Both hyperlipidemic acute pancreatitis and fatty liver disease are associated with lipid metabolism disorders and are commonly comorbid with each other in clinical practice. The pathogenesis of such comorbidity involves the interaction between multiple factors such as hypertriglyceridemia， metabolic syndrome， obesity， and insulin resistance， and these factors may form a vicious cycle and jointly promote disease progression. In clinical practice， hyperlipidemic acute pancreatitis is characterized by severe disease conditions， a high incidence rate of complications， a high mortality rate， and a tendency for recurrence， and it can easily lead to multi-organ damage and even multiple organ failure without timely treatment， posing a serious threat to the life of patients. Starting from the various signaling pathways associated with hyperlipidemic acute pancreatitis comorbid with fatty liver disease， this article discusses the potential molecular mechanisms of synergistic pathogenesis between hyperlipidemic acute pancreatitis and fatty liver disease， so as to provide a reference for the early prevention and treatment of such comorbidity.

ObjectiveTo investigate the metabolic alterations of serum short chain fatty acids （SCFAs） in pediatric patients with atopic dermatitis （AD） and their correlation with different clinical phenotypes using targeted metabolomics. MethodsThis study enrolled 87 AD patients and 67 healthy controls （HC）. Serum levels of eight SCFAs were quantified by ultra-high-performance liquid chromatography-mass spectrometry. The associations between SCFAs and AD were assessed using various statistical methods. ResultsCompared with the HC group， levels of acetic acid （AA）， propionic acid （PA）， and caproic acid （CA） （P=0.002，P=0.002，P=0.043） decreased in the AD group. Logistic regression analysis identified AA （OR=0.449， 95% CI： 0.289–0.698） and PA （OR = 0.487， 95% CI： 0.324–0.732） as protective factors against AD. The combination of AA and PA yielded an area under the curve （AUC） greater than 0.7， indicating good diagnostic efficacy. Age-stratified analysis revealed that AA reduction was predominant in childhood， whereas PA reduction was predominant in adolescence. Pathway enrichment analysis showed significant enrichment of fatty acid biosynthesis （FDR=0.341， P=0.003） and vitamin K metabolism （FDR=1， P=0.039） pathways. Furthermore， subgroup analyses based on disease severity， personal/family history of atopy， and sex revealed no significant differences in SCFAs levels among the groups. ConclusionDifferential serum SCFAs and their enriched metabolic pathways may be implicated in the pathogenesis of AD.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Objective To assess the situation and influencing factors of occupational burnout among the staff at the Center for Disease Control and Prevention (CDC) in Sichuan Province. Methods A total of 1 038 CDC staff members in Sichuan Province were selected as the study subjects using the stratified random sampling method. Occupational burnout of the staff was assessed using the Maslach Burnout Inventory General Survey via an online questionnaire. Results The detection rate of occupational burnout was 42.3% (439/1 038). Binary logistic regression analysis result showed that, after controlling for confounding factors such as education level and alcohol consumption, CDC staffs aged at 20-<31, 31-<41, and 41-<51 years were at higher risk of occupational burnout compared with those ≥51 years (all P<0.05). CDC staffs with 5-<10 or ≥10 years of service had higher occupational burnout risk compared with those with <5 years (both P<0.05). CDC staffs with poor or fair health status, irregular diet, and poor sleep quality had higher risk of occupational burnout compared with those healthy, have regular diet, and good sleep quality (all P<0.05). The risk of occupational burnout increased with higher overtime frequency (all P<0.05). Conclusion Occupational burnout among CDC staffs in Sichuan Province is relatively high. Age, years of service, health status, diet, sleep quality, and overtime frequency are key influencing factors.

BACKGROUND: Chronic liver disease (CLD), mainly non-alcoholic fatty liver disease (NAFLD), is a significant public health concern worldwide. This study aims to quantify the burden of NAFLD in CLD globally and within China, using data from the Global Burden of Disease (GBD) Study 2021, providing crucial insights for global and local health policies. METHODS: The study used comprehensive data from the GBD study 2021. It included estimates of prevalence, incidence, mortality, and disability-adjusted life years (DALYs). Age-standardized rates and average annual percent change (AAPC) from 2011 to 2021 were reported. A meticulous decomposition analysis was conducted. RESULTS: In 2021, there were 1582.5 million prevalent cases, 47.6 million incident cases, 1.4 million deaths, and 44.4 million DALYs attributable to CLD, globally. Among these, NAFLD has emerged as the predominant cause, accounting for 78.0% of all prevalent CLD cases (1234.7 million) and 87.2% of incident cases (41.5 million). Correspondingly, NAFLD had the highest age-standardized prevalence (15,017.5 per 100,000 population) and incidence (876.5 per 100,000 population) rates among CLDs. In addition, China's CLD age-standardized prevalence rate was 21,659.5 per 100,000 population, and the age-standardized incidence rate was 752.6 per 100,000 population, higher than the global average. From 2011 to 2021, the global prevalence rate of CLD increased slowly (AAPC = 0.17), consistent with the trend in China (AAPC = 0.23). Furthermore, the prevalence rate of NAFLD rose significantly in China (AAPC = 1.30) compared with the global average (AAPC = 0.91). Decomposition analysis also showed the worldwide increase in deaths and DALYs for NAFLD, which were primarily attributable to population growth and aging. CONCLUSIONS The burden of CLD and NAFLD remains substantial globally and within China in terms of high prevalence and incidence. As such, this underscores the need for targeted prevention and treatment strategies. These findings emphasize the importance of continued surveillance and research to mitigate the growing impact of liver diseases on global and Chinese health systems.
Humans ; Non-alcoholic Fatty Liver Disease/mortality* ; Global Burden of Disease ; China/epidemiology* ; Prevalence ; Male ; Disability-Adjusted Life Years ; Female ; Incidence ; Middle Aged ; Chronic Disease ; Adult ; Quality-Adjusted Life Years ; Liver Diseases/epidemiology* ; Aged

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Bawei Chenxiang Powder(BCP), first documented in the Tibetan medical work Four Medical Classics, has been widely applied in clinical practices in Tibetan and Mongolian medicines since its development. It has the effect of clearing the heart heat, calming the mind, and inducing resuscitation. On the basis of BCP, multiple types of formulae have been developed, such as Bawei Yiheyi Chenxiang Powder, Bawei Rang Chenxiang Powder, and Bawei Pingchuan Chenxiang Powder, which are widely used for treating cardiovascular and respiratory diseases. Current pharmacological research has revealed the pharmacological effects of BCP and its related formulae against myocardial ischemia, cerebral ischemia, renal ischemia, and anti-hypoxia. BCP and its related formulae introduced more treatment options for related clinical diseases and provided insights for fully comprehending the essence and pharmacological components of the formulae. This paper systematically reviewed the clinical and pharmacological research on BCP and its related formulae, analyzing the formulation principles and potential key flavors and active ingredients. This lays a fundamental scientific basis for the clinical use, quality evaluation, and subsequent development and application of BCP and its related formulae, providing references for studying traditional Chinese medicine formulae in a thorough and systematic manner.
Drugs, Chinese Herbal/chemistry* ; Humans ; Powders/chemistry* ; Animals ; Medicine, Chinese Traditional

The medicinal materials of Bawei Chenxiang Pills(BCPs) were extracted via three methods: reflux extraction by water, reflux extraction by 70% ethanol, and extraction by pure water following reflux extraction by 70% ethanol, yielding three extracts of ST, CT, and CST. The efficacy of ST(760 mg·kg~(-1)), CT(620 mg·kg~(-1)), and CST(1 040 mg·kg~(-1)) were evaluated by acute myocardial ischemia(AMI) and p-chlorophenylalanine(PCPA)-induced insomnia in mice, respectively. Western blot was further utilized to investigate their hypnosis mechanisms. The main chemical components of different extracts were identified by the UPLC-Q-Exactive-MS technique. The results showed that CT and CST significantly increased the ejection fraction(EF) and fractional shortening(FS) of myocardial infarction mice, reduced left ventricular internal dimension at end-diastole(LVIDd) and left ventricular internal dimension at end-systole(LVIDs). In contrast, ST did not exhibit significant effects on these parameters. In the insomnia model, CT significantly reduced sleep latency and prolonged sleep duration, whereas ST only prolonged sleep duration without shortening sleep latency. CST showed no significant effects on either sleep latency or sleep duration. Additionally, both CT and ST upregulated glutamic acid decarboxylase 67(GAD67) protein expression in brain tissue. A total of 15 main chemical components were identified from CT, including 2-(2-phenylethyl) chromone and 6-methoxy-2-(2-phenylethyl) chromone. Six chemical components including chebulidic acid were identified from ST. The results suggested that chromones and terpenes were potential anti-myocardial ischemia drugs of BCPs, and tannin and phenolic acids were potential hypnosis drugs. This study enriches the pharmacological and chemical research of BCPs, providing a basis and reference for their secondary development, quality standard improvement, and clinical application.
Animals ; Drugs, Chinese Herbal/isolation & purification* ; Mice ; Male ; Sleep Initiation and Maintenance Disorders/physiopathology* ; Humans ; Myocardial Infarction/drug therapy* ; Myocardial Ischemia/drug therapy*