[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 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

Lung cancer is the leading cause of cancer-related deaths worldwide. Radiation pneumonitis is a major complication in lung cancer radiotherapy. Four-dimensional computed tomography (4DCT) imaging provides dynamic ventilation information, which is valuable for lung function assessment and radiation pneumonitis prevention. Many methods have been developed to calculate lung ventilation from 4DCT, but a systematic comparison is lacking. Prediction of radiation pneumonitis using 4DCT-based ventilation is still in an early stage, and no comprehensive review exists. This paper presented the first systematic comparison of functional lung ventilation algorithms based on 4DCT over the past 15 years, highlighting their clinical value and limitations. It then reviewed multimodal approaches combining 4DCT ventilation imaging, dose metrics, and clinical data for radiation pneumonitis prediction. Finally, it summarized current research and future directions of 4DCT in lung cancer radiotherapy, offering insights for clinical practice and further studies.
Humans ; Lung Neoplasms/diagnostic imaging* ; Four-Dimensional Computed Tomography/methods* ; Radiation Pneumonitis/etiology* ; Algorithms ; Lung/radiation effects* ; Pulmonary Ventilation

Most current medical image segmentation models are primarily built upon the U-shaped network (U-Net) architecture, which has certain limitations in capturing both global contextual information and fine-grained details. To address this issue, this paper proposes a novel U-shaped network model, termed the Multi-View U-Net (MUNet), which integrates self-attention and multi-view attention mechanisms. Specifically, a newly designed multi-view attention module is introduced to aggregate semantic features from different perspectives, thereby enhancing the representation of fine details in images. Additionally, the MUNet model leverages a self-attention encoding block to extract global image features, and by fusing global and local features, it improves segmentation performance. Experimental results demonstrate that the proposed model achieves superior segmentation performance in coronary artery image segmentation tasks, significantly outperforming existing models. By incorporating self-attention and multi-view attention mechanisms, this study provides a novel and efficient modeling approach for medical image segmentation, contributing to the advancement of intelligent medical image analysis.
Humans ; Image Processing, Computer-Assisted/methods* ; Neural Networks, Computer ; Algorithms ; Attention ; Coronary Vessels/diagnostic imaging* ; Diagnostic Imaging/methods*

At present, research on the efficacy of local physical cooling devices is mainly based on clinical observation, but there is relatively little research on evaluating the effectiveness of local cold therapy cooling and the penetration depth. This study is based on the research of the structure and morphology of local muscle tissue in the human body, as well as the heat transfer characteristics and mechanisms of the human body. A simulation phantom of human muscle tissue under temperature cycling was created, and the differences in evaluating the effectiveness of local cold therapy between the human body and the simulation phantom were compared. This provides a new evaluation method for evaluating the cooling effectiveness of local physical cooling equipment.
Humans ; Phantoms, Imaging ; Hypothermia, Induced/methods*

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

With the rapid development of competitive sports, the incidence of anterior cruciate ligament (ACL) injury is on the rise. Such injuries may shorten athletes′ career and lead to other long-term adverse consequences. Although athletes generally recover well after ACL reconstruction, many still struggle to return to their pre-injury performance levels. Advances in the understanding of ACL anatomy and injury mechanisms, along with the evolution of surgical techniques and rehabilitation methods, have provided more individualized and tailored options for athletes following ACL injuries. However, there is currently no consensus in China regarding surgical and rehabilitation strategies for competitive athletes aiming to return to sports after ACL injuries. To this end, the Sports Medicine Committee of the Chinese Research Hospital Association and the Editorial Board of the Chinese Journal of Trauma jointly formulated the Expert consensus on surgical treatment and rehabilitation for competitive sports athletes returning to sports after anterior cruciate ligament injury ( version 2025), and presented 14 recommendations covering surgical indications, preoperative rehabilitation, surgical timing, surgical strategies and postoperative rehabilitation strategies, aiming to improve the surgical treatment and rehabilitation system for ACL injuries in competitive athletes and facilitate their return to high-level sports performance after injury.

Objective:To analyze the clinical characteristics and related factors of cognition disorders in elderly hypertensive patients.Methods:It was a cross-sectional study. A total of 612 hypertensive patients with the age of (69.06±6.58) years (median 68.00 years) admitted in the Department of Cardiology, General Hospital of Chinese People′s Liberation Army from October 2022 to April 2024 were enrolled. The demographic and clinical data were collected, the cognition status was assessed with Mini-Mental State Examination (MMSE) at admission. The related factors of cognition disorders were analyzed with univariate and multivariate logistic regression.Results:The results showed that female hypertensive patients and those with older age, lower education, higher fasting blood glucose (FBG) and diabetes mellitus, higher low-density lipoprotein cholesterol (LDL-C) level, higher systolic blood pressure (SBP) and more cardiovascular comorbidities were likely to have cognition disorders (all P<0.05). Multivariate logistic regression analysis showed that smoking history, elevated SBP, elevated heart rate, elevated FBG, and elevated LDL-C were independent risk factors for cognition disorders in elderly hypertensive patients,while higher education level was an independent protective factor (all P<0.05). Conclusion:Smoking, increased SBP, increased heart rate, increased FBG, increased LDL-C and lower education level are independently associated with cognition disorders in elderly hypertensive patients.