Objective To investigate muscle mass reduction and the effect of exercise training intervention in non-obese patients with type 2 diabetes (T2DM). Methods A total of 324 non-obese patients with T2DM admitted to the First Affiliated Hospital of Xinjiang Medical University were enrolled from February 2023 to February 2025. Dual-energy X-ray absorptiometry was adopted to detect and analyze the data of appendicular skeletal muscle index (ASMI). Non-obese T2DM patients were classified into an observation group (n=162, receive sports training intervention) and a control group (n=162, receiving routine exercise intervention) by adopting random number grouping criteria. Both groups were intervened for 3 months. The muscle mass indicators [ASMI, body mass index (BMI), and body fat rate], exercise ability [6-minute walking distance (6MWD), grip strength, and one-leg standing time], metabolic indicators [fasting plasma glucose (FPG), glycosylated hemoglobin (HbA1c), and homeostasis model assessment insulin resistance index (HOMA-IR)], and quality of life [Diabetes Quality of Life Scale (DQOL)] were compared between the two groups to evaluate the effectiveness of sports training intervention. Results A total of 324 non-obese T2DM patients were enrolled, including 123 cases with reduced muscle mass (37.96%). There were no significant differences in the baseline data and the proportion of patients with muscle mass reduction between the two groups before intervention (P>0.05). After intervention, the ASMI, 6MWD, grip strength, and one-leg standing time in the observation group were higher or longer than those of the control group (P<0.05), while the body fat rate, FPG, HbA1c, HOMA-IR and DQOL scores were lower than those of the control group (P<0.05). Conclusion The incidence of muscle mass reduction is relatively high among non-obese T2DM patients, and exercise training intervention has significant effects on improving muscle mass, metabolic status, exercise capacity and quality of life in non-obese T2DM patients.

ObjectiveTo analyze the clinicopathological features of patients with comorbidities of chronic hepatitis B （CHB） and steatotic liver disease （SLD）， to investigate the impact of hyperglycemia on the risk of liver fibrosis and end-stage liver diseases （ESLD）， and to provide a basis for the clinical management of such population. MethodsA total of 668 adult patients with CHB-SLD confirmed by liver biopsy in The Fifth Medical Center of Chinese PLA General Hospital from January 2011 to December 2019 were enrolled， and a retrospective cohort was established with the time of liver biopsy as the baseline and the onset of ESLD as the endpoint. All patients were followed up to March 31， 2024. Propensity score matching （PSM） was performed at a ratio of 1∶4 to balance baseline features between groups， resulting in 82 patients in the hyperglycemia group and 281 in the non-hyperglycemia group. The two groups were compared in terms of metabolic profiles， laboratory markers， and histopathological features. The Mann-Whitney U test was used for comparison of non-normally distributed quantitative data between two groups. The chi-square test or Fisher exact test was used for comparison of categorical data between two groups. A multivariate Logistic regression analysis was used to investigate the influencing factors for advanced fibrosis （AF）， and the Kaplan-Meier survival analysis and the Cox proportional-hazards regression model were used to determine the influencing factors for the development of ESLD. ResultsCompared with the non-hyperglycemia group， the hyperglycemia group had a significantly higher number of factors for metabolic disorders， a significantly higher degree of hepatic steatosis， and a significantly higher detection rate of AF （all P<0.05）. The multivariate Logistic regression analysis showed that hyperglycemia was a risk factor for AF （odds ratio = 1.753， 95% confidence interval ［CI］： 1.017　—　3.023， P=0.043）. The survival analysis showed that hyperglycemia increased the risk of ESLD （χ²=4.340， P=0.037）. The multivariate Cox regression analysis confirmed that hyperglycemia was a significant metabolic risk factor for ESLD in patients with AF （adjusted hazard ratio=3.208， 95%CI： 1.201　—　8.568， P=0.020）. ConclusionHyperglycemia can increase the risk of AF and ESLD in CHB-SLD patients. Clinical monitoring and active management should be strengthened for patients who have already developed AF and hyperglycemia.

ObjectiveTo explore the latent profiles of sleep patterns and their association with gastrointestinal heat accumulation syndrome in preschool children in Beijing. MethodsA cross-sectional study design was adopted， and preschool children were recruited from 57 kindergartens in Beijing using convenience sampling. Sleep characteristics and gastrointestinal heat accumulation syndrome was assessed using the Chinese version of the Sleep Disturbance Scale for Children （SDSC） and Self-rating Diagnostic Scale for Gastrointestinal Heat Retention Syndrome in children （GHRS）. Latent profile analysis （LPA） was applied to identify distinct sleep-related subgroups， and multivariate logistic regression was used to analyze the association between different sleep profiles and gastrointestinal heat accumulation syndrome. ResultsA total of 6878 preschool children were included in the study. Among them， 3.46% of the children （238/6878） had sleep disorders， while 54.42% （3743/6878） had gastrointestinal heat accumulation. Compared to children without gastrointestinal heat accumulation syndrome， those with this syndrome exhibited a higher prevalence of sleep disorders， higher SDSC scores， higher T-transformed total scores， and higher scores across all dimensions， including disorders of initiating sleep， disorders of maintaining sleep， sleep hyperhidrosis， sleep breathing disorders， parasomnias， nonrestorative sleep and excessive somnolence （P＜0.01）. Latent profile analysis identified four distinct sleep characteristic profiles， which were the mixed high-symptom group （32.39%， 2228/6878）， sleep initiation and maintenance difficulty symptom group （49.07%， 3375/6878）， low-symptom group （14.19%， 976/6878）， and the group with no significant symptoms （4.35%， 299/6878）. Multivariate logistic regression analysis demonstrated that the mixed high-symptom group， sleep initiation and maintenance difficulty symptom group， and low-symptom group were significantly associated with gastrointestinal heat accumulation syndrome. Among them， the mixed high-symptom group had the most significant association with gastrointestinal heat accumulation （OR=12.657， P＜0.001）， followed by the sleep initiation and maintenance difficulty symptom group （OR=4.964， P＜0.001）. ConclusionSleep characteristics in preschool children mainly present as composite patterns with different symptom combinations. Moreover， the sleep latent profiles of the mixed high-symptom group， the sleep initiation and maintenance difficulty symptom group， and the low-symptom group were significantly associated with gastrointestinal heat accumulation syndrome.

ObjectiveTo investigate the expression features of HBsAg and HBcAg in liver tissue and their correlation with HBV serum markers in children with chronic hepatitis B （CHB）. MethodsA total of 257 patients who were consecutively admitted to The Fifth Medical Center of Chinese PLA General Hospital from January 2013 to December 2023 and underwent liver biopsy to achieve a confirmed diagnosis of CHB were enrolled in this study. The NIS-Elements system was used to capture the immunohistochemical images of HBsAg and HBcAg in liver tissues， and Image J software was used for quantitative analysis. The one-sample chi-square test was used for within-group comparison of continuous data， and the Pearson/Spearman/Kendall’s Tau-b correlation analysis was used to investigate the correlation between viral antigen expression and serological markers. ResultsAmong the 257 CHB patients， there were 162 children （76 children aged<5 years and 86 children aged 5 — 18 years） and 95 adults. There were significant differences in the expression pattern， area， and intensity of HBsAg and the area and intensity of HBcAg in liver tissue between different age groups and between the children with different HBeAg statuses （all P<0.05）. In the children aged<5 years， HBsAg staining area was significantly negatively correlated with anti-HBs and HBeAg （both P<0.05）and was significantly positively correlated with ALT and AST （both P<0.05）， and HBsAg staining intensity was significantly positively correlated with qHBsAg （P<0.05） and was significantly negatively correlated with anti-HBs （P<0.05）. In the children group， HBsAg staining area was negatively correlated with anti-HBs and HBeAg （both P<0.05）， and HBsAg staining intensity was positively correlated with qHBsAg （P<0.05） and was negatively correlated with anti-HBs （P<0.05）. In the adult group， HBsAg staining area was positively correlated with ALT， AST， and liver inflammatory activity （all P<0.05）， and HBsAg staining intensity was positively correlated with qHBsAg， HBeAg， and HBV DNA （all P<0.05） and was negatively correlated with liver inflammatory activity and fibrosis degree （both P<0.05）. In the children aged<5 years， HBcAg staining area was positively correlated with qHBsAg and HBV DNA （both P<0.05）， and HBcAg staining intensity was significantly positively correlated with HBV DNA （P<0.001）. In the children aged 5 — 18 years， the area and intensity of HBcAg staining were positively correlated with qHBsAg， HBeAg， and HBV DNA （all P<0.05）. In the children group， HBcAg staining area was positively correlated with qHBsAg， HBeAg， and HBV DNA （all P<0.05）， and HBcAg staining intensity was positively correlated with qHBsAg and HBV DNA （both P<0.05）. In the adult group， the area and intensity of HBcAg staining were positively correlated with qHBsAg， HBeAg， and HBV DNA （all P<0.001）， and HBcAg staining area was positively correlated with the serum level of ALT （P=0.043）. ConclusionThe expression levels of HBsAg and HBcAg in liver tissue of children with CHB are significantly correlated with serological markers， and in clinical practice， HBsAg and HBcAg combined with serological markers can help to assess the condition of the liver， determine the immune stage， and provide evidence-based guidance for treatment timing.

ObjectiveTo investigate the prevalence of cardiovascular diseases and their influencing factors in community-based schizophrenia patients in Shanghai, and to provide a scientific basis for the early identification and prevention of cardiovascular disease in this population. MethodsBased on the Shanghai community cohort with severe mental disorders in 2022, a total of 3 954 community-based schizophrenia patients were identified and included in this study through a stratified cluster sampling method. Basic information and relevant clinical data (including metabolic index data) were collected through questionnaire survey, physical examination and laboratory testing. Univariate analyses were performed using the chi-square tests, and multivariate logistic regression analyses were employed to identify influencing factors of comorbid cardiovascular diseases. ResultsA total of 3 954 community-based schizophrenia patients were included, of which a total of 1 237 (31.28%) patients had comorbid cardiovascular diseases. Multivariate logistic regression analyses showed that age 60 years old or above (OR=5.524, 95%CI: 3.716‒8.214), smoking behavior (OR=1.328, 95%CI: 1.042‒1.692), overweight (OR=1.900, 95%CI: 1.046‒3.451) or obesity (OR=2.678, 95%CI: 1.439‒4.985), elevated blood pressure (OR=1.546, 95%CI: 1.294‒1.846), abnormal fasting blood glucose (OR=1.552, 95%CI: 1.322‒1.823) and high-density lipoprotein cholesterol abnormalities (OR=1.283, 95%CI: 1.025‒1.606) were positively associated with the risk of comorbid cardiovascular diseases in patients with schizophrenia, while educational attainment of college/bachelor’s degree or above (OR=0.640, 95%CI: 0.450‒0.910) and being unmarried (OR=0.552, 95%CI: 0.457‒0.667) were negatively associated with the risk of cardiovascular diseases comorbidity. ConclusionAdvanced age, unhealthy behaviors and lifestyles, as well as abnormalities in blood pressure, blood glucose, and blood lipids, could all increase the risk of comorbid cardiovascular diseases in community schizophrenia patients. It is suggested to strengthen the monitoring and management of these risk factors in this population in the future, so as to achieve early detection, early diagnosis and early intervention of cardiovascular diseases.

Objective:To establish ferroptosis-related risk characteristics, to evaluate the prognostic correlation of ferroptosis-related genes in hepatocellular carcinoma, and to explore the complex relationship between hepatocellular carcinoma, ferroptosis and immune microenvironment.Methods:The bioinformatics analysis involved obtaining ferroptosis-related differentially expressed genes (DEGs) from the GeneCards database and the cancer genome atlas database. The biological functions of ferroptosis-related DEGs were analyzed using gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment. Ferroptosis-related DEGs clusters were identified using univariate Cox regression analysis and cluster analysis, etc. The correlation between ferroptosis-related DEGs clusters and tumor immune microenvironment and tumor occurrence score was evaluated using immunopanoramic analysis and tumor-related score analysis. Based on ferroptosis-related characteristics, a ferroptosis-related characteristic spectrum and nomogram were constructed using multivariate Cox regression and correlation analysis, etc. The correlation between the risk characteristics and tumor immune microenvironment, tumor occurrence score and gene mutation were evaluated using immune panoramic analysis, tumor-related score analysis and gene mutation analysis. In the experimental verification stage, the mRNA expression levels of aurora kinase A ( Aurka), acetyl-CoA carboxylase alpha ( Acaca) and arrestin domain containing 3 ( Arrdc3) in mouse primary hepatocytes and mouse hepatoma Hepa1-6 cells were verified by real-time reverse transcription-PCR (RT-qPCR). The mRNA expression levels of AURKA, ACACA and ARRDC3 in adjacent normal tissues and tumor tissues of patients with hepatocellular carcinoma were verified by RT-qPCR. A heat map was used to show the correlation between clustering and clinical parameters, and this was analyzed using a chi-square test. Significance analysis was performed using a two-sided unpaired t test. Results:A total of 35 up-regulated genes and 19 down-regulated genes were identified. These genes were mainly involved in biological processes and signaling pathways related to ferroptosis, oxidative stress and fatty acid metabolism. A total of 14 ferroptosis-related DEGs were identified to be associated with prognosis. The clusterring effect was best when hepatocellular carcinoma patients were divided into two subgroups. The survival rate of cluster 2 was lower than that of cluster 1 ( P<0.05). There was no significant difference in the tumor immune dysfunction and exclusion (TIDE) score between cluster 2 and cluster 1 ( P=0.43). Cluster 1 exhibited higher levels of immune cell infiltration, particularly CD4 + T cells ( P<0.01). The expression levels of 10 major histocompatibility complex (MHC) molecule-related genes were higher in cluster 1. The angiogenesis activity score ( P=0.048) and stemness score ( P=0.038) of cluster 2 were increased, and the expression levels of programmed death-1 ( PDCD1) and cytotoxic T lymphocyte-associated antigen-4 ( CTLA-4) in cluster 2 (5.924±0.013 and 5.475±0.042) were higher than those in cluster 1 (4.539±0.143 and 4.372±0.176) (both P<0.05). The expression levels of AURKA, glucose-6-phosphate dehydrogenease ( G6PD), ACACA, GABA type A receptor associated protein like 1 ( GABARAPL1) and ARRDC3 were correlated with the T stage, clinical stage and survival status of hepatocellular carcinoma. The survival rate of the high-risk group was lower than that of the low-risk group with time ( P<0.01). The area under the curve of the risk characteristics at 1, 3 and 5 years was 0.797, 0.717 and 0.639, respectively. The actual survival time 1, 3, and 5 years was highly consistent with the corresponding predicted survival time. The levels of memory B cell infiltration, angiogenesis activity score and cell stemness score, programmed death-ligand 1, CTLA-4, hepatitis A virus cell receptor 2, lymphocyte activation gene 3 and PDCD1 gene expression (0.013 8±0.036 0, 0.884±0.212, 0.387±0.135, 6.273±0.228, 5.847±0.331, 8.179±0.259, 6.859±0.263 and 5.142±0.326) in the high-risk group were higher than those in the low-risk group (0.001 5±0.021 0, 0.874±0.132, 0.298±0.125, 5.866±0.132, 3.742±0.237, 7.236±0.321, 6.324±0.242 and 4.513±0.211) ( P<0.05, 0.01). The expression levels of MHC molecule-related genes in the high-risk group were also higher than those in the low-risk group ( P<0.05, 0.01), while the infiltration levels of resting mast cells, activated natural killer cells, and resting natural killer cells (0.043 2±0.135 0, 0.032 1±0.143 0 and 0.016 3±0.001 9) and the TIDE score (0.072 0±0.018 0) in the high-risk group were lower than those in the low-risk group (0.054 9±0.023 0, 0.042 7±0.017 0, 0.024 6±0.021 2 and 0.094 0±0.013 5) ( P<0.05, 0.01). The top five genes with the highest mutation frequency in the high-risk group were tumor protein P53 ( TP53, 43%), titin ( TTN, 21%), catenin beta 1 ( CTNNB1, 20%), mucin 16 ( MUC16, 18%) and piccolo presynaptic cytomatrix protein ( PCLO, 11%). The top five genes with the highest mutation frequency in the low-risk group were CTNNB1 (30%), TTN (24%), albumin ( ALB, 16%), MUC16 (15%) and PCLO (11%). The cube protein and PCLO showed the co-occurrence of gene mutations in the high-risk group, while MUC16 and axis 1 protein showed the co-occurrence of gene mutations in the low-risk group. There was no significant difference in tumor mutation burden (TMB) between the high-risk group (1.374±0.026) and the low-risk group (1.303±0.081) ( P=0.073). There was no significant difference in survival time between the high-TMB group (2.3 years) and the low-TMB group (3.8 years) ( P=0.293). The mutation rates of AURKA, G6PD, ACACA, GABARAPL1 and ARRDC3 genes (2.0%, 2.0%, 4.0%, 0.3% and 0.6%) were relatively low. The relative expression levels of Aurka, Acaca and Arrdc3 mRNA in Hepa1-6 cells (13.331±0.000, 6.619±0.000 and 1.209±0.002) were higher than those in mouse primary hepatocytes (1.000±0.000, 1.000±0.000 and 1.000±0.000) (all P<0.01). The relative expression levels of AURKA, ACACA and ARRDC3 mRNA in tumor tissues of patients with hepatocellular carcinoma (2.102±0.365, 2.476±0.351 and 11.460±9.189) were higher than those in adjacent normal tissues of patients with hepatocellular carcinoma (1.122±0.648, 0.831±0.935 and 0.852±0.171) ( P<0.05, 0.01). Conclusions:This study constructed a prognostic signature comprising five ferroptosis-related genes ( AURKA, G6PD, ACACA, GABARAPL1, and ARRDC3) that is highly correlated with clinical hepatocellular carcinoma data. This study highlights the significance of ferroptosis-related genes as prognostic markers for hepatocellular carcinoma and provides insights into the complex relationship between hepatocellular carcinoma, ferroptosis, and the immune microenvironment.

In line with the rising global incidence of cancer,tumor metastasis has become the leading cause of mortality among cancer patients.Formation of the pre-metastatic niche(PMN)creates an optimal microenvironment for tumor cell colonization and metastasis,thus facilitating tumor dissemination.In this context,cancer-associated fibroblasts(CAFs)have garnered significant attention as a result of their multifaceted roles in tumor progression.CAFs enhance the formation of the PMN and promote the invasive behavior of tumor cells by remodeling the extracellular matrix,inducing epithelial-mesenchymal transition,stimulating angiogenesis and modulating the tumor immune microenvironment.These processes not only expedite metastasis but also enable tumor immune evasion.This paper reviews the fundamental mechanisms and functions of CAFs in tumor metastasis,examines their potential applications in cancer research and therapy,and offers new perspectives and directions for the development of anti-tumor metastasis strategies.

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

Objective:To develop a training curriculum targeting the core competences of neurosurgery nurses, so as to provide a reference for standardized training of neurosurgery nurses and to strengthen their professionality.Methods:Centering on the core competences required for neurosurgery nurses, we formed the curriculum framework based on the cell structure-inspired concept proposed by the School of Nursing of The Hong Kong Polytechnic University, and determined the contents through a literature analysis and two rounds of questionnaire-based Delphi consultations with 16 experts. We increased, reduced, or modified the items and dimensions, and finally estabilished the curriculum for neurosurgery nurse training. SPSS 18.0 software was used to analyze the general information of experts, coordination coefficient, variation coefficient, full mark ratio, and mean importance value. Categorical data were described as frequencies and percentages, and continuous data were described as mean±standard deviation. Ranked data were analyzed by using the chi-square test.Results:In the two rounds of expert consultations, questionnaires were both 100.00% returned, and the coefficients of expert authority were 0.873 and 0.888, respectively. The coordination coefficient of curriculum modules and curriculum contents were 0.416 and 0.221, respectively ( P<0.001). For individual items across the curriculum modules, the mean importance value was 3.188-3.938, the variation coefficient was 0.063-0.178, and the full mark ratio was 0.250-0.875. For content items, the mean importance value was 3.250-4.000, the variation coefficient was 0-0.238, and the full mark ratio was 0.375-1.000. The established clinical practice-directed curriculum for neurosurgery nursing training included 6 course modules (anatomy and physiology of the nervous system, neurosurgery patient evaluation and monitoring, neurosurgery disease nursing, commonly used neurosurgery nursing techniques, nursing management, and scientific research basis) and 77 content items. Conclusions:The established training curriculum targeting the core competences for neurosurgery nurses is reliable, which can provide a reference for standardized training of neurosurgery nurses.

Objective To construct a classification model for surgical patients and apply it in the allocation of nursing human resources,providing a reference for nursing human resource management.Methods A convenience sampling method was used to retrospectively select 5,431 hospitalized surgical patients admitted to 6 surgical nursing units of a tertiary general hospital in Suzhou from July to November 2022 as the subjects of this study.The nursing hours were measured,and related influencing factors were analyzed.A decision tree classification method was used to establish a classification model for surgical patients.From August to October 2022,1,527 hospitalized surgical patients admitted to 3 nursing units of the same hospital were conveniently selected.The minimum number of nurses required daily was calculated using the surgical patient classification model,actual nursing hours measurement method,nurse-to-bed ratio method,and 8-hour continuous shift scheduling method.The application effect of the surgical patient classification model in nursing human resource allocation was evaluated with the actual nursing hours measurement method as the standard.Results The surgical patient classification model includes 7 classification indicators:length of hospital stay,diagnosis-related group weight,presence or absence of secondary care orders,surgical grade,anesthesia method,age,and presence or absence of critical illness orders.Patients were divided into 14 groups,and the model explained 90.5％of the total variance in nursing workload.The minimum number of nurses required in surgical nursing units calculated based on this model was closest to the result of the actual nursing hours measurement method and was superior to the results of the nurse-to-bed ratio method and the 8-hour continuous shift scheduling method.Conclusion The surgical patient classification model can accurately reflect the nursing workload of such patients.The classification indicators are simple and easy to obtain,and can guide the allocation of human resources in surgical nursing units.