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 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.

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 analyze the key factors in quality control for clinical laboratory instrument by constructing an analysis framework of the model that entropy weight method(EWM)combines with decision laboratory analysis(DEMATEL),so as to obtain the key factors of quality control for clinical laboratory instrument,and provide a basis in formulating targeted quality control strategies for clinical laboratory instruments.Methods:Based on EWM,the entropy weight values of various factors of quality control for clinical laboratory instruments that produced influence on quality control for clinical laboratory instruments were obtained,and the DEMATEL was combined to determine the value of influence degree among different factors.The combined weight values of each factor were calculated to construct the analysis framework of the model that EWM combined with DEMATEL.Then,the main influencing factors were determined to formulate the model of management system of quality control for clinical laboratory instruments.Results:The management system of quality control for clinical laboratory instruments included 23 key factors of 5 aspects:performance and design of instruments,operators'training and skills,environmental factors,maintenance management,and mechanism of quality feedback.The combined weights of 10 factors,which included maintenance for instrument,operators'experience and proficiency,repair for instrument,operators'understanding for instrument performance,accuracy of instrument,mechanism of quality control and continuous feedback,stability of instrument,data security,suggestions of analyzing and optimizing data,and calibration for instrument,has a relatively high weight,and they were extremely key factors in the quality control for clinical laboratory instruments.Conclusion:The analysis framework of EWM combined with DEMATEL model can improve the accuracy and reliability of analyzing key factors of quality control for clinical laboratory instrument,and provide scientific basis in formulating targeted quality control strategies for clinical laboratory instrument,and help to promote continuous improvement and enhancement of quality control for clinical laboratory instrument.

Objective To explore the value of ECG-less technology and deep learning image reconstruction(DLIR)algorithm for coronary CT angiography(CCTA).Methods Seventy-one patients with suspected coronary artery disease(CAD)were prospectively enrolled and randomly divided into group A(n=35,underwent CCTA using ECG-less technology)and B(n=36,underwent CCTA using physical electrocardiographic gating).CCTA images of group A were reconstructed using filtered back projection(FBP),adaptive statistical iterative reconstruction V(ASiR-V)(50％blending)and high-strength DLIR(DLIR-H),respectively,while those of group B were reconstructed using conventional ASiR-V(50％blending).The radiatio n doses and examination durations of CCTA were compared between groups.Then subjective and objective evaluation of imaging quality were compared between groups and within group A among 3 reconstruction algorithms.Results No significant difference of radiation dose of CCTA was found between groups(P＞0.05).The examination duration in group A was reduced by approximately 29.37％compared to group B(P＜0.05).No significant difference of subjective image quality scores nor objective evaluation of ASiR-V reconstructed CCTA was detected between groups(all P＞0.05).In group A,compared to FBP algorithm,subjective image quality scores of DLIR-H and ASiR-V upgraded,signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)increased and standard deviation(SD)values decreased(all P＜0.05),but no significant difference of CT values was found(all P＞0.05).Conclusion ECG-less technology could significantly shorten CCTA examination duration,while DLIR could reduce image noise and improve image quality of CCTA.

Objective:To investigate the effects of short-peptide-based enteral nutrition on nutritional status, immune function, and chemotherapy-related adverse reactions in children with acute lymphoblastic leukemia (ALL).Methods:A total of 106 children with ALL receiving chemotherapy at the Affiliated Hospital of Jining Medical University between January 2021 and April 2022 were enrolled. According to the principle of between-group baseline data matching, the patients were divided into observation group and control group by random number table method, with 53 cases in each group. All patients received chemotherapy according to the CCCG-ALL-2020 protocol established by the Multi-center Cooperative Group of the Chinese Society of Pediatric Oncology (2020). The control group received a regular diet, while the observation group received a regular diet supplemented with short-peptide-based enteral nutrition. The incidence rates of malnutrition, hypoproteinemia, hypoalbuminemia, abnormal immunoglobulin levels (IgG, IgM, IgA), and adverse reactions (liver injury, infection) were compared between both groups before chemotherapy and at the end of each of the following seven chemotherapy phases: Induction remission therapy (PVDL), Induction remission therapy (CAT), Early intensification therapy (CAT+), Consolidation therapy (HDMTX), Interim maintenance therapy, Reinduction therapy, and prior to the end of Maintenance therapy. Normally or approximately normally distributed measurement data were expressed as xˉ± s and compared by independent samples t-test. Counting data were expressed as n (%) and compared by χ2 test. Results:During the CAT phase, the incidence of malnutrition was significantly lower in the observation group than in the control group [20.8% (11/53) vs. 39.6% (21/53), χ2=4.48, P=0.034]. The incidence of hypoproteinemia was significantly lower in the observation group during HDMTX, Reinduction, Interim maintenance, and prior to the end of Maintenance therapy [47.2% (25/53) vs. 69.8% (37/53), χ2=5.60, P=0.018; 45.3% (24/53) vs. 67.9% (36/53), χ2=5.53, P=0.019; 41.5% (24/53) vs. 64.2% (34/53), χ2=5.45, P=0.020; 28.3% (15/53) vs. 54.7% (29/53), χ2=7.62, P=0.006, respectively]. The incidence of hypoalbuminemia was significantly lower in the observation group during CAT+, HDMTX, Reinduction, Interim maintenance, and prior to the end of Maintenance therapy [5.7% (3/53) vs. 22.6% (12/53), χ2=6.29, P=0.012; 9.4% (5/53) vs. 26.4% (14/53), χ2=5.19, P=0.023; 9.4% (5/53) vs. 28.3% (15/53), χ2=6.16, P=0.013; 7.6% (4/53) vs. 24.5% (13/53), χ2=5.68, P=0.017; 3.8% (2/53) vs. 18.9% (10/53), χ2=6.01, P=0.014, respectively]. For IgG, incidence was significantly lower in the observation group during Interim maintenance, Reinduction, and prior to the end of Maintenance therapy [7.6% (4/53) vs. 22.6% (12/53), χ2=4.71, P=0.030; 20.8% (11/53) vs. 39.6% (21/53), χ2=4.48, P=0.034; 11.3% (6/53) vs. 26.4% (14/53), χ2=3.94, P=0.047, respectively]. For IgM, incidence was significantly lower in the observation group during the CAT and CAT+ phases [45.3% (24/53) vs. 66.0% (35/53), χ2=4.63, P=0.032; 58.5% (31/53) vs. 77.4% (41/53), χ2=4.33, P=0.037, respectively]. For IgA, incidence was significantly lower in the observation group during Reinduction therapy and Interim maintenance [22.6% (12/53) vs. 45.3% (24/53), χ2=6.06, P=0.014; 9.4% (5/53) vs. 24.5% (13/53), χ2=4.28, P=0.038, respectively]. For liver injury, incidence was significantly lower in the observation group during the CAT, CAT+, and prior to the end of Maintenance phases [22.6% (12/53) vs. 43.4% (23/53), χ2=5.16, P=0.023; 26.4% (14/53) vs. 50.9% (27/53), χ2=6.72, P=0.010, 11.3% (6/53) vs. 26.4%(14/53), χ2=3.94、 P=0.047,respectively]. For infection, incidence was significantly lower in the observation group during the CAT+ and HDMTX phases [35.9% (19/53) vs. 56.6% (30/53), χ2=4.59, P=0.032; 24.5% (13/53) vs. 43.4% (23/53), χ2=4.21, P=0.040, respectively]. Conclusions:Short-peptide-based enteral nutrition demonstrates significant advantages in the treatment of pediatric ALL. It provides substantial support for patient treatment and recovery by improving nutritional status, modulating immune function, and reducing chemotherapy-related adverse reactions.

Objective To explore the surgical treatment strategy for patients with thyroid cancer complicated with primary hyperparathyroidism(PHPT).Methods A retrospective analysis was conducted on the case data of thyroid cancer patients who underwent surgical treatment at Beijing Friendship Hospital,Capital Medical University from January 2016 to January 2022.Among them,22 patients with PHPT were included in study group,and 44 patients were randomly selected from thyroid cancer patients during the same period at a ratio of 1∶2 and included in control group.The operation time,intraoperative blood loss,hospital stay and occurrence of complications of two groups of patients were compared.Results The operation time of patients in study group was significantly longer than that in control group(P＜0.01).There was no statistically significant difference in intraoperative blood loss and hospital stay between two groups of patients(P＞0.05).There were 5 cases of temporary hypocalcemia in study group,12 cases of temporary hypocalcemia and 1 case of incision infection in control group.There was no statistically significant difference in incidence of postoperative complications between two groups of patients(P＞0.05).Conclusion Thyroid cancer complicated with PHPT increases the complexity of treatment.Through adequate preoperative diagnosis and reasonable surgical treatment strategies,the risks of secondary surgery and postoperative complications can be effectively reduced,and the prognosis of patients can be improved.

Objective:To retrieve and obtain relevant evidence at home and abroad on the prevention and management of chylous leakage after thyroid cancer surgery, and provide reference for clinical practice.Methods:Based on the 6S pyramid model system, evidence related to the prevention and management of chylous leakage after thyroid cancer surgery in the databases of UpToDate, BMJ best practice, Guidelines International Network (GIN), National Guideline Clearinghouse (NGC), PubMed, EMbase, Wanfang Database, China National Knowledge Infrastructure (CNKI) and other databases, including guidelines, expert consensus, systematic reviews, evidence summary, clinical decisions, and position statements. The retrieval time was from database establishment to June 1st 2024.Results:A total of 16 articles were included, including 5 guidelines, 9 expert consensus, and 2 systematic reviews. The 30 best pieces of evidence were summarized from 6 aspects: preoperative evaluation and preparation, intraoperative prevention, diagnosis, diet and nutrition management, monitoring and treatment, and health education.Conclusions:This study summarized relevant evidence and provides reference for medical staff to formulate intervention measures and management plans for chyle leakage after thyroid cancer surgery.