Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal malignancy with limited therapeutic options. This study aimed to explore the role of disulfidptosis‑related genes (DRGs) in shaping the tumor immune microenvironment of PDAC, and to identify candidate prognostic biomarkers with potential therapeutic implications. DRG expression was profiled using transcriptomic data from The Cancer Genome Atlas (TCGA), and consensus clustering identified two molecular subtypes—C1 and C2—with C2 exhibiting a higher disulfidptosis activity score and distinct immune‑related features. Univariate and multivariate Cox regression analyses identified MYH9 as an independent prognostic factor. A nomogram incorporating MYH9 expression, age, gender, AJCC pathological stage, and histological grade predicted 1‑, 2‑, and 3‑year overall survival with areas under the curve (AUC) values of 0.66, 0.80, and 0.64, respectively. Further immune and drug‑sensitivity analyses revealed that MYH9 expression correlated significantly with immune cell infiltration and response to agents such as staurosporine, dasatinib, and oxaliplatin. Experimental validation showed that MYH9 overexpression significantly promoted the proliferation of PDAC cells, whereas MYH9 knockdown markedly suppressed it, and rescue experiments with the MYH9 inhibitor blebbistatin further confirmed its regulatory role in PDAC cell growth. Moreover, clinical specimen validation confirmed that elevated MYH9 expression correlated with reduced CD8+ T cell infiltration and poorer overall survival in PDAC patients. Collectively, these findings indicate that DRG expression profiles are closely associated with the PDAC tumor microenvironment. MYH9, identified from the disulfidptosis‑related gene set, serves as a reliable prognostic biomarker and a candidate oncogene in PDAC. Its potential association with disulfidptosis provides a preliminary basis for further mechanistic investigation and the exploration of targeted therapy for PDAC.

The development of dual inhibitors of histone deacetylases (HDACs) and enhancer of zeste homologue 2 (EZH2) is an efficient strategy that not only synergistically suppresses critical pathways in tumorigenesis but also circumvents the potential risks of drug cocktails. In this study, a series of pyridone derivatives were rationally designed via pharmacophore merging, and N1-((4,6-dimethyl-2-oxo-1,2-dihydropyridin-3-yl)methyl)-N8-hydroxyoctanediamide (15c) was identified as the most potent compound against hematological tumor cells MV4-11 and SU-DHL-10, with IC50 values in the submicromolar range. 15c also effectively inhibited HDAC1 and EZH2 with IC50 values of 9.2 nM and 311.1 nM, respectively. Molecular simulations revealed key interactions between 15c and both targets. These findings indicated that compound 15c warrants further investigation as a novel dual HDAC/EZH2 agent.

BackgroundNeoadjuvant immunotherapy combined with chemotherapy has revolutionized the treatment of locally advanced gastric cancer (LAGC), yet optimizing patient selection remains challenging due to heterogeneous responses. This study aimed to evaluate the divergent predictive values of nutritional and inflammatory biomarkers—specifically the Prognostic Nutritional Index (PNI), Systemic Immune-inflammation Index (SII), and Creatinine to Cystatin C Ratio (CCR)—for short-term pathological response and long-term survival.MethodsA prospective cohort of 132 LAGC patients receiving neoadjuvant nivolumab plus chemotherapy followed by curative resection was analyzed. Logistic regression and a decision tree model were employed to identify predictors of pathological complete response (pCR). Furthermore, univariate and multivariate Cox proportional hazards regression analyses were performed to determine independent prognostic factors for overall survival (OS).ResultsIn this study, patients with pCR showed significantly better OS and disease-free survival (DFS) compared to patients with non-pCR (both P < 0.01). Additionally, patients in the pCR group exhibited a significant decrease in the SII levels, while PNI and CCR were significantly increased (all P < 0.05). Restricted Cubic Spline (RCS) analysis confirmed that these indices were significantly linearly correlated with survival risks (all P < 0.05), and Kaplan-Meier curves revealed that patients with low SII, high PNI and CCR levels had longer OS and DFS (all P < 0.0001). Based on decision tree analysis, a prediction model was constructed by combining PNI, SII, CCR and CA199, which significantly enhanced the predictive ability of pCR (Area Under the Curve, AUC = 0.917). Finally, the nomogram models for OS and DFS also demonstrated good calibration and discrimination.ConclusionsNutritional and inflammatory status (SII, PNI, CCR) and CA199 serve as a sensitive marker for immediate pathological response, SII, PNI and CA125 are more indicative of long-term prognosis. Integrating these distinct biomarkers into phase-specific predictive models facilitates precise risk stratification and personalized management for patients undergoing neoadjuvant immunotherapy.

Background Previous epidemiological studies have yielded inconclusive results regarding the causality between blood metabolites and the risk of gastric cancer (GC). To address this shortcoming, we conducted a two-sample Mendelian randomization (MR) study, combined with metabolomics techniques, to elucidate the causality between 486 genetically predicted blood metabolites and GC.Methods MR analysis and metabolomics techniques such as ultra-high performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) and gas chromatography/tandem mass spectrometry (GC-MS/MS) technologies were employed to assess the causality of 486 genetically predicted blood metabolites on the risk of GC. The genome-wide association study (GWAS) summary data for 486 blood metabolites from 7,824 individuals. The GWAS summary data for GC (ebi-a-GCST90018849) were obtained from the IEU Open GWAS project, including 1,029 GC cases and 474,841 controls. Primary causality estimates were obtained using inverse variance weighting (IVW), supplemented with the weighted median, MR-Egger, weighted mode, and simple mode. In addition, we conducted sensitivity analyses (including Cochran's Q, MR-Egger intercept, MR-PRESSO, and leave-one-out tests),Steiger's test, linked disequilibrium score regression, and multivariate MR (MVMR) to improve the assessment of causality between GC and blood metabolite. Finally, we recruited a total of 11 patients diagnosed with gastric cancer from the First Affiliated Hospital of Air Force Military Medical University between September and October 2024. The control group comprised 11 healthy individuals. Serum samples were collected from both groups for the evaluation of blood-related metabolite expression levels using advanced techniques such as ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography-mass spectrometry (GC-MS/MS).Results The MVMR analysis revealed a significant association between genetically predicted elevated levels of tryptophan (odds ratio [OR] = 0.523, 95% confidence interval [CI] = 0.313-0.872, p = 0.013), nonadecanoate (19:0) (odds ratio [OR] = 0.460, 95% confidence interval [CI] = 0.225-0.943, p = 0.034), and erythritol (odds ratio [OR] = 0.672, 95% confidence interval [CI] = 0.468-0.930, p = 0.016) with a decreased risk of gastric cancer. Based on metabolomic techniques such as UPLC-MS/MS and GC-MS/MS analyses, it has been demonstrated that the expression levels of tryptophan, nonadecanoate (19:0), and erythritol are reduced in patients with gastric cancer. This finding aligns with the results obtained from our MR analysis and provides further confirmation regarding the protective role of tryptophan, nonadecanoate (19:0), and erythritol against gastric cancer.Conclusions These findings indicate that three blood metabolites are causally related to GC and provide new perspectives for combining genomics and metabolomics to study the mechanisms of metabolite-mediated GC development.

Background and Aims: More and more studies have proved that Perineural Invasion (PNI)plays an important role in cancer development,but the traditional detection methods are cumbersome pathological examinations and extremely dependent on doctors' experience, can not be applied to all hospitals. Therefore, we aim to build a model that predicts PNI using machine learning. Methods Outliers were removed using the Isolation Forest method and eligible patients were divided into training and testing cohorts using the Isolation Forest algorithm, and the data were subjected to binary tree segmentation, sample selection, feature selection and segmentation point selection, all using randomisation. The distributions of categorical variables were compared using the Chi-squared test and Fisher's exact test. AUC, balanced F Score, confusion matrix, Matthews correlation coefficient and diagnostic odds ratio to compare the predictive power of the models. Results The X-tree (random forest) model is a convenient and reliable tool for predicting PNI status in gastric cancer patients using preoperative clinical indicators. It has demonstrated excellent performance with an AUC of 0.97, precision of 0.93, and recall of 0.84 for the test set. Conclusions PNI is not conducive to the survival of gastric cancer patients, and the study established a model for predicting PNI in patients with gastric cancer based on their preoperative clinical characteristics.

Background and Aim: The incidence of Early-Onset Colorectal Cancer (EOCRC) is increasing. However, the prognosis of EOCRC compared to Late-Onset Colorectal Cancer (LOCRC), and the ideal age for initial colorectal cancer (CRC) screening are not clear. In this study, we identified the pathological differences between the groups and determined the optimal screening age for CRC patients. Methods: We included 10,172 patients diagnosed with CRC from January 2011 to December 2021 in this study. Survival differences were compared by plotting Kaplan-Meier survival curves and conducting landmark analysis. Additionally, the diagnostic age of CRC patients was analyzed using age cumulative curves. Results : Compared to LOCRC patients, EOCRC patients had a higher proportion of defective mismatch repair (dMMR) and more advanced TNM staging (P < 0.05). The five-year survival of EOCRC patients was significantly better than that of LOCRC patients (P < 0.05). Laparoscopic surgery improved the long-term survival of EOCRC patients. Proficient mismatch repair (pMMR) favored the long-term survival of EOCRC patients. The survival rate of EOCRC patients at TNM stages I and II was higher than that of LOCRC patients at the same stages (P < 0.05). The age cumulative curve showed a substantial increase in the number of CRC patients at 40 years. Conclusion: The long-term prognosis of EOCRC patients is better than that of LOCRC patients, especially among those with pMMR, stages I-II, and who undergo laparoscopic surgery. For high-risk groups, the starting age for CRC screening should be 40 years.

Circadian rhythm genes were reported to be strongly associated with the development and prognosis of circadian rhythm disorders related to stomach adenocarcinoma (STAD), which is one of the most prevalent cancers. This study aimed to identify a circadian rhythm-related gene signature that could help predict STAD outcome. Using bioinformatics analysis approaches, 105 genes were examined in 350 patients with STAD. Overall, six hub-type circadian rhythm-associated genes (GNA11, PER1, SOX14, EZH2, MAGED1, and NR1D1) were identified using univariate and multivariate Cox regression analyses. These genes were then used to build a genetic predictive model, which was further validated using a publicly available dataset (GSE26899). Overall, genes associated with the circadian rhythm were found to be substantially correlated with the characteristics of the STAD patients (grade, sex, and M stage). In addition, the circadian rhythm-related gene signature was significantly associated with the MAPK and Notch signaling pathways, which are known risk factors for poorer STAD outcome. Taken together, these findings suggest that the herein proposed prognostic model based on six circadian rhythm-associated genes may have predictive value and potential application for clinical decision-making and for personalized treatment of STAD.

兔子是医药生物实验中常见的实验动物,尤其以新西兰兔居多,在医学实验中广泛被饲养和使用,因此保障其健康生存必不可少,但我国目前大部分高校及小型医学研究机构因资金及管理水平等一系列因素,难以大范围使用SPF级实验动物房,必不可少地造成了实验动物携带病菌而被感染的情况发生.本试验通过对相关病例的观察与治疗,寻找在实验兔中螨病治疗的合理化方案.为解决类似传染病的蔓延提供例证和新思路.

临床基本操作课程是基层军医卫勤指挥、专科培训、特定任务卫勤保障培训的重要内容,围绕提升军事医学人才的职业特质、专业技能、综合素养等,全面分析基层部队卫生专业人员的学习特点,建设以紧贴实战的围伤(病)期救治技术为主要内容的高质量在线慕课.在此基础上,研究分析临床基本操作慕课在军事医学职业教育中的应用成效,证明其对于完善军事医学职业教育体系、培养三位一体新型军事人才具有重要意义.

现代战场环境下,一线战士战创伤救治是战时减少部队人员伤亡的重要保障.专业的军事医学院校及卫勤培训基地无法大规模地对一线战士进行战伤救治能力的培训.笔者提出充分利用基层军医的专业知识背景和水平,发挥其作为部队卫勤保障核心力量的作用,通过提升基层军医的战创伤救治水平,由他们向一线战士进行推广的模式.通过建规范、创教法、考实操的培训策略,切实提升一线战士的战创伤救治水平.

思政教育的理念对我国医学教育改革产生了深远的影响,强调将课程作为"主阵地",致力于实现"思想政治工作贯穿教育教学全过程",促进教育教学深化改革,全方位优化课程思政供给.新教学模式的探索和医学人才培养模式的改革是促进医学教育高质量发展的关键,以"三全育人"作为"以德树人"理念和使命下课程建设的有力抓手,在各高校中掀起了"三全育人"综合改革实践新征程.《临床基本操作》是我校一门纵、横向特色性整合的临床医学课程,创新性改革以学科为中心的传统构架,以"系统-疾病"为主线建立全面完整的知识结构体系.结合"三全育人"理念,从"三全"模式的构建、无菌术课程教学的思政设计、无菌术课程教学的实践以及考核评价体系四个方面展开研究和实践,并通过调查问卷分析等方法对教学效果进行深度剖析,对新教学模式进行总结、凝练,并上升为理论素材,旨在将"三全育人"贯彻到医学临床基本操作课程教学中,为建设临床基本操作一流本科课程奠定基础.