ObjectiveTo construct a risk prediction model for frequent acute exacerbations of chronic obstructive pulmonary disease （COPD） under disease-syndrome combination， thus providing decision support for precise clinical intervention. MethodsA total of 2 029 patients with acute exacerbations of COPD admitted to the First Affiliated Hospital of Anhui University of Chinese Medicine from January 2020 to August 2024 were retrospectively included. These patients were classified into groups of frequent acute exacerbations （≥2 times/year） and infrequent acute exacerbations （<2 times/year） according to the hospitalization times per year. Risk factors were screened by LASSO regression combined with logistic regression， and a nomogram model was constructed. The model performance was assessed based on the area under the curve （AUC）， calibration curves， and decision curve analysis （DCA）. ResultsThe differences in baseline characteristics between the frequent acute exacerbations group （1 196 cases） and infrequent acute exacerbations group （833 cases） were not statistically significant. LASSO regression combined with multivariate logistic regression screened the following independent risk factors： body mass index （BMI）， hospitalization days， number of smoking years， place of residence， use of noninvasive ventilators， oxygen-demanding therapy， liver cirrhosis， use of systemic glucocorticosteroids， and traditional Chinese medicine syndrome （phlegm and stasis obstructing the lung）. The nomogram model showed good discrimination and calibration in both the training set （AUC=0.748） and validation set （AUC=0.774）. ConclusionThe risk prediction model for frequent acute exacerbations of COPD， integrating traditional Chinese medicine syndrome， constructed in this study has high accuracy. It can provide a scientific basis for early clinical identification of high-risk patients and individualized intervention.

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by the selective loss of dopaminergic neurons in the substantia nigra pars compacta and the pathological accumulation ofα‑synuclein. Although extensive progress has been made in elucidating its pathogenesis, current therapeutic approaches remain largely symptomatic, and effective disease-modifying treatments are still unavailable. Increasing evidence indicates that PD is driven by the interaction of multiple pathological processes, including neuroinflammation, iron homeostasis dysregulation and ferroptosis, endoplasmic reticulum (ER) stress, mitochondrial dysfunction, oxidative stress, and impaired protein homeostasis, which together contribute to neuronal vulnerability and degeneration. Fibroblast growth factors (FGFs) comprise a family of 22 ligands that play important roles in neural development, stress responses, metabolic regulation, and the maintenance of nervous system homeostasis. Recent studies have shown that several FGF family members, such as FGF1, FGF2, FGF9, and FGF21, exert neuroprotective effects in cellular and animal models of PD. These effects include the regulation of inflammatory responses, oxidative stress, iron homeostasis, cellular stress adaptation, and neuronal survival. Compared with therapeutic strategies targeting a single pathogenic pathway, FGFs appear to influence multiple disease-related processes, suggesting their potential relevance to the complex pathophysiology of PD. Experimental evidence indicates that altered FGF signaling may contribute to dopaminergic neuron dysfunction through the coordinated regulation of several interconnected mechanisms. FGFs have been reported to modulate neuroinflammation by affecting the activation of microglia and astrocytes, thereby influencing the inflammatory environment in the central nervous system. In addition, FGFs are involved in the regulation of iron homeostasis and ferroptosis, partly through antioxidant signaling pathways associated with NRF2, SLC7A11, and GPX4. Moreover, FGFs can alleviate ER stress and mitochondrial dysfunction by activating intracellular signaling pathways such as PI3K/AKT, AMPK-PGC-1α, as well as SIRT1-dependent programs, which support cellular energy metabolism and redox balance. Recent advances in single-cell and spatial transcriptomic studies further suggest that FGF signaling is not limited to neuron-intrinsic mechanisms but also involves interactions among different glial cell types. Altered FGF ligand-receptor communication between astrocytes and oligodendrocytes has been observed in PD models and is associated with increased susceptibility of dopaminergic neurons to oxidative stress and ferroptosis. These findings indicate that the biological effects of FGFs are influenced by cell type and disease stage and may vary under different pathological conditions. In this review, we summarize recent progress in understanding the roles of FGF family members in PD, with a focus on their involvement in iron homeostasis dysregulation and ferroptosis, neuroinflammation, cellular stress responses, and neuronal protection and regeneration. By integrating current evidence, this review aims to provide a clearer understanding of how FGFs participate in PD pathogenesis and to offer a theoretical basis for future studies exploring their potential value in disease-modifying therapeutic strategies.

[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。

Objective To explore the clinical efficacy of the medicated stick massage at meridian knot points in treating Qi stagnation and blood stasis type lumbar disc herniation(LDH)based on the meridian theory.Methods The patients with LDH in the ward 5 of orthopedics department in this hospital from Sep-tember 2024 to April 2025 were selected as the research subjects.On the basis of routine treatment and care,the control group adopted the medicated stick massage at points,while the experimental group adopted the medicated stick massage at meridian knots.The visual analogue scale(VAS)scores,Japanese Orthopaedic So-ciety(JOA)score,TCM syndrome scores and TCM syndrome therapeutic effects before intervention and in two weeks after intervention were compared between the two groups.Results The VAS scores,each item score and total score of JOA,TCM syndrome scores and TCM therapeutic effects after 2-week intervention in the experimental group all were superior to those in the control group,and the differences were statistically significant(P＜0.05).Conclusion Selecting the medicated stick massage at the meridian knots under the guidance of meridian theory could significantly improve the pain symptoms,lumbar function,TCM syndrome scores,the therapeutic effects are definite,and is worthy of clinical promotion and application.

Objective:To investigate the risk factors of skin adverse events associated with immune checkpoint inhibitor (ICI) therapy in patients with urologic neoplasms, and establish a predictive model.Methods:A single-center retrospective case-control study enrolled 91 advanced urologic neoplasms patients who received ICI therapy at the Department of Urology, Beijing Friendship Hospital, Capital Medical University from January 2020 to June 2025. Patients were divided into the skin lesion group ( n=44) and the control group ( n=47). Patients in the skin lesion group experienced related skin adverse events during ICI treatment, while patients in the control group did not experience such events during ICI treatment. The general data and laboratory indicators were compared between the two groups. The normally distributed measurement data were expressed as mean±standard deviation ( ± s), and the independent sample t-test was used for comparison between groups; the non-normally distributed measurement data were expressed as the median (interquartile range) [ M ( Q1, Q3)], and the Kruskal-Wallis test was used for comparison between groups. The count data were expressed as the number of cases and percentages, and the Chi-test was used for comparison between groups. First, a univariate analysis was conducted on the influencing factors of skin adverse events in patients with urologic neoplasms after ICI treatment. Then, the indicators with statistically significant differences in the univariate analysis were further included in the multivariate Logistic regression model to screen the independent risk factors for predicting skin adverse events. The R software was used to incorporate the factors with significant differences from multivariate analysis into the prediction model and construct a Nomogram. The calibration curve was utilized to evaluate the consistency between predicted values and actual observed results. Meanwhile, the discrimination of the model was verified by the receiver operating characteristic (ROC) curve and the area under the curve (AUC), so as to comprehensively verify the reliability and clinical application value of the prediction model. Results:The results of univariate analysis showed that there were statistically significant differences between the skin lesion group and the control group in terms of the proportion of other immune responses, serum albumin level, absolute eosinophil count, and C-reactive protein (CRP) levels ( P<0.05). These factors were included in multivariate Logistic regression, which identified elevated absolute eosinophil count and elevated CRP as the independent risk factors for related skin adverse events in patients with urologic neoplasms after ICI treatment. A predictive nomogram was built based on these factors. The calibration curve showed high consistency between predicted and actual probabilities, and ROC analysis confirmed the combined model had high predictive value (AUC=0.883, P<0.001). Conclusions:Elevated absolute eosinophil count and elevated CRP level are independent predictors of immune-related skin adverse events in urologic neoplasms patients after ICI treatment. The prediction model constructed based on these two factors facilitates early clinical screening and identification of high-risk patients.

Objective:To evaluate the value of a combined model based on primary lesion 18F-fluorodeoxyglucose ( 18F-FDG) PET/CT radiomics for predicting lymph node metastasis in non-small cell lung cancer (NSCLC) . Methods:A retrospective analysis was conducted on the clinical data of 203 NSCLC patients who underwent pre-treatment PET/CT imaging at Nanjing Drum Tower Hospital from June 2013 to July 2023. Patients were randomly assigned to the training set ( n=142) and the validation set ( n=61) at a ratio of 7∶3. A predictive model was developed in the training set, and its predictive performance and clinical application value were assessed in both the training and validation sets. Traditional PET/CT parameters and PET/CT radiomics features of the primary lesion were obtained by 3D-slicer software. Least absolute shrinkage and selection operator (LASSO), random forest, and extreme gradient boosting were performed to extract features. Support vector machine was used to construct a radiomics score (Radscore). Univariate and multivariate logistic regression analysis was used to predict the influencing factors of lymph node metastasis in NSCLC patients and to establish models. Predictive performance of the models was evaluated by receiver operator characteristic (ROC) curves and clinical application value was assessed by calibration curves and decision curve analysis (DCA) . Results:Among 203 NSCLC patients, 116 had lymph node metastasis, with 64 cases in the training set and 52 cases in the validation set. Three complementary classical machine learning methods were used for feature screening, and finally 10 radiomics features were obtained. The optimal threshold for Radscore-PET was 0.43 and the optimal threshold for Radscore-CT was 0.39. Univariate analysis showed that, sex ( OR=0.48, 95% CI: 0.24-0.95, P=0.036), tumor marker levels ( OR=3.81, 95% CI: 1.84-7.91, P<0.001), long diameter of tumor ( OR=2.56, 95% CI: 1.27-5.16, P=0.009), short diameter of tumor ( OR=3.73, 95% CI: 1.75-7.92, P=0.001), vacuolar sign ( OR=0.32, 95% CI: 0.12-0.86, P=0.024), ring-like metabolism ( OR=3.67, 95% CI: 1.33-10.13, P=0.012), maximum standardized uptake value (SUV max) ( OR=6.57, 95% CI: 3.03-14.25, P<0.001), metabolic tumor volume (MTV) ( OR=2.91, 95% CI: 1.43-5.92, P=0.003), total lesion glycolysis (TLG) ( OR=4.23, 95% CI: 2.08-8.59, P<0.001), Radscore-PET ( OR=21.93, 95% CI: 9.04-53.20, P<0.001) and Radscore-CT ( OR=13.72, 95% CI: 6.12-30.76, P<0.001) were all influencing factors for predicting lymph node metastasis in NSCLC patients. Multivariate analysis showed that, tumor marker levels ( OR=2.55, 95% CI: 1.11-5.90, P=0.028), vacuolar sign ( OR=0.26, 95% CI: 0.08-0.83, P=0.023), SUV max ( OR=5.94, 95% CI: 1.99-17.75, P=0.001), Radscore-PET ( OR=25.51, 95% CI: 5.92-110.22, P<0.001), and Radscore-CT ( OR=8.68, 95% CI: 2.73-27.61, P<0.001) were independent influencing factors for predicting lymph node metastasis in patients with NSCLC. Based on the above independent influencing factors, models were constructed: the traditional model (tumor marker levels, vacuolar sign, SUV max), the PET model (SUV max, Radscore-PET), the CT model (vacuolar sign, Radscore-CT), and the combined model (tumor marker levels, vacuolar sign, SUV max, Radscore-PET, Radscore-CT). ROC curve analysis showed that, the area under curve (AUC) of the traditional, PET, CT, and combined models in the training set were 0.75 (95% CI: 0.67-0.82), 0.90 (95% CI: 0.84-0.95), 0.85 (95% CI: 0.78-0.90), and 0.94 (95% CI: 0.88-0.97), respectively. The predictive value of the combined model was higher than that of the traditional model ( Z=5.01, P<0.001), the PET model ( Z=1.99, P=0.047), and the CT model ( Z=3.25, P=0.001). In the validation set, the AUCs for the traditional model, PET model, CT model, and combined model were 0.65 (95% CI: 0.52-0.77), 0.86 (95% CI: 0.74-0.93), 0.85 (95% CI: 0.73-0.93), and 0.90 (95% CI: 0.80-0.96), respectively. The predictive value of the combined model was superior to that of the traditional model ( Z=3.23, P=0.001). The sensitivity and specificity of the combined model in the training set were 84.37% and 91.03%, while in the validation set, the sensitivity and specificity were 82.61% and 94.74%, respectively. Calibration curves showed a good agreement between the predicted and actual probabilities in both the training and validation sets. DCA showed that the combined models had good discriminative ability in both the training and validation sets. Conclusions:Tumor marker levels, vacuolar sign, SUV max, Radscore-PET, and Radscore-CT are all independent influencing factors for predicting lymph node metastasis in patients with NSCLC. The combined model based on these factors demonstrates excellent predictive performance and clinical application value for predicting lymph node metastasis in NSCLC.

Objective To conduct an analysis on objective data of tongue manifestations and complexions among college students with yang deficiency constitution and balanced constitution,thus to explore the correlation between yang deficiency constitution and the objective data of tongue manifestations and complexions among college students.Methods From August 2023 to January 2024,data collection was carried out in 325 cases of yang deficiency constitution(yang deficiency group)and 175 cases of balanced constitution(balanced group)from college students of Hunan University of Chinese Medicine,Central South University,Hunan Normal University,Hunan University and Changsha University of Science and Technology in Hunan Province.YM-MA-Ⅰ digital detection system for tongue manifestations and complexions of traditional Chinese medicine(TCM)was utilized for data collection and image analysis,and the differences in the Lab parameters of tongue color,tongue shape,tongue coating color,complexions,and lip color were compared between yang deficiency group and balanced group.Of the Lab parameters,letter"L"stands for luminance,which expresses the luminance from absolute black to absolute white,and takes the value of 0-100;letter"a"and letter"b"stand for two color channels,letter"a"represents the color from dark green to grey then to bright pink,and takes a value from-128 to 127,and letter"b"represents the color from bright blue to grey then to yellow,and also takes a value from-128 to 127.Results(1)The analysis of tongue manifestations showed that in comparison with the balanced group,enlarged tongue(72.62％),tooth-marked tongue(83.69％),and greasy coating(59.38％)were frequently seen in the yang deficiency group,and the differences were all statistically significant(P＜0.05 or P＜0.01).(2)The analysis of complexions showed that in comparison with the balanced group,lusterless complexion(79.08％)and pale lip(42.15％)were frequently seen in the yang deficiency group,with statistically significant differences(P＜0.01).(3)The yang deficiency group had higher L value of tongue color,L value of tongue coating color,L value of complexions,and L and b values of lip color than the balanced group,and the differences were all statistically significant(P＜0.05),indicating that the tongue color,complexions,and lip color of the yang deficiency group were all pale.Conclusion The objective data and image analysis of tongue manifestations and complexions can accurately identify the population of yang deficiency constitution from college students,and the results will provide approaches and references for the identification of other TCM constitutions from the population.

Objective:To investigate the relationship among social support, anxiety and cancer pain behavior in patients undergoing radiotherapy for advanced colorectal cancer, and to explore the mediating role of social support between anxiety and cancer pain behavior.Methods:A sample of 100 patients with advanced colorectal cancer admitted to the Oncology Radiotherapy Department of the Affiliated Hospital of Jiangnan University was recruited from March 2021 to March 2023. The hospital anxiety and depression scale (HADS), perceived social support scale (PSSS) and visual analogue scale (VAS) were utilized to assess patients' anxiety levels, individually perceived levels of social support and cancer pain intensity.The SPSS 25.0 software and AMOS 26.0 software were used for data analysis.Pearson correlation analysis was conducted to examine the relationships between these variables, and the Bootstrap method was employed to investigate the mediating role of social support in the relationship between anxiety and cancer pain behavior.Results:The patients' HADS anxiety score was (10.63±2.56), VAS pain score was (5.31±1.92), and PSSS social support score was (56.19±6.28). Pearson correlation analysis showed that anxiety was positively correlated with cancer pain behavior ( r=0.785, P<0.001), and social support was significantly correlated with both anxiety ( r=0.671) and cancer pain behavior ( r=0.672) (both P<0.001). Structural equation modeling indicated that social support partially mediated the relationship between anxiety and cancer pain behavior, with an indirect effect value of 0.177 (95% CI=0.033-0.287), accounting for 22.55%(0.177/0.785) of the total effect and the direct effect value was 0.608 (95% CI=0.287-0.642), accounting for 77.45%(0.608/0.785) of the total effect. Conclusion:Social support plays a mediating role in the effect of anxiety on cancer pain behavior in patients with advanced colorectal cancer undergoing radiotherapy. Enhancing social support can effectively alleviate anxiety in patients with advanced colorectal cancer undergoing radiotherapy, thereby alleviating cancer pain behavior, providing a theoretical basis for clinical comprehensive interventions.

Executive function(EF) is an advanced cognitive function of the central nervous system, and is closely related to an individual's capacity for daily living and adaptation. Patients with attention deficit hyperactivity disorder (ADHD) typically exhibit significant executive dysfunction. While most existing studies on the executive function of individuals with ADHD are cross-sectional, and little is known about the longitudinal maturation process of related brain structures and functional connectivity patterns. The findings indicate that ADHD patients exhibit differential developmental trajectories in brain structural and functional connectivity compared with typically developing group.Furthermore, there is a lifespan association between abnormal brain network development and ADHD symptoms. This article aims to elucidate the characteristics of executive function deficits in ADHD patients across different developmental stages, examining their relationship with the nervous system’s development from a development perspective.

Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.