyperfiltration； SmartDose or ClinCalc can be used for patients with normal or mildly impaired renal function； SmartDose is recommended for patients with moderately impaired renal function； Pharmado or Gulou may be considered for patients with severely impaired renal function.

Large language models (LLMs) such as ChatGPT, Claude, Llama, and Qwen are emerging as transformative technologies for the diagnosis and treatment of various diseases. With their exceptional long-context reasoning capabilities, LLMs are proficient in clinically relevant tasks, particularly in medical text analysis and interactive dialogue. They can enhance diagnostic accuracy by processing vast amounts of patient data and medical literature and have demonstrated their utility in diagnosing common diseases and facilitating the identification of rare diseases by recognizing subtle patterns in symptoms and test results. Building on their image-recognition abilities, multimodal LLMs (MLLMs) show promising potential for diagnosis based on radiography, chest computed tomography (CT), electrocardiography (ECG), and common pathological images. These models can also assist in treatment planning by suggesting evidence-based interventions and improving clinical decision support systems through integrated analysis of patient records. Despite these promising developments, significant challenges persist regarding the use of LLMs in medicine, including concerns regarding algorithmic bias, the potential for hallucinations, and the need for rigorous clinical validation. Ethical considerations also underscore the importance of maintaining the function of supervision in clinical practice. This paper highlights the rapid advancements in research on the diagnostic and therapeutic applications of LLMs across different medical disciplines and emphasizes the importance of policymaking, ethical supervision, and multidisciplinary collaboration in promoting more effective and safer clinical applications of LLMs. Future directions include the integration of proprietary clinical knowledge, the investigation of open-source and customized models, and the evaluation of real-time effects in clinical diagnosis and treatment practices.
Humans ; Large Language Models ; Tomography, X-Ray Computed

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

OBJECTIVE: Coronavirus disease 2019 (COVID-19) can result in fatigue and post-exertional malaise; however, whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection exacerbates lower urinary tract symptoms (LUTS) is unclear. This study investigated the association between prenatal SARS-CoV-2 infection and postpartum LUTS. METHODS: A multicenter, retrospective cohort study was conducted at two tertiary hospitals in China from November 1, 2022, to November 1, 2023. Participants were classified into infected and uninfected groups based on SARS-CoV-2 antigen results. LUTS prevalence and severity were assessed using self-reported symptoms and the Incontinence Impact Questionnaire-Short Form (IIQ-7). Pelvic floor muscle activity was measured using electromyography following the Glazer protocol. Group comparisons were performed to evaluate the association of SARS-CoV-2 infection with LUTS and electromyography parameters, with stratified analyses conducted using SPSS version 26.0. RESULTS: Among 3,652 participants (681 infected, 2,971 uninfected), no significant differences in LUTS prevalence or IIQ-7 scores were observed. However, SARS-CoV-2 infection was an independent factor influencing the electromyographic activity of the pelvic floor muscles (mean tonic contraction amplitudes), regardless of delivery mode ( P = 0.001). CONCLUSION Prenatal SARS-CoV-2 infection was not significantly associated with an increased risk of postpartum LUTS but independently altered pelvic floor muscle electromyographic activity, suggesting potential neuromuscular effects.
Humans ; Female ; COVID-19/epidemiology* ; Retrospective Studies ; Adult ; Pregnancy ; Lower Urinary Tract Symptoms/virology* ; Postpartum Period ; Pregnancy Complications, Infectious/virology* ; China/epidemiology* ; Electromyography ; SARS-CoV-2/physiology* ; Pelvic Floor/physiopathology* ; Prevalence

ObjectiveTo analyze the evolutionary characteristics and genetic variations of the HA (hemagglutinin) and NA (neuraminidase) genes of influenza A(H1N1) viruses in Shanghai during 2024, to investigate their transmission patterns, and to evaluate their potential impact on vaccine effectiveness. MethodsFrom January to October 2024, throat swab specimens were collected from influenza like illness (ILI) patients at 4 hospitals in Shanghai. Real-time fluorescence ploymerase chain reaction (RT-PCR) was used for virus detection and isolation of H1N1 influenza viruses. Forty influenza A(H1N1) virus strains were sequenced using Illumina NovaSeq 6000 platform, followed by phylogenetic analyses, genetic distance analysis, and amino acid variation analyses of HA and NA genes. ResultsPhylogenetic tree of the HA and NA genes revealed that the 40 influenza A(H1N1) virus strains circulating in Shanghai in 2024 exhibited no significant geographic clustering, with a broad origin of strains and complex transmission chains. Genetic distance analyses demonstrated that the average intra-group genetic distances of HA and NA genes among the Shanghai strains were 0.005 1±0.000 6 and 0.004 6±0.000 6, respectively, which were comparable to or higher than those observed in global surveillance strains. Both HA and NA genes displayed frequent mutations. Compared to the 2023‒2024 and 2024‒2025 Northern Hemisphere A(H1N1) vaccine strains (WHO-recommended), the HA proteins of 40 Shanghai strains exhibited amino acid substitutions at positions 120, 137, 142, 169, 216, 223, 260, 277, 356 and 451, with critical mutations at positions 137 and 142 located within the Ca2 antigenic determinant. Furthermore, mutations in the NA protein were observed at positions 13, 50, 200, 257, 264, 339 and 382. ConclusionThe genetic background of the 2024 Shanghai influenza A(H1N1) virus strains is complex and diverse, and antigenic variation may affect vaccine effectiveness. Therefore, it is recommended to enhance genomic surveillance of influenza viruses, evaluate vaccine suitability, and implement more targeted prevention and control strategies against imported influenza viruses.