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.

BackgroundLow medication compliance among patients with severe mental disorders increases the disease burden on both the patients' families and the society. Medication adherence is influenced by numerous factors. Traditional methods such as Logistic regression struggle to quantify the importance of these factors. By introducing Extreme Gradient Boosting （XGBoost） combined with Shapley Additive Explanations （SHAP）， enables the quantification of the relative contribution weights of each factor， providing support for identifying the core influencing factors. ObjectiveTo explore the influencing factors of medication adherence among patients with severe mental disorders in Zhuhai， aiming to provide references for optimizing patient management strategies. MethodsExtract the data of patients with severe mental disorders who were registered on the mental health system platform in Zhuhai City from January 1， 2023 to March 31， 2025. A total of 9 329 patients were finally included for analysis. Influencing factors were screened using univariate analysis and multivariate logistic regression analysis， and an XGBoost model combined with the SHAP algorithm was constructed to quantify the importance of each influencing factor. ResultsAmong 9 329 patients， 8 446 demonstrated medication adherence， yielding an adherence rate of 90.53%. Multivariable analysis identified several risk factors significantly associated with medication non-adherence， being unmarried （OR=1.237， 95% CI： 1.019–1.502） or divorced （OR=1.389， 95% CI： 1.038–1.832）， a diagnosis of mental retardation with psychiatric disorders （OR=3.025， 95% CI： 2.402–3.796） or paranoid psychosis （OR=5.117， 95% CI： 3.086–8.299）， a disease duration of 2–4 years （OR=1.355， 95% CI： 1.085–1.696）， 4–6 years （OR=2.143， 95% CI： 1.671–2.747）， or >6 years （OR=1.681， 95% CI： 1.365–2.079）， lack of guardian subsidies （OR=1.412， 95% CI： 1.099–1.801）， absence of a disability certificate （OR=1.900， 95% CI： 1.588–2.282）， not being enrolled in care and support groups （OR=1.384， 95% CI： 1.183–1.617） or community services （OR=1.313， 95% CI： 1.042–1.645）， and not cohabiting with a guardian （OR=1.257， 95% CI： 1.048–1.501）. Conversely， the enrollment in special outpatient disease programs （OR=0.716， 95% CI： 0.609–0.842） and a family history of mental illness （OR=0.713， 95% CI： 0.503–0.982） were identified as protective factors. The XGBoost model exhibited robust predictive performance， with a sensitivity of 0.433， specificity of 0.944， accuracy of 0.891， Area Under the Curve （AUC） of 0.837， and F1 value of 0.449. Feature importance ranking indicated that the top three factors were disease duration， diagnosis， and the acquisition of disability certificates. ConclusionPolicy-based support （acquisition of disability certificates， special outpatient disease enrollment） and clinical disease characteristics （disease duration， diagnosis type） are key factors affecting medication adherence among patients with severe mental disorders in Zhuhai City. ［Funded by Zhuhai Medical Research Project （number， 2220009000281）］

Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

ObjectiveThe most prevalent mRNA modification, N6-methyladenosine (m⁶A) plays an important role in various RNA metabolism, including gene expression and translation. By recruiting different “reader” proteins and their cofactors, m⁶A modification can affect messenger RNA (mRNA) degradation, splicing, nuclear export and translation. However, the selective mechanism by which m⁶A sites regulate mRNA translation through m⁶A reader YTHDF1 binding remains poorly understood, due to a lack of computational methods for identifying context-specific m⁶A sites that regulate translation. To address this, we developed a novel computational framework named m⁶ATEpre, the first tool designed to predict cell-specific m⁶A sites that regulate translation efficiency. Methodsm⁶ATEpre integrates multi-omics data, introduces a novel feature representation strategy for m⁶A site sequences, and employs an autoencoder to effectively capture embedded feature representations. Specifically, m⁶ATEpre first integrated MeRIP-seq data and PAR-CLIP data through overlapping m⁶A sites with YTHDF1 binding sites and identified YTHDF1-mediated m⁶A sites. Then, m⁶ATEpre detected the translation gene by analyzing the Ribo-seq data under YTHDF1 knockdown vs control condition. Genes whose translation is mediated by YTHDF1 in an m⁶A-dependent manner were identified by a significant decrease in translation efficiency upon YTHDF1 knockdown. Next, we proposed a binary vector indicating the presence or absence of YTHDF1 binding motifs to characterize each m⁶A site sequence. This represents a novel feature representation strategy for m⁶A sites. m⁶ATEpre utilized the autoencoder to extract the potentially important feature representations and constructed a multilayer perceptron neural networks model to predict potential m⁶A sites that regulating translation efficiency. ResultsA comprehensive evaluation of m⁶ATEpre was conducted through a series of experiments. We compared its performance against that of a similar prediction task model, as well as other classifiers. The results indicate that m⁶ATEpre achieved the best prediction performance. In addition, we analyzed different feature representation strategies and performed ablation experiments to validate the rationality of the model design. The results demonstrate that our proposed feature representation strategy has a greater advantage in improving prediction performance. In the HeLa cell line, bioinformatic analysis of the metagene distribution and sequence minimum free energy of m⁶A sites regulating translation efficiency (m⁶A-reg-TE sites) revealed their specific properties in translation regulation. Functional enrichment analysis indicated that m⁶A-reg-TE genes are associated with specific biological processes and KEGG pathways. By integrating the binding sites of YTHDF1 co-factors with m⁶A-reg-TE sites, we revealed that YTHDF1-mediated and m⁶A-dependent translation efficiency regulation requires the cooperation of multiple translation-regulatory RNA-binding proteins among its co-factors in the HeLa cell line. Furthermore, we extended our predictions to the dataset of the HEK293T cell line. Similarly, bioinformatic analysis of the metagene distribution and functional enrichment revealed the cell-specific characteristic of these predicted m⁶A-reg-TE sites in HEK293T cells. Likewise, integrated analysis of multiple YTHDF1 co-factors and m⁶A-reg-TE sites predicted in the HEK293T cell line reveals their m⁶A-dependent cooperation in regulating translation efficiency. Conclusionm⁶ATEpre is a timely tool that will advance our understanding of the mechanisms of m⁶A regulation in translation efficiency. The source code and datasets used in this work can be downloaded from https://www.scidb.cn/s/bAZZFr.

ObjectiveTo investigate whether Carthamus tinctorius L.-derived nanovesicles （CDNVs） can alleviate angiotensin Ⅱ （ANGⅡ）-induced cardiomyocyte （H9C2） hypertrophy by inhibiting the NF-κB signaling pathway and to elucidate the underlying molecular mechanisms. MethodsCDNVs were isolated and purified by ultracentrifugation combined with sucrose density gradient centrifugation， and their morphology and particle size distribution were identified by transmission electron microscopy and nanoparticle tracking analysis. Rat H9C2 cardiomyocytes were cultured in vitro and randomly divided into the normal control group （NC）， ANGⅡ （1.0 μmol/L） group， ANGⅡ+CDNVs group， and ANGⅡ+CDNVs+NF-κB activator 1 group. After 24 h of intervention， cell viability was detected by the CCK-8 assay， the expression of myocardial hypertrophy-related genes （ANP， BNP） was determined by qPCR， the relative cell area was measured by phalloidin staining， the expression of hypertrophy marker proteins and NF-κB pathway proteins （P-p65/p65， P-IκBα/IκBα） was examined by Western blot， and nuclear translocation of p65 was observed by immunofluorescence. Subsequently， NF-κB signaling pathway agonist activator 1 was added， and the expression of myocardial hypertrophy marker proteins and NF-κB pathway proteins was detected. ResultsCDNVs exhibited a typical round-like vesicle structure with an average particle size of 140.4 nm， which was consistent with the morphological characteristics of exosomes. ANGⅡ at concentrations of 0.1-1.0 μmol/L had no significant effect on cardiomyocyte viability. Compared with the NC group， ANGⅡ significantly upregulated the gene expression of ANP and BNP， increased the relative surface area of cardiomyocytes， elevated the levels of myocardial hypertrophy marker proteins and NF‑κB pathway proteins， and promoted the nuclear translocation of p65 （P<0.05）. Following treatment with CDNVs， all the above indicators were markedly reduced in comparison with the ANGⅡ group （all P<0.05）. However， all these experimental results were reversed after the addition of an NF‑κB agonist. ConclusionCDNVs alleviate ANGⅡ-induced H9C2 cell hypertrophy by inhibiting the NF-κB signaling pathway.

Objective To identify core targets of hepatocellular carcinoma (HCC) by using bioinformatics and specific algorithms, explore their relationships with immune cells, and investigate the causal relationships between immune cells and HCC through Mendelian randomization. Methods Relevant genes associated with the development of HCC were screened using the GEO and TCGA databases. Immune infiltration analysis was conducted using GSVA and CIBERSORT algorithms. A bidirectional Mendelian randomization analysis was then performed to explore the causal relationships between immune cells and HCC. Results A total of 284 HCC-related genes were identified, with 120 genes recognized within the protein interaction network. Immune infiltration analysis revealed significant correlations between key genes and immune cells. Mendelian randomization results indicated that HLA DR on CD33⁺ HLA DR⁺ CD14dim (OR=1.097, 95%CI: 1.002–1.201, P=0.045, P_Bonferroni=0.091) and CD8 on CD28⁺ CD45RA⁺ CD8⁺ T cell (OR=1.123, 95%CI: 1.027–1.228, P=0.011, P_Bonferroni=0.022) were the risk factors for HCC. Conversely, HLA DR⁺⁺ monocyte absolute count was identified as a protective factor for HCC (OR=0.812, 95%CI: 0.702–0.938, P=0.005, P_Bonferroni=0.139). Conclusion The occurrence and development of liver cancer may be related to CDK1, CCNB1, and CDC20, showing a high degree of correlation with Th2 cells, T helper cells, Th17 cells, and DCs. Mendelian randomization shows that HLA DR on CD33⁺HLA DR⁺ CD14dim and CD8 on CD28⁺CD45RA⁺CD8⁺T cells are associated with an increased risk of HCC. The risk of hepatocellular carcinoma is associated with a decrease in the level of HLA DR⁺⁺monocyte absolute count.

ObjectiveTo investigate the efficacy and safety of stereotactic body radiotherapy （SBRT） combined with sintilimab and bevacizumab in the treatment of patients with unresectable hepatocellular carcinoma （uHCC） and related prognostic factors. MethodsA total of 42 patients with uHCC who underwent SBRT combined with sintilimab and bevacizumab in Department of Radiation Oncology， The Fifth Medical Centre of PLA General Hospital， from March to December 2022 were enrolled. The prescribed dose of planning target volume was 36‍ ‍—‍ ‍50 Gy in 5‍ ‍—‍ ‍6 fractions for continuous irradiation， followed by the regimen of sintilimab and bevacizumab. Each course of treatment was 3 weeks until the presence of tumor progression or serious adverse events. The Kaplan-Meier method was used to calculate overall survival （OS） rate and progression-free survival （PFS） rate， and the log-rank test was used for comparison between groups； the Cox proportional hazards model was used to investigate the influencing factors for prognosis. ResultsThe median follow-up time was 21.6 months， with an objective response rate of 69%， a disease control rate of 85.7%， a median PFS of 10.0 months （95% confidence interval ［CI］： 6.7‍ ‍—‍ ‍13.0）， and a median OS of 23.3 months （95%CI： 14.7‍ ‍—‍ ‍31.8）. Most adverse events were grade 1‍ ‍—‍ ‍2 events， and there were no fatal adverse events. At 6‍ ‍—‍ ‍8 weeks after treatment， the AFP response group had a significantly better OS than the non-AFP response group （not reached vs 11.8 months， P=0.007）. The multivariate analysis showed that AFP response was associated with the good prognosis of patients （hazard ratio=0.31， 95%CI： 0.13‍ ‍—‍ ‍0.75， P=0.009）. ConclusionFor patients with uHCC， SBRT combined with sintilimab and bevacizumab can improve survival with a manageable safety profile， and a >50% reduction in AFP at 6‍ ‍—‍ ‍8 weeks after treatment can be used as a potential prognostic indicator.

Endometrial cancer is one of the common malignant tumors of the female reproductive system.Its incidence rate in China is second only to cervical cancer,posing a serious threat to women's life and health,and the onset shows a trend of affecting younger individuals.Currently,the primary treatment for endometrial cancer is surgical intervention,and some postoperative patients and those with postoperative recurrence require adjuvant radiotherapy.Pelvic external beam radiotherapy(EBRT)and vaginal brachytherapy(VBT)are two modalities of postoperative radiotherapy.The appropriate postoperative radiotherapy approach should be selected based on individual conditions and guideline recommendations.Most patients can achieve satisfactory treatment outcomes through surgery and postoperative adjuvant radiotherapy.However,the specific indications for postoperative radiotherapy in endometrial cancer patients and the radiotherapy principles for those with postoperative recurrence are relatively complex,and recommendations for radiotherapy modalities in postoperative patients vary slightly across different guidelines.This article reviews the treatment principles for endometrial cancer patients in recent years,as well as the indications for postoperative and post operative recurrent radiotherapy and the radiotherapy techniques,aiming to provide a reference for radiotherapy in the endometrial cancer patients.

Objective To investigate the predictive value of β3-adrenergic receptor(β3-AR)expression levels for recurrence after radiofrequency ablation in patients with atrial fibrillation(AF).Methods Patients with AF who underwent their first radiofrequency ablation in the Department of Cardiology from January 2022 to February 2024(AF group,n=166)and healthy individuals undergoing routine medical check-ups during the same period(control group,n=100)were selected as study subjects.Based on whether AF recurred after the procedure during follow-up,AF patients were divided into a non-recurrence group and a recurrence group.General clinical data and relevant laboratory indices of AF patients were collected.The relative expression lev-el of lymphocyte β3-AR mRNA was measured using fluorescence real-time quantitative PCR.Multivariate lo-gistic regression analysis was used to identify risk factors for AF recurrence after surgery,and receiver operat-ing characteristic(ROC)curve analysis was employed to evaluate the predictive value of β3-AR mRNA ex-pression levels for AF recurrence after ablation.Results After 9 months of follow-up post-radiofrequency ab-lation,among 166 AF patients,42 experienced recurrence,with a recurrence rate of 25.3%.Compared with the non-recurrence group,patients in the recurrence group had significantly higher levels of sST2,IL-6 and left at-rial diameter(LAD),with a statistically significant differences(P<0.05).The relative expression level of β3-AR was higher in the recurrence group than in the non-recurrence group,with a statistically significant differ-ence(P<0.05).Multivariate logistic regression analysis showed that LAD,sST2,IL-6,and β3-AR were inde-pendent risk factors for AF recurrence after surgery(P<0.05).ROC curve analysis indicated that the area under the curve for β3-AR mRNA relative expression level in predicting AF recurrence after radiofrequency ablation was 0.884(95%CI:0.794 to 0.975;P<0.05).Conclusion High preoperative expression levels of β3-AR in AF patients are associated with recurrence after radiofrequency ablation,and β3-AR can serve as a potential biological marker for predicting AF recurrence.

objective:To investigate the factors influencing failure of preoperative optimisation with exclusive enteral nutrition(EEN)in patients with Crohn's disease(CD)and to construct a predictive model.Methods:Clinical data of 161 patients with Crohn's disease who underwent surgical treatment after preoperative EEN optimization at the Inflammatory Bowel Disease Center of General Surgery of the Eastern Theater General Hospital from June 2021 to November 2023 were retrospectively analyzed.Patients were divided into two groups according to the preoperative EEN optimisation effect:optimisation success and optimisation failure.Logistic regression analysis was used to determine the factors influencing optimisation failure,and a column line graphical model was constructed using R4.4.0 software.Results:After at least 4 weeks of EEN treatment,a total of 44 patients(27.33%)failed preoperative optimization.Multifactorial analysis showed that FC>500 μg/g and use of corticosteroids were independent risk factors for failure of preoperative optimization,and an increase in prealbumin after 1 week of treatment was a protective factor for successful preoperative optimization.Based on the results of the multivariate analysis,a column graph was constructed,and the C-index was 0.873(95%CI=0.783～0.964).The calibration curve shows that the probability of failure predicted by the nomogram model prior to optimization is in good agreement with the actual probability.The clinical decision curve confirms that the risk threshold is between 0.03～0.96,and the nomogram model can be used to predict the failure of preoperative EEN optimization over other treatment options.Conclusion:FC>500μg/g and history of corticosteroid use were independent risk factors for failure of preoperative optimization,and an increase in prealbumin after 1 week of treatment was a protective factor for successful preoperative optimization.The nomogram constructed on the basis of these results has a good predictive value and is clinically applicable.