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 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.

ObjectiveTo understand the whole genome characteristics and the information for genetic evolution in the two coxsackievirus A2 (CVA2) strains isolated from patients with herpangina in Shanghai, and to provide a scientific basis for the prevention and treatment of herpetic angina. MethodsTwo CAV2 strains isolated from patients with herpetic angina in Shanghai were performed whole genome sequencing and analysis for phylogenetics, nucleotide homology, and evolution. ResultsA phylogenetic analysis of the VP1 region revealed that the two Shanghai strains both belonged to CVA2 genotype D, with the highest homology to OL357660, a strain from Yunnan. The average nucleotide identity (ANI) of the whole genome between the two Shanghai strains was 98.88%, and the ANI of the whole genome comparisons to other CVA2 genotype D strains and CVA2 genotypes A-C strains ranged from 84.64% to 97.42% and from 79.21% to 84.20%, respectively. The two Shanghai strains had low homology in the 3D region compared to the existing CVA2 strains. The phylogenetic analysis and sliding window nucleotide similarity analysis indicated that the two Shanghai strains and the Yunnan OL357660 strain might constitute a new genetic lineage. ConclusionThe two CVA2 strains isolated for the first time in Shanghai are assigned to genotype D (GenBank: PQ130039 and PQ130040), which is identical to the existing subtype prevalent in China. As represented by the Shanghai strains, a new CVA2 genetic lineage is been identified. This study has enriched the data on genetic evolution and genetic variation of CVA2 in Shanghai, indicating the requirement to strengthen surveillance for the epidemiological pattern of CVA2.

Objective To investigate the perioperative differences between video-assisted thoracoscopic surgery (VATS) and thoracotomy after neoadjuvant therapy in patients with non-small cell lung cancer (NSCLC). Methods Clinical data of NSCLC patients who underwent VATS or thoracotomy after neoadjuvant therapy at Shanghai Pulmonary Hospital from June 2020 to May 2022 were retrospectively collected. Perioperative outcomes were compared between the two groups. Results A total of 260 patients were enrolled, 184 (70.8%) patients underwent VATS and 76 (29.2%) patients underwent thoracotomy. After propensity matching, there were 113 (62.4%) patients in the VATS group and 68 (37.6%) patients in the thoracotomy group. VATS had similar lymph node dissection ability and postoperative complication rate with thoracotomy (P>0.05), with the advantage of having shorter operative time (146.00 min vs. 165.00 min, P=0.006), less intraoperative blood loss (50.00 mL vs. 100.00 mL, P<0.001), lower intraoperative blood transfusion rate (0.0% vs. 7.4%, P=0.003), less 3-day postoperative drainage (250.00 mL vs. 350.00 mL, P=0.011; 180.00 mL vs. 250.00 mL, P=0.002; 150.00 mL vs. 235.00 mL, P<0.001), and shorter postoperative drainage time (9.34 d vs. 13.84 d, P<0.001) and postoperative hospitalization time (6.19 d vs. 7.94 d, P=0.006). Conclusion VATS after neoadjuvant therapy for NSCLC is safer than thoracotomy and results in better postoperative recovery.

Volatile organic compounds (VOCs) and semi-volatile organic compounds (SVOCs) are common organic compounds in indoor and outdoor air, and enter the human body primarily through the respiratory tract and directly damage the respiratory system. Previous studies have suggested that exposure to VOCs/SVOCs may associate with the prevalence, incidence, and progression of asthma, but the extent of the associations is still vague. Furthermore, biomarkers for efficient and simple asthma diagnosis, typing, and attack prediction remain unclear at this stage. From the perspective of the collection and detection methods of VOCs/SVOCs, this paper summarized the epidemiological associations and underlying biological mechanisms between VOCs/SVOCs exposure and the prevalence, incidence, and progression of asthma in children/adults. It also demonstrated the application of VOCs/SVOCs in recent years in assisting asthma diagnosis, such as distinguishing asthma patients from the healthy population, differentiating different asthma phenotypes, and predicting asthma acute exacerbations, aiming to provide a scientific basis for improving current asthma management.

In the field of liver transplantation, due to the shortage of donor livers, ABO-incompatible donor livers, as a type of marginal donor livers, have expanded the source of donors for end-stage renal disease patients who are on the brink of death while waiting for liver transplantation. With the continuous progress of various desensitization techniques in the perioperative period, desensitization treatment for ABO-incompatible liver transplantation has achieved certain effects, but the incidence of postoperative complications remains high. In recent years, with the emergence of new desensitization measures, the therapeutic effect of ABO-incompatible liver transplantation has been further improved, but the mechanisms of action and the synergistic effects of drugs still need to be further explored. Given this, this article provides a review of the mechanisms of action, current clinical applications and future development directions of various new desensitization measures. It aims to explore the feasibility of different desensitization measures in ABO-incompatible liver transplantation, provide supporting evidence for clinical application, and thereby improve the prognosis of liver transplant recipients.

Incomplete Miller-Fisher syndrome （MFS） mediated by GT1a antibody often has atypical clinical manifestations and a high misdiagnosis rate. This article reports the diagnosis and treatment of a patient with incomplete MFS mediated by GT1a antibody and discussed clinical manifestations， pathogenesis， and treatment regimens with reference to the relevant literature， so as to improve the understanding of this disease.

Objective: To explore the effect of HIF-1α on osteogenic-angiogenic coupling response in bone mesenchymal stem cells (BMSCs) and provide new concepts for engineered bone tissue in vitro. Methods: With the approval of the hospital’s experimental animal ethics committee, BMSCs were harvested from Wistar rats. The lentivirus carrying hypoxia-inducible factor-1α (HIF-1α) and empty lentivirus were stably transfected into the third generations of BMSCs to form LV-HIF-1α-BMSCs and LV-BMSCs. Meanwhile, BMSCs without transfection of lentivirus were used as a blank control. Then, the effect of HIF-1α transfection was verified by qPCR and Western Blot. LV-HIF-1α-BMSCs were induced to differentiate into endothelium-like cells (iECs). The morphology was observed by optical microscopy, the differentiation rate was detected by cellular flow CD31, and the Transwell test was used to detect the migration ability. At the same time, LV-HIF-1α-BMSCs and LV-BMSCs were continuously cultured to form osteogenic cell sheets (OCTs), which were stained by alkaline phosphatase on day 14 and alizarin red staining on day 21, and counted for mineralization capacity. Finally, iECs were implanted into OCTs to form prevascularized osteogenic cell sheets (P-OCTs), immunofluorescence CD31 was performed to detect the formation of vascular networks, and the results were recorded on days 1, 3, 7, and 14. Meanwhile, osteopontin (OPN) and osteocalcin (OCN) were detected by western blot to verify their ability for osteogenic differentiation on days 1, 7, and 14. Results: The optimal multiplicity of infection (MOI) for lentiviral transfection was 30, and the transfection efficiency was >80%. The results of qPCR and western blot showed that compared with the LV-BMSCs group and BMSCs group, the LV-HIF-1α-BMSCs group had stable and high expressions of HIF-1α (P<0.05). LV-HIF-1α-BMSCs showed an enhanced ability to differentiate into endothelial cells, with a differentiation rate as high as 91.81%. Transwell assay verified that HIF-1α could recruit iECs in vitro. Alkaline phosphatase staining and alizarin red staining confirmed that OCTs formed by LV-HIF-1α-BMSCs had a statistically significant osteogenic differentiation ability compared with LV -BMSCs control group (P<0.05). When iECs were implanted into the LV-HIF-1α-BMSCs group OCTs to form P-OCTs, iECs substantially proliferated and rapidly fused, and formation of the progressive lumen was revealed by immunofluorescent CD31 staining. The expressions of OPN and OCN were significantly enhanced compared with those of the LV-BMSCs control group; OCN was the highest on day 7, and OPN was the highest on day 1 (P<0.05). Conclusion BMSCs transfected by HIF-1α have good osteogenic-angiogenic effect after induction and differentiation, which provides experimental foundation for optimizing the construction of three-dimensional prevascularized bone tissue.