Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Objective: To develop QingNangTCM, a specialized large language model (LLM) tailored for expert-level traditional Chinese medicine (TCM) question-answering and clinical reasoning, addressing the scarcity of domain-specific corpora and specialized alignment. Methods: We constructed QnTCM_Dataset, a corpus of 100 000 entries, by integrating data from ShenNong_TCM_Dataset and SymMap v2.0, and synthesizing additional samples via retrieval-augmented generation (RAG) and persona-driven generation. The dataset comprehensively covers diagnostic inquiries, prescriptions, and herbal knowledge. Utilizing P-Tuning v2, we fine-tuned the GLM-4-9B-Chat backbone to develop QingNangTCM. A multi-dimensional evaluation framework, assessing accuracy, coverage, consistency, safety, professionalism, and fluency, was established using metrics such as bilingual evaluation understudy (BLEU), recall-oriented understudy for gisting evaluation (ROUGE), metric for evaluation of translation with explicit ordering (METEOR), and LLM-as-a-Judge with expert review. Qualitative analysis was conducted across four simulated clinical scenarios: symptom analysis, disease treatment, herb inquiry, and failure cases. Baseline models included GLM-4-9B-Chat, DeepSeek-V2, HuatuoGPT-II (7B), and GLM-4-9B-Chat (freeze-tuning). Results: QingNangTCM achieved the highest scores in BLEU-1/2/3/4 (0.425/0.298/0.137/0.064), ROUGE-1/2 (0.368/0.157), and METEOR (0.218), demonstrating a balanced and superior normalized performance profile of 0.900 across the dimensions of accuracy, coverage, and consistency. Although its ROUGE-L score (0.299) was lower than that of HuatuoGPT-II (7B) (0.351), it significantly outperformed domain-specific models in expert-validated win rates for professionalism (86%) and safety (73%). Qualitative analysis confirmed that the model strictly adheres to the “symptom-syndrome-pathogenesis-treatment” reasoning chain, though occasional misclassifications and hallucinations persisted when dealing with rare medicinal materials and uncommon syndromes. Conclusion Combining domain-specific corpus construction with parameter-efficient prompt tuning enhances the reasoning behavior and domain adaptation of LLMs for TCM-related tasks. This work provides a technical framework for the digital organization and intelligent utilization of TCM knowledge, with potential value for supporting diagnostic reasoning and medical education.

ObjectiveThis study systematically analyzed the arginine metabolic dysregulation in the rat model of heart failure （HF）， providing a modern scientific basis for elucidating the pathogenesis of HF and offering new insights for the prevention and treatment of HF with traditional Chinese medicine （TCM）. MethodsA thoracotomy was performed to ligate the left anterior descending coronary artery of rats， which induced acute myocardial ischemia and thus led to the development of post-myocardial infarction heart failure. The rats were divided into a sham surgery group and a model group， with eight rats in each group. Serum targeted metabolomics analysis was performed using ultra-performance liquid chromatography-triple quadrupole mass spectrometry （UPLC-TQ-S）， and the spatial distribution of metabolites in cardiac tissue was observed using airflow-assisted desorption electrospray ionizationmass spectrometry imaging （AFADESI-MSI）. Targets associated with HF and arginine metabolism were screened from databases including GeneCards and the Gene Expression Omnibus （GEO）， a protein-protein interaction （PPI） network was constructed， and enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway and Gene Ontology （GO） was performed. Finally， molecular docking was conducted to verify the binding between core metabolic components and key targets， and potential TCMs were predicted based on the core pathways and targets. ResultsCompared with the sham surgery group， the levels of arginine and citrulline in the serum of model rats were significantly decreased （P<0.01）， while those of proline， ornithine， creatine， creatinine and glutamate were significantly increased （P<0.05， P<0.01）. Cardiac mass spectrometry imaging showed a decreased abundance of arginine in the local myocardial tissue. Bioinformatics analysis identified 24 core functional targets， such as the angiotensin-converting enzyme （ACE）， neuronal nitric oxide synthase （NOS1）， 5-hydroxytryptamine receptor 2A （HTR2A）， and epidermal growth factor receptor （EGFR）， and enrichment analysis indicated that these targets were significantly involved in the calcium signaling pathway， neuroactive ligand-receptor interactions， and phosphatidylinositol signaling pathway. Molecular docking confirmed strong binding activities between arginine， citrulline and HTR2A， as well as between creatine， creatinine and EGFR. Based on pathway-target prediction， potential TCM interventions， such as ginseng and magnolia， were identified. ConclusionThis study revealed characteristic arginine metabolic disorder in HF， and the core targets of HF were closely associated with the phosphatidylinositol signaling pathway. It provides a modern biological interpretation of the pathogenesis of HF in TCM from the perspectives of metabolites and signaling pathways， and offers valuable insights for targeted therapy of HF and the development of TCM.

ObjectiveThis study systematically analyzed the arginine metabolic dysregulation in the rat model of heart failure （HF）， providing a modern scientific basis for elucidating the pathogenesis of HF and offering new insights for the prevention and treatment of HF with traditional Chinese medicine （TCM）. MethodsA thoracotomy was performed to ligate the left anterior descending coronary artery of rats， which induced acute myocardial ischemia and thus led to the development of post-myocardial infarction heart failure. The rats were divided into a sham surgery group and a model group， with eight rats in each group. Serum targeted metabolomics analysis was performed using ultra-performance liquid chromatography-triple quadrupole mass spectrometry （UPLC-TQ-S）， and the spatial distribution of metabolites in cardiac tissue was observed using airflow-assisted desorption electrospray ionizationmass spectrometry imaging （AFADESI-MSI）. Targets associated with HF and arginine metabolism were screened from databases including GeneCards and the Gene Expression Omnibus （GEO）， a protein-protein interaction （PPI） network was constructed， and enrichment analysis of the Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway and Gene Ontology （GO） was performed. Finally， molecular docking was conducted to verify the binding between core metabolic components and key targets， and potential TCMs were predicted based on the core pathways and targets. ResultsCompared with the sham surgery group， the levels of arginine and citrulline in the serum of model rats were significantly decreased （P<0.01）， while those of proline， ornithine， creatine， creatinine and glutamate were significantly increased （P<0.05， P<0.01）. Cardiac mass spectrometry imaging showed a decreased abundance of arginine in the local myocardial tissue. Bioinformatics analysis identified 24 core functional targets， such as the angiotensin-converting enzyme （ACE）， neuronal nitric oxide synthase （NOS1）， 5-hydroxytryptamine receptor 2A （HTR2A）， and epidermal growth factor receptor （EGFR）， and enrichment analysis indicated that these targets were significantly involved in the calcium signaling pathway， neuroactive ligand-receptor interactions， and phosphatidylinositol signaling pathway. Molecular docking confirmed strong binding activities between arginine， citrulline and HTR2A， as well as between creatine， creatinine and EGFR. Based on pathway-target prediction， potential TCM interventions， such as ginseng and magnolia， were identified. ConclusionThis study revealed characteristic arginine metabolic disorder in HF， and the core targets of HF were closely associated with the phosphatidylinositol signaling pathway. It provides a modern biological interpretation of the pathogenesis of HF in TCM from the perspectives of metabolites and signaling pathways， and offers valuable insights for targeted therapy of HF and the development of TCM.

Objective To investigate serum HCV-RNA detection rate in patients with positive hepatitis C virus (HCV) immunoglobulin G (IgG) antibody, and to analyze the related factors of HCV-RNA detection in patients with positive HCV IgG antibody by logistic regression analysis. Methods A retrospective study was conducted on 500 patients with positive HCV IgG antibody. The positive rate of HCV-RNA was counted. Logistic regression analysis was adopted to analyze the related factors of HCV-RNA detection in HCV IgG antibody positive population. Results A total of 317 patients with positive HCV-RNA detection were included in serum HCV-RNA positive group (n=317), and 183 patients with negative HCV-RNA detection were enrolled as serum HCV-RNA negative group (n=183). The diagnosis rate of HCV infection was 63.40% (317/500). Logistic regression analysis showed that abnormal levels of serum ALT, AST, GGT, TBIL, HCV IgG antibody, prothrombin time, and the presence of clinical symptoms were independently correlated with the detection of HCV-RNA in HCV IgG antibody positive individuals (P<0.05). Established 7-factor prediction models and created a nomogram. The chi-square value was 0.586, and P = 0.89 > 0.05. The ROC curve was plotted using pROC, and the area under the ROC curve was 0.912. Conclusion Among the population positive for HCV IgG antibody, the detection rate of serum HCV-RNA is high. Abnormal levels of ALT, AST, GGT, TBIL, IgG antibody, prothrombin time and clinical symptoms are the related factors for the detection of HCV-RNA. These indicators provide a reference for the clinical judgment of the real infection risk of HCV IgG positive individuals.

Objective: To analyze the epidemiological characteristics and changing trends of non suicidal self injury (NSSI) behaviors among middle school students in Jiading District of Shanghai, from 2015 to 2023, so as to provide a basis for the development of NSSI prevention and control measures among students. Methods: Using a stratified cluster random sampling method, a total of five times for Shanghai Adolescent Health Risk Behavior Surveys were conducted for every two years in Jiading District of Shanghai from 2015 to 2023. A total of 5 231 middle school students from junior high schools and senior high schools were selected for questionnaire surveys. Intergroup comparisons were performed using the x 2 test or the χ 2 trend test, and the JointPoint 5.0 software was used to analyze the changing trends, with the annual percent change (APC) used for evaluation. A binary Logistic regression model was employed to analyze the related factors of NSSI behavior among middle school students. Results: In 2023, the reported NSSI rate among middle school students in Jiading District was 14.2%. The rate was significantly higher among junior high school students (17.1%) than that among senior high school students (11.1%), and higher among females (19.2%) than that among males (10.0%) ( χ 2=10.04, 23.21, both P <0.01). From 2015 to 2023, the overall reported NSSI rate showed an increasing trend, rising from 8.6% in 2015 to 14.2% in 2023 ( χ 2 trend =22.25), with an APC of 6.64% ( t =3.49), and the APC for girls was 9.79 % ( t =3.20) (all P <0.05). Among students reporting NSSI, the proportion experiencing ≥6 episodes increased from 10.8% in 2015 to 19.2% in 2023 ( χ 2 trend =6.57, P <0.05). Multivariate Logistic regression analysis indicated that girls, junior high school students, those with insomnia, depressive emotion and drinkers had higher risks of NSSI, compared to boys, senior high school students, those without insomnia, non depressive emotion students and non drinkers ( OR =1.71, 1.96, 3.44, 4.76, 1.77, all P < 0.05 ). Conclusions The reported rate of NSSI among middle school students in Jiading District of Shanghai, increased annually from 2015 to 2023, and the proportion of repeated NSSI also showed an upward trend. Early intervention measures targeting middle school students, especially junior high school students and females, should be implemented to prevent and control its occurrence and development.

Objective: To understand current state of physical health levels of first year students in different body mass index (BMI) categories in Ningxia universities, and to explore the correlation between BMI and physical fitness index (PFI), so as to provide a reference for enhancing physical health levels of university students. Methods: In November 2024, physical fitness test data from 16 631 first year students across four universities in Yinchuan City, Ningxia from 2019 to 2023 were collected by adopting convenience and stratified cluster random sampling methods. The PFI was calculated using the Z score of the physical fitness test results, and a nonlinear quadratic model was established via least squares regression to examine the relationship between BMI and PFI among university students. Results: The BMI for males was (21.69±3.53)kg/m 2, while for females was (20.78±2.94)kg/m 2. The composite score for males physical fitness (69.86±9.25) was lower than that for females (72.24± 8.15 ), with a statistically significant difference ( t =-17.54, P <0.01). Moreover, the failure rates of various physical fitness indicators (vital capacity, sit and reach, standing long jump, pull ups/1 minute sit ups, 1 000 m/800 m run) were higher among males than females ( χ 2=103.48, 72.45, 14.38, 5 134.85, 188.89, all P <0.01). Comparisons across BMI categories revealed that among males, the normal weight group outperformed other groups in the 50 m sprint, standing long jump, 1 000 m sprint, composite score, and PFI ( F =89.17, 113.90, 179.02, 573.35, 593.08); among female students, the normal weight group outperformed other groups in the 50 m sprint, sit and reach, 800 m run, composite score, and PFI ( F =10.67, 19.58 , 96.45, 294.05, 183.45) (all P <0.01). The relationship between BMI and PFI among first year students exhibited a parabolic change trend, students with a moderate BMI demonstrated higher PFI, and as BMI increased, PFI decreased (all P <0.01). Conclusions The physical health level of male students in Ningxia universities is lower than that of female students. There is a correlation between BMI classification and PFI. Tailored intervention measures should be implemented according to the physical characteristics of students across different genders and BMI classifications to enhance university students physical health.

OBJECTIVE: To explore the effects of different endotracheal tube cuff pressure management modes on cuff sealing and the pressure exerted on the tracheal wall. METHODS: A prospective self-controlled study was conducted. Eleven patients undergoing endotracheal intubation and mechanical ventilation with an automatic airway management system (AGs) admitted to the Second Medical Centre of the Chinese People's Liberation Army General Hospital from October 1, 2020, to April 1, 2022, were enrolled as the study subjects. Within 24 hours after the establishment of artificial airway and mechanical ventilation, four cuff pressure management modes were randomly applied to each patient for 24 hours in sequence: automatic cuff pressure management mode [modeI: the safe range of cuff pressure was set at 20-35 cmH₂O (1 cmH₂O≈0.098 kPa), and the CO₂ pressure above the endotracheal tube cuff was automatically detected by AGs every 5 minutes to determine the cuff sealing status, and the cuff pressure was automatically adjusted], constant cuff pressure (25 cmH₂O) management mode (mode II: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 25 cmH₂O via a pressure pump), constant cuff pressure (30 cmH₂O) management mode (mode III: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 30 cmH₂O via a pressure pump), and manual cuff pressure management mode (mode IV: the cuff pressure was manually measured by nurses every 6-8 hours using a cuff pressure gauge to keep the cuff pressure at 25-30 cmH₂O after inflation). The CO₂ pressure above the endotracheal tube cuff (at 60-minute intervals) and the cuff pressure changes (at 50-ms intervals) were recorded to compare the differences in number of cuff leaks [no leak was defined as CO₂ pressure = 0, small leak as 0 < CO₂ pressure < 2 mmHg (1 mmHg≈0.133 kPa), and large leak as CO₂ pressure ≥ 2 mmHg] and cuff pressure among modesI-IV. RESULTS: A total of 24 CO₂ pressure measurements were taken per patient across the four modes, resulting in a total of 264 detections for each mode. Regarding the cuff leak, the total number of leak and large leak in modeIwas significantly lower than that in modes II-IV [total leak: 30 cases (11.36%) vs. 81 cases (30.68%), 70 cases (26.52%), 103 cases (39.02%); large leak: 15 cases (5.68%) vs. 50 cases (18.94%), 48 cases (18.18%), 66 cases (25.00%), all P < 0.05]. There was no significant difference in the number of cuff leak between modes II and III, and mode IV had the most severe cuff leak. In terms of cuff pressure, since mode IV required blocking the cuff tube from the AGs tube and the AGs cuff pressure management module did not actually work, real-time monitoring of cuff pressure was not possible. Therefore, cuff pressure changes were only analyzed in modes I-III. Each of the 11 patients underwent 24-hour cuff pressure monitoring under modes I-III, with 19 008 000 monitoring times for each mode. The cuff pressure in mode I was between that in modes II and III [cmH₂O: 27.09 (26.10, 28.14) vs. 26.60 (25.92, 27.47), 31.01 (30.33, 31.88), both P < 0.01]. Moreover, the number of extreme values of cuff pressure > 50 cmH₂O in mode I was significantly lower than that in modes II and III [19 900 cases (0.105%) vs. 22 297 cases (0.117%), 27 618 cases (0.145%), both P < 0.05]. CONCLUSION Dynamically monitoring the CO₂ pressure above the cuff to guide the adjustment of endotracheal tube cuff pressure can achieve better cuff sealing with a relatively lower cuff pressure load.
Humans ; Intubation, Intratracheal/instrumentation* ; Pressure ; Prospective Studies ; Respiration, Artificial ; Male ; Airway Management/methods* ; Female ; Middle Aged