[摘 要] 目的：探讨m6A调控因子在宫颈癌预后评估、免疫微环境特征及治疗反应中的作用，构建基于m6A调控因子的预后风险模型，并分析其与免疫浸润、药物敏感性及细胞间通信的关系。方法：基于TCGA和GEO数据库中宫颈鳞癌及腺癌（CESC）转录组数据，分析22个m6A调控因子的表达与突变情况；采用LASSO‑Cox回归构建m6A相关预后风险模型，并依据风险评分将患者分为高、低风险组。利用CIBERSORT和ESTIMATE算法评估两组免疫细胞浸润及微环境特征；通过oncoPredict预测抗肿瘤药物敏感性。整合单细胞转录组数据（E-MTAB-12305），采用CellChat分析细胞间通信网络。结果：共鉴定出12个在宫颈癌中差异表达的m6A调控因子。高风险组患者总生存期缩短（P < 0.05），免疫评分降低，且对紫杉醇、氟尿嘧啶、多柔比星等抗肿瘤药物敏感性较差（IC50较高）。单细胞分析显示宫颈癌组织中细胞间通信网络发生改变，其中T细胞与内皮/上皮细胞间的相互作用可能主要由CCL5‑ACKR1和MIF‑（CD74 + CXCR4）配体‑受体介导。在临床样本中，对关键的m6A调控因子进行mRNA和蛋白水平的验证，结果显示部分调控因子在宫颈癌组织中的表达水平高于正常宫颈组织（P < 0.05）。结论：m6A调控因子特征可有效预测宫颈癌患者预后，其风险评分与肿瘤免疫浸润、药物敏感性及细胞通信密切相关，为宫颈癌的预后分层及个体化治疗提供了新的分子依据。

ObjectiveTo elucidate the effects of autonomic neuromodulators [calcium chloride (CaCl₂)-acetylcholine (ACh)] on atrial electrical remodeling and histopathological changes in rats, thereby providing evidence for further investigation into the pathological mechanisms by which autonomic imbalance induces atrial fibrillation (AF). MethodsTen 8-week-old male Sprague-Dawley (SD) rats were randomly divided into experimental and control groups, with 5 rats in each group. The experimental group received daily tail vein injections of a CaCl₂-ACh mixed solution for 28 days, while the control group received an equal volume of saline. Surface electrocardiograms were recorded before and after daily administration. On day 28 of administration, under isoflurane inhalation anesthesia, echocardiography was performed, and then the rats were euthanized by exsanguination under isoflurane anesthesia for tissue collection. Body weight and heart weight of rats were measured, and electrophysiological parameters including AF inducibility, conduction velocity, and conduction dispersion in isolated rat hearts were monitored using the MappingLab multichannel electrophysiological mapping system. HE staining was performed to evaluate atrial tissue architecture and inflammatory cell infiltration. The expression levels of matrix metalloproteinase 9 (MMP-9) and interleukin-1 beta (IL-1β) were analyzed by Western blotting. Masson staining was used to quantitatively analyze the proportional distribution of collagen fibers and myocardial fibers, and to calculate the area of collagen deposition, thereby evaluating the degree of myocardial fibrosis. Wheat germ agglutinin (WGA) staining was used to evaluate morphological changes of cardiomyocytes. Dihydroethidium (DHE) staining was used to detect the level of oxidative stress in atrial myocytes. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was used to detect atrial cell apoptosis. ResultsCompared with the control group, the experimental group showed obvious arrhythmias on electrocardiograms. Echocardiography after 28 days of administration revealed significant structural remodeling in the experimental group, with a marked increase in left atrial anteroposterior diameter (P < 0.05), and also showed cardiac dysfunction, with significant decreases in left ventricular ejection fraction and left ventricular fractional shortening (P < 0.01). Compared with the control group, the experimental group showed a significantly increased heart weight-to-body weight ratio (P < 0.05), a markedly higher AF inducibility (P < 0.001), a significantly slowed atrial conduction velocity (P < 0.05), an uneven isochronal map with irregular directions, and a significantly increased conduction dispersion (P < 0.01). HE staining showed that atrial myocytes in the experimental group were disorganized, with slight inflammatory cell infiltration. Western blotting showed that the expression levels of MMP-9 and IL-1β in the atrial tissue of the experimental group were significantly upregulated (P < 0.05). Masson staining showed a significant increase in collagen deposition and a significant increase in fibrosis area in the atrial tissue of the experimental group (P < 0.001). WGA staining showed that cardiomyocytes in the experimental group were significantly hypertrophied compared with the control group (P < 0.05). DHE staining and TUNEL staining revealed that the level of oxidative stress in atrial myocytes (P < 0.001) and the apoptotic rate (P < 0.01) were both significantly increased. Conclusion Daily tail vein injections of the autonomic neuromodulator CaCl₂-ACh mixed solution for 28 days can successfully induce AF in rats, accompanied by significant atrial structural remodeling, electrical remodeling, and oxidative stress.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To establish an analytical strategy covering multi-dataset processing, recursive feature elimination (RFE) screening and multi-model evaluation based on multiple machine learning algorithms, so as to screen radiation-sensitive genes and verify the feasibility of the evaluation strategy. Methods Qualified radiation transcriptome datasets were retrieved from public gene expression databases. Following standardized data preprocessing and feature preselection, 13 machine learning algorithms were adopted to construct models. The performance of each model was compared and validated in independent datasets. Results A total of 38 eligible datasets were included. Sixteen differentially expressed genes unreported in existing literature were screened out, among which ugcrhl, pdcl3, mct4, h2-g2 and fam120aos were correlated with radiation phenotypes. Ensemble learning algorithms including random forest and gradient boosting exhibited the optimal comprehensive performance. Independent dataset verification confirmed that the screened genes overlapped with known radiation-sensitive genes, and the model performance was consistent with the findings. Conclusion The machine learning strategy constructed in this study can effectively explore potential radiation-sensitive genes, and provides methodological support for subsequent relevant studies.

Objective To explore the health issues and influencing factors of workers in new forms of employment, represented by couriers and food delivery workers, based on the social-ecological model (SEM). Methods A total of 44 couriers and food delivery workers from Beijing City, Shanghai City, Guangzhou City, and Chongqing City were recruited as the study subjects using purposive sampling combined with snowball sampling method. An interview guide was developed based on the SEM to conduct semi-structured interviews. Thematic analysis was employed to code and analyze the interview data. Results The health influencing factors among the couriers and food delivery workers based on the SEM included three first-level themes at the micro-, meso-, and macro-levels, namely "individual factors," "occupational environmental factors," and "social environmental factors," each comprising three second-level themes. At the micro-level, individual factors such as insufficient health literacy, unhealthy lifestyles and behaviors, and sustained psychological burden jointly contributed to the health vulnerability among these couriers and food delivery workers. At the meso-level, occupational environmental factors including algorithmic management, high-load work environments, and inadequate interpersonal support, jointly construct a high-pressure and high-intensity work pattern. At the macro-level, social environmental factors such as insufficient social security caused by the de facto nature of labor relations, economic pressure resulting from unstable income in the market environment, and psychological depletion caused by occupational discrimination further exacerbate the health vulnerability among these workers. Conclusion The health issues of the couriers and food delivery workers result from the interplay of factors across micro-, meso-, and macro- levels. Therefore, a multi-level collaborative health protection system involving individuals, organizations, and society should be established to improve their health status.

Objective: To identify the risk factors for pulmonary arterial hypertension(PAH) in maintenance peritoneal dialysis(MPD) patients and to develop and validate a nomogram-based risk-prediction model. Methods: A total of 168 hospitalized MPD patients from the Department of Nephrology were enrolled.Body-fluid composition was measured by bioelectrical impedance analysis,and pulmonary-artery systolic pressure(PASP) was assessed by echocardiography.Patients were randomly allocated into a training set and a validation set at 1:1 ratio.Variables with P< 0. 05 in multivariable Logistic regression in the training set were incorporated to construct a nomogram .The validation set was used to test the model ’s predictive performance . ROC curves , calibration curves , and decision-curve analysis were applied to evaluate accuracy , consistency , and clinical usefulness of the model . Results: Dialysis vintage ( OR : 1 . 038 , 95% CI: 1 . 008 - 1 . 069 , P = 0. 012) , hemoglobin level ( OR : 0. 961 , 95% CI: 0. 929 - 0. 994 , P = 0. 021) , and extracellular water/intracellular water ratio (E/I) (OR : 1 . 069 , 95% CI: 1 . 024- 1 . 115 , P = 0. 002) were independent risk factors for PAH . ROC analysis yielded area under curve as 0. 867 (95% CI: 0. 782 - 0. 953) and 0. 808 (95% CI: 0. 714 - 0. 902) in the training and validation sets , respectively .Calibration plots showed that the predicted curves for both the training and validation sets closely overlapped with the ideal reference line , indicating that the nomogram risk-prediction model had good predictive performance . Decision-curve analysis demonstrated that , within threshold ranges of 0. 13 - 0. 76 ( training set ) and 0. 20 - 0. 76 (val- idation set ) , clinical net benefit was substantial when interventions were guided by the nomogram . Conclusion Dialysis vintage , hemoglobin level , and fluid-overload index (E/I) are independent risk factors for PAH in MPD patients . The nomogram based on these parameters reliably predicts PAH risk and may aid clinical decision-making.

Progressive pulmonary fibrosis (PPF) is a progressive and lethal condition with few effective treatment options. Improvements in quality of life for patients with PPF remain limited even while receiving treatment with approved antifibrotic drugs. Traditional Chinese medicine (TCM) has the potential to improve cough, dyspnea and fatigue symptoms of patients with PPF. TCM treatments are typically diverse and individualized, requiring urgent development of efficient and precise design strategies to identify effective treatment options. We designed an innovative Bayesian adaptive two-stage trial, hoping to provide new ideas for the rapid evaluation of the effectiveness of TCM in PPF. An open-label, two-stage, adaptive Bayesian randomized controlled trial will be conducted in China. Based on Bayesian methods, the trial will employ response-adaptive randomization to allocate patients to study groups based on data collected over the course of the trial. The adaptive Bayesian trial design will employ a Bayesian hierarchical model with "stopping" and "continuation" criteria once a predetermined posterior probability of superiority or futility and a decision threshold are reached. The trial can be implemented more efficiently by sharing the master protocol and organizational management mechanisms of the sub-trial we have implemented. The primary patient-reported outcome is a change in the Leicester Cough Questionnaire score, reflecting an improvement in cough-specific quality of life. The adaptive Bayesian trial design may be a promising method to facilitate the rapid clinical evaluation of TCM effectiveness for PPF, and will provide an example for how to evaluate TCM effectiveness in rare and refractory diseases. However, due to the complexity of the trial implementation, sufficient simulation analysis by professional statistical analysts is required to construct a Bayesian response-adaptive randomization procedure for timely response. Moreover, detailed standard operating procedures need to be developed to ensure the feasibility of the trial implementation. Please cite this article as: Zhang C, Nie YS, Zhang CT, Yang HJ, Zhang HR, Xiao W, Cui GF, Li J, Li SJ, Huang QS, Yan SY. An adaptive Bayesian randomized controlled trial of traditional Chinese medicine in progressive pulmonary fibrosis: Rationale and study design. J Integr Med. 2025; 23(2): 138-145.
Female ; Humans ; Male ; Bayes Theorem ; Disease Progression ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional/methods* ; Pulmonary Fibrosis/therapy* ; Quality of Life ; Randomized Controlled Trials as Topic ; Research Design ; Adaptive Clinical Trials as Topic

OBJECTIVE: This study aimed to investigate the impact of glycemic control and diabetes duration on subsequent myocardial infarction (MI) in patients with both coronary heart disease (CHD) and type 2 diabetes (T2D). METHODS: We conducted a retrospective cohort study of 33,238 patients with both CHD and T2D in Shenzhen, China. Patients were categorized into 6 groups based on baseline fasting plasma glucose (FPG) levels and diabetes duration (from the date of diabetes diagnosis to the baseline date) to examine their combined effects on subsequent MI. Cox proportional hazards regression models were used, with further stratification by age, sex, and comorbidities to assess potential interactions. RESULTS: Over a median follow-up of 2.4 years, 2,110 patients experienced MI. Compared to those with optimal glycemic control (FPG < 6.1 mmol/L) and shorter diabetes duration (< 10 years), the fully-adjusted hazard ratio ( HR) (95% Confidence Interval [95% CI]) for those with a diabetes duration of ≥ 10 years and FPG > 8.0 mmol/L was 1.93 (95% CI: 1.59, 2.36). The combined effects of FPG and diabetes duration on MI were largely similar across different age, sex, and comorbidity groups, although the excess risk of MI associated with long-term diabetes appeared to be more pronounced among those with atrial fibrillation. CONCLUSION Our study indicates that glycemic control and diabetes duration significant influence the subsequent occurrence of MI in patients with both CHD and T2D. Tailored management strategies emphasizing strict glycemic control may be particularly beneficial for patients with longer diabetes duration and atrial fibrillation.
Humans ; Diabetes Mellitus, Type 2/blood* ; Male ; Female ; Middle Aged ; Aged ; Coronary Disease/complications* ; Myocardial Infarction/etiology* ; Retrospective Studies ; China/epidemiology* ; Glycemic Control ; Blood Glucose ; Adult ; Risk Factors ; Time Factors