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.

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）］

Drawing on recent advances in modern fascial anatomy and biomechanics， this paper interprets the biomechanical implications of yin-yang balance at the physical level from the perspective of holistic force lines. It posits that holistic force lines represent the functional expression of mechanical load transmission and integration within the myofascial network； the channel sinews system and myofascial chains exhibit significant similarities in terms of their distribution， functional attributes， and principles of holistic regulation， and can thus be understood as structural-functional carriers of yin-yang balance. Accordingly， this paper provides a biomechanical interpretation of the yin-yang relationship from four aspects， including interdependence， mutual restriction， dynamic balance through waxing and waning， and mutual transformation， proposing that in a healthy state， the body relies on the continuous integration， distribution， and readjustment of the myofascial tension network to maintain overall coordination， whereas disease states are often associated with compensatory transmission of local tension abnormalities along holistic force lines， the accumulation of imbalances， and structural rigidity. The holistic force-line perspective provides a biomechanical explanatory framework for the theory of yin-yang balance and offers a new theoretical basis for clinical diagnosis and treatment to shift from empirical holistic balancing toward holistic force-line balancing based on posture， function， and tension transmission pathways.

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.

Objective:To investigate the change trend in the burden of 5 common malignant tumors of digestive system (esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer and liver cancer) in the Chinese population from 1990 to 2021.Methods:The descriptive epidemio-logic method was conducted. The number of new cases, crude incidence rate, age-standardized incidence rate, the number of deaths, crude mortality rate and age-standardized mortality rate of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021 of the Global Burden of Disease were collected. The age-standardized rate was calculated based on the standardized demographics of the whole world in the Global Burden of Disease for the year 2021. Observation indicators: (1) The incidence of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021; (2) the mortality of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021; (3) the change trend of age-standardized incidence rate of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021; (4) the change trend of age-standardized mortality rate of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021. The Joinpoint regression model was constructed for trend analysis, specifically to calculate the annual percentage change, average annual percentage change (AAPC), and their 95% confidence interval ( CI) for age-standardized incidence and mortality rates for each cancer type at different time periods. Results:(1) The incidence of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021. The number of new cases of esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer and liver cancer in the Chinese population changed from 207 495, 407 471, 158 389, 37 818 and 96 434 in 1990 to 320 805, 611 799, 658 321, 118 665 and 196 637 in 2021. The crude incidence rates of the above cancer types changed from 17.64/100 000, 34.64/100 000, 13.46/100 000, 3.21/100 000, 8.20/100 000 in 1990 to 22.55/100 000, 43.00/100 000, 46.27/100 000, 8.34/100 000, 13.82/100 000 in 2021. The new cases of esophageal cancer, stomach cancer, colorectal cancer, pancreatic cancer, and liver cancer all showed an increasing trend, with absolute changes of 54.61%, 50.15%, 315.64%, 213.78%, and 103.91%, respectively. (2) The mortality of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021. The number of deaths of esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer and liver cancer in the Chinese population changed from 210 821, 374 066, 119 303, 38 883 and 94 937 in 1990 to 296 443, 445 013, 275 129, 119 602 and 172 068 in 2021. The crude death rates of the above cancer types changed from 17.92/100 000, 31.80/100 000, 10.14/100 000, 3.31/100 000, 8.07/100 000 in 1990 to 20.84/100 000, 31.28/100 000, 19.34/100 000, 8.41/100 000, 12.09/100 000 in 2021. Death cases of esophageal cancer, stomach cancer, colorectal cancer, pancreatic cancer, and liver cancer all showed an increa-sing trend, with absolute changes of 40.61%, 18.97%, 130.61%,207.59%, and 81.24%, respectively. (3) The change trend of age-standardized incidence rate of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021. The change trends of age-standardized incidence rates of esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer, and liver cancer in the Chinese population were divided into 5, 5, 4, 5, and 5 periods, respectively, and the AAPCs of age-standardized incidence rates of the above cancer types were -1.60% (95% CI as -1.78% to -1.42%), -1.60% (95% CI as -1.78% to -1.43%), 1.66% (95% CI as 1.39% to 1.94%), 0.72% (95% CI as 0.36% to 1.08%), and -0.31% (95% CI as -0.39% to -0.23%). (4) The change trend of age-standardized mortality rate of 5 common malignant tumors of digestive system in the Chinese population from 1990 to 2021. The change trend of age-standardized mortality rates of esophageal cancer, gastric cancer, colorectal cancer, pancreatic cancer, and liver cancer in the Chinese population were divided into 5, 5, 4, 5, and 4 periods, respectively, and the AAPC of age-standardized mortality rates for each of the above mentioned cancer types were -1.96% (95% CI as -2.03% to -1.90%), -2.44% (95% CI as -2.50% to -2.38%), -0.49% (95% CI as -0.58% to -0.41%), 0.56% (95% CI as 0.48% to 0.63%), and -0.68% (95% CI as -0.89% to -0.52%). Conclusions:From 1990 to 2021, the disease burden of esophageal cancer, gastric cancer and liver cancer in the Chinese population show a downward trend. The standardized incidence of colorectal cancer shows an upward trend, and the standardized mortality rate shows a downward trend. The disease burden of pancreatic cancer shows an upward trend.

Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.

Objective To explore the application value of combining the ultrasound breast imaging reporting and data system(BI-RADS)classification with serum fibroblast growth factor receptor 1(FGFR1)and growth differentiation factor 3(GDF3)in the differential diagnosis of benign and malignant breast masses.Methods A total of 159 patients with breast masses were selected and divided into the benign mass group(n=83)and the malignant mass group(n=76)based on postoperative pathological diagnosis.All patients underwent ultrasound examination,and enzyme-linked immunosorbent assay(ELISA)was applied to detect serum levels of FGFR1 and GDF3.Receiver operating characteristic(ROC)curve was applied to analyze the diagnostic value of ultrasound BI-RADS classification and serum FGFR1 and GDF3 levels for benign and malignant breast masses.Kappa test was applied to analyze the consistency between various diagnostic methods and pathological diagnosis.Results The serum levels of FGFR1 and GDF3,the proportions of irregular morphology,unclear boundaries,spiculation,microcalcifications,blood flow grade Ⅱ-Ⅲ and posterior echo attenuation,RI and PI were higher in the malignant tumor group than those in the benign tumor group(P＜0.05).The area under the curve(AUC)of FGFR1,GDF3 and ultrasound BI-RADS classification in the differential diagnosis of benign and malignant breast masses separately and in combination was 0.802(95%CI:0.732-0.871),0.817(95%CI:0.751-0.884),0.848(95%CI:0.784-0.912)and 0.956(95%CI:0.918-0.993),respectively.The combined diagnosis was more effective than that of the individual diagnosis of each indicator.The consistency between the individual and combined diagnosis of benign and malignant breast masses and pathological diagnosis showed that the Kappa values were 0.517,0.514,0.688 and 0.912,respectively,with the highest consistency observed in the combined diagnosis(P＜0.05).Conclusion Ultrasound BI-RADS classification combined with serum FGFR1 and GDF3 has high application value in the differential diagnosis of benign and malignant breast masses.

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Objective To explore the mechanism of Jiawei Jisheng Shenqi Decoction in improving the hypoxic microenvironment and antagonizing liver cirrhosis.Methods In vivo experiments were conducted using a rat model of carbon tetrachloride(CCL4)-induced liver cirrhosis.Rats were divided into normal,model,colchicine,JWJSSQ low-dose,JWJSSQ medium-dose,and JWJSSQ high-dose group.Pathological changes in liver tissues in each group were examined by hematoxylin and eosin(HE)and Masson staining,changes in serum liver function were detected using test kits,levels of hyaluronic acid(HA),laminin(LN),procollagen Ⅲ(PC Ⅲ),and collagen typeⅣ(COL4)were detected by enzyme-linked immunosorbent assay(ELISA),and protein expression levels of hypoxia-inducible factor-1α(HIF-1α),Notch1,Jagged1,and α-smooth muscle actin(α-SMA)were detected by Western blot.In vitro experiments were conducted in HSC-T6 cells,and the optimal concentration of CoCl2(100 μ mol/L,200μmol/L,400 μmol/L,600 μmol/L and 800 μmol/L)in the cultured cells and the optimal concentration of drug-containing serum(5％,10％,15％,20％)were determined by Cell Counting Kit-8(CCK-8)assay.The migration ability of cells in each group was detected by scratch testing,and changes in the apoptosis rates were determined by flow cytometry.Protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,matrix metallopeptidase 9(MMP9),and tissue inhibitor of metalloproteinases 1(TIMP-1)were detected by Western blot.Results In the in vivo experiments,liver swelling,inflammatory cell infiltration,collagen deposition,and the appearance of pseudolobules were significantly increased in the model group compared with those in the normal group.Serum levels of alanine aminotransferase(ALT),aspartate aminotransferase(AST),HA,LN,PCⅢ,and COL4 were significantly increased and albumin(ALB)was significantly decreased in the model group,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were significantly increased(P＜0.01).Liver swelling,inflammatory cell infiltration,and collagen deposition were significantly reduced in each treatment group compared with those in the model group,and the degree of fibrosis was reduced.Serum ALT,AST,HA,LN,PCⅢ,and COL4 were significantly decreased and ALB was significantly increased,while liver levels of HIF-1α,Notch1,Jagged1,and α-SMA proteins were also significantly decreased to varying degrees(P＜0.05).In the in vitro experiments,hypoxia promoted HSC-T6 migration and reduced apoptosis,increased the protein expression levels of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1,and reduced the expression levels of MMP9(P＜0.01).Serum containing Jiawei Jisheng Shenqi Decoction inhibited HSC-T6 migration,promoted HSC-T6 apoptosis,lowered the expression of HIF-1α,Notch1,Jagged1,α-SMA,and TIMP-1 proteins,and enhanced the expression of MMP9 protein(P＜0.01).The inhibitory effect of Jiawei Jisheng Shenqi on HSC-T6 cell activation was reversed by the HIF-1α agonist dimethyloxalylglycine.Conclusions Jiawei Jisheng Shenqi Decoction can improve the hypoxic microenvironment via the HIF-1α/Notch pathway,thereby exerting an anti-liver cirrhosis effect.