Sustained inflammatory responses are closely related to various severe diseases, and inhibiting the excessive activation of inflammasomes and pyroptosis has significant implications for clinical treatment. Natural products have garnered considerable concern for the treatment of inflammation. Huanglian-Wumei decoction (HLWMD) is a classic prescription used for treating inflammatory diseases, but the necessity of their combination and the exact underlying anti-inflammatory mechanism have not yet been elucidated. Inspired by the supramolecular self-assembly strategy and natural drug compatibility theory, we successfully obtained berberine (BBR)-chlorogenic acid (CGA) supramolecular (BCS), which is an herbal pair from HLWMD. Using a series of characterization methods, we confirmed the self-assembly mechanism of BCS. BBR and CGA were self-assembled and stacked into amphiphilic spherical supramolecules in a 2:1 molar ratio, driven by electrostatic interactions, hydrophobic interactions, and π-π stacking; the hydrophilic fragments of CGA were outside, and the hydrophobic fragments of BBR were inside. This stacking pattern significantly improved the anti-inflammatory performance of BCS compared with that of single free molecules. Compared with free molecules, BCS significantly attenuated the release of multiple inflammatory mediators and lipopolysaccharide (LPS)-induced pyroptosis. Its anti-inflammatory mechanism is closely related to the inhibition of intracellular nuclear factor-kappaB (NF-κB) p65 phosphorylation and the noncanonical pyroptosis signalling pathway mediated by caspase-11.

Objective To investigate the epidemiological characteristics and risk factors of non-alcoholic fatty liver disease in Jincheng between 2015 and 2020. Methods Clinical data of 8,578 medical check-ups at Physical Examination Center of ou hospital from January 2015 to December 2020 were retrospectively selected. The prevalence of non-alcoholic fatty liver disease in the last 5 years was recorded, and Logistic regression was utilized to identify the risk factors for the development of non-alcoholic fatty liver disease. Results The overall prevalence of non-alcoholic fatty liver disease in Jincheng was 14.57% in 2015-2020. The prevalence of non-alcoholic fatty liver disease was higher in men than in women (16.99% vs 10.98%) and highest in the 40-59 age group (18.76%). No statistical difference was reported in blood urea nitrogen (BUN) and serum creatinine (Scr) between groups (P>0.05), while statistical difference was found in diabetes, hypertension, body mass index (BMI), waist circumference, weekly exercise frequency, daily vegetable intake, triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), alanine aminotransferase (ALT) and uric acid (UA) between two groups (P<0.05). Multivariate Logistic regression analysis denoted that BMI (OR=2.794, 95% CI: 1.745-4.550), waist circumference (OR=2.586, 95% CI: 1.585-4.299), diabetes (OR=0.644, 95% CI: 1.425-2.781), hypertension (OR=1.479, 95% CI: 1.121-2.290), weekly exercise ≥6h (OR=0.617, 95% CI: 0.519-0.709), daily vegetable intake ≥300g (OR=0.590, 95% CI: 0.467-0.652), TG (OR=1.481, 95% CI: 1.122-1.996), TC (OR=1.562, 95% CI:1.143-2.135), LDL-C (OR=1.440, 95% CI: 1.139-2.048), HDL-C (OR=0.656 , 95% CI: 0.587-0.783) , ALT (OR=1.591, 95% CI: 1.056-2.183), and UA (OR=1.412, 95% CI: 1.009-1.887) were risk factors for non-alcoholic fatty liver disease (P<0.05) . Conclusion The prevalence of non-alcoholic fatty liver disease in Jincheng City from 2015 to 2020 is 14.57%, the prevalence of males is higher than that of females, and the prevalence rate is the highest in the 40-59 age group. Moreover , diabetes mellitus , hypertension , BMI , waist circumference , weekly exercise , daily vegetable intake , serum TG, TC, LDL-C, HDL-C, ALT, and UA are all associated with the risk of the disease.

The Mofeng Ointment Formulation （MOF， 摩风膏方） is recorded in the Dunhuang manuscript Unnamed Treatise on the Pulse （《亡名氏脉经》） and stands as a representative ancient external therapeutic formula in traditional Chinese medicine （TCM）. Known for dispelling wind， activating blood circulation， warming the meridians， and relieving pain， it is particularly effective in treating rheumatic arthralgia. Through literature research， this paper systematically reviews the composition， preparation techniques， and clinical application characteristics of MOF. In recent years， advancements in modern pharmaceutical technology have led to the development of various innovative ointment-based formulations derived from the traditional recipe， such as Dunhuang Xiaoding Ointment （敦煌消定膏）， Dunhuang Xiaozhong and Zhentong Ointment （Patch） （敦煌消肿镇痛膏/贴）， Xiaoding Ointment （消定膏） gel patch， and Xiaoding Ointment （消定膏） cataplasm. These innovations explore pathways for transforming classical prescriptions into modern applications， providing a theoretical basis for the external TCM treatment of pain-related and orthopedic conditions.

The Fragment of Dunhuang Ancient Tibetan Moxibustion Therapy contains rich content on fire moxibustion therapy of Tubo-period Tibetan medicine, characterized by distinctive clinical features of Tibetan acupuncture and strong regional attributes. This paper systematically reviews the relevant materials on moxibustion in the Fragment and summarizes the findings as follows: Tibetan fire moxibustion mainly uses mugwort as the material, and terms like "fine mugwort", "broad bean" and "sheep dung pellet" refer to the size of the moxa cone. The number of moxa cones used is predominantly odd numbers, usually ranging from 5 to 21. The main indications for fire moxibustion cover internal medicine, external medicine, gynecology, pediatrics, and various pain syndromes. The therapy advocates for treating acute conditions and heat syndromes with moxibustion. The manuscript also records detailed contraindications, including time-based and seasonal taboos. Moxibustion is applied to both local and distal acupoints, reflecting the therapeutic concept of treating both proximal and distal regions. Furthermore, it documents simple and practical acupoint localization methods such as surface anatomical markers, proportional bone measurement, finger measurement, and hand-span measurement. Compared with contemporaneous Chinese medical moxibustion techniques, the moxibustion methods recorded in this Fragment are rich in content and present unique Tibetan theoretical characteristics. It provides valuable data and evidence for the excavation, application, and further research of Tibetan acupuncture and moxibustion.
Moxibustion/instrumentation* ; Humans ; History, Ancient ; Medicine, Tibetan Traditional/history* ; Tibet ; Acupuncture Points

BACKGROUND: Periodontitis is characterized by alveolar bone resorption, aggravated by osteoblast dysfunction, and associated with intracellular oxidative stress linked to the nuclear factor erythroid 2-related factor 2 (NRF2) level. We evaluated the molecular mechanism of periodontitis onset and development and the role of NRF2 in osteogenic differentiation. METHODS: Primary murine mandibular osteoblasts were extracted and exposed to Porphyromonas gingivalis lipopolysaccharide (Pg-LPS) or other stimuli. Reactive oxygen species (ROS) and 5,5',6,6'-tetrachloro-1,1',3,3'-tetraethylbenzimidazolylcarbocyanine iodide (JC-1) staining were used to detect intracellular oxidative stress. Alkaline phosphatase staining and alizarin red S staining were used to detect the osteogenic differentiation of osteoblasts. Immunofluorescence and western blotting were used to determine the changes in the mitogen-activated protein kinase (MAPK) pathway and related molecule activities. Immunofluorescence colocalization and co-immunoprecipitation were performed to examine the nuclear translocation of NRF2 and its interaction with dual-specific phosphatase 1 (DUSP1) in cells. RESULTS: Ligated tissue samples showed higher alveolar bone resorption rate and lower NRF2 level than healthy periodontal tissue samples. Pg-LPS increased intracellular oxidative stress levels and inhibited osteogenic differentiation, whereas changes in NRF2 expression were correlated with changes in the oxidative stress and osteogenesis rate. NRF2 promoted the dephosphorylation of the MAPK pathway by nuclear translocation and the upregulation of DUSP1 expression, thus enhancing the osteogenic differentiation capacity of mandibular osteoblasts. The interaction between NRF2 and DUSP1 was observed. CONCLUSIONS: NRF2 and its nuclear translocation can regulate the osteogenic differentiation of mandibular osteoblasts under Pg-LPS conditions by interacting with DUSP1 in a process linked to the MAPK pathway. These findings form the basis of periodontitis treatment.
Animals ; NF-E2-Related Factor 2/physiology* ; Lipopolysaccharides/pharmacology* ; Osteoblasts/drug effects* ; Mice ; Porphyromonas gingivalis/chemistry* ; Cell Differentiation ; Osteogenesis ; Dual Specificity Phosphatase 1/metabolism* ; Mandible/cytology* ; Reactive Oxygen Species/metabolism* ; Oxidative Stress ; Periodontitis/metabolism* ; Cells, Cultured ; Male ; Cell Nucleus/metabolism*

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objective To investigate the spatiotemporal expression pattern of metabotropic glutamate receptor 4(mGluR4)in the mouse cochlear basilar membrane and its dynamic changes during postnatal development until hair cell synaptic maturation.Methods Ten healthy 3-month-old C57BL/6L wild-type mice(5 males,5 females,25～35 g)were bred to obtain offspring.Cochlear samples from postnatal days 1～30(P1～P30)were analyzed.Frequency-specific auditory brainstem response(ABR)thresholds were measured at 45.2,32.0,22.6,16.0,11.3,8.0,5.6,and 4.0 kHz in P12,P14,P16,P21,and P30 mice.Immunofluorescence assay combined with confocal laser scanning microscopy was used to scan cochlear whole-mount preparations.Spatiotemporal co-localization profiling of mGluR4 and synaptic markers Ctbp2 and Snap25 was observed,and quantitative comparisons of fluorescent puncta density were performed.Results ABR testing revealed undifferentiated waveforms in all P12 mice,while 70%of P14 mice exhibited well-defined Wave I.In P14,P16,P21 and P30,mice undergoing ABR testing,50%failed to exhibit ABR waveforms when stimulated by 45.2 kHz tones,and 87.5%showed no response to 32.0 kHz stimuli.Auditory response thresholds for other frequencies progressively decreased with increasing postnatal age.Immunolocalization demonstrated stronger mGluR4 expression in inner hair cells(IHCs)versus outer hair cells(OHCs).Distinct mGluR4 puncta were observed at IHC presynaptic active zones(co-localized with Snap25)as early as P11,but showed minimal overlap with CtBP2-labeled ribbons.Quantitative analysis revealed significantly higher mGluR4 puncta density at P30 compared to P14 synapses(P<0.05).Conclusion Postnatal upregulation of mGluR4 at IHC synaptic regions correlates with functional maturation.These findings suggest mGluR4 may modulate vesicular exocytosis regulation and exert pharmacological inhibition on glutamate release,potentially influencing synaptic plasticity during auditory pathway refinement.

Objective:To analyze the molecular mechanism of Huangqin Decoction in the treatment of acute lung injury (ALI) with network pharmacology; To conduct experimental validation.Methods:Active compounds and corresponding targets of Huangqin Decoction were retrieved from the TCMIP database. ALI-related targets were obtained from GeneCards, DisGeNet, TTD, and OMIM, and the intersection targets were obtained. The intersection targets were imported into the string database to build the PPI network, and the core targets were obtained through topology analysis by Cytoscape 3.10.1 software. GO and KEGG pathway enrichment analyses were conducted using clusterProfiler software. 16 SD rats were divided into two groups ( n = 8 per group) with random number table method: control and Huangqin Decoction. Rats in the Huangqin Decoction group received Huangqin Decoction by gavage at a dosage of 40 mg/kg, while the control group was administered an equal volume of distilled water. After seven consecutive treatments, drug-containing serum was collected. A549 cells were divided into four groups: control, model, Huangqin Decoction, and received relevant drugs as intervention for 24 h. Levels of SOD, MDA, GSH-Px, IL-1β, TNF-α, and IL-6 in the culture supernatant were measured by ELISA. Apoptosis was analyzed by flow cytometry. The expressions of PI3K, p-PI3K, Akt, p-Akt, mTOR, p-mTOR, LC3Ⅱ/Ⅰ, and Beclin-1 proteins were determined by Western blot. Results:A total of 137 active compounds and 178 common targets were identified in Huangqin Decoction, with TP53, AKT1, STAT3, TNF, IL6, and ESR1 as core nodes. GO enrichment indicated involvement in oxidative stress and responses to lipopolysaccharides, bacterial molecules, and hypoxia. KEGG analysis revealed enrichment in lipid and atherosclerosis, PI3K-Akt signaling pathway, hepatitis, MAPK signaling pathway, prostate cancer, small-cell lung cancer, and mTOR signaling pathway. In cell experiments, compared with the model group, Huangqin Decoction and inhibitor groups showed increased A549xibo ( P<0.05); levels of IL-1β, TNF-α, IL-6, and MDA in the supernatant were reduced ( P<0.05 or P<0.01), while SOD and GSH-Px levels were elevated ( P<0.05 or P<0.01); the apoptosis rate decreased ( P<0.05 or P<0.01); the expressions of LC3-Ⅱ/Ⅰ and Beclin-1 proteins decreased ( P<0.05 or P<0.01), whereas the expressions of p-mTOR/mTOR, p-Akt/Akt, and p-PI3K/PI3K increased ( P<0.05 or P<0.01). Conclusion:Huangqin Decoction exerts protective effects against ALI mainly by reducing cellular autophagy, and its mechanism may be related to the activation of the mTOR/Akt/PI3K signaling pathway.

Objective To investigate biological markers associated with psychotic symptoms in patients with bipolar disorder(BD)based on electronic medical records of patients,and to develop an interpretable risk prediction model that supports the identification of high-risk individuals and that facilitates decision-making for providing clinical intervention in a timely manner.Methods A total of 2 352 patients diagnosed with BD and admitted to West China Hospital,Sichuan University were enrolled using the electronic medical records system of the hospital.The participants were divided into two subgroups,the bipolar disorder depression(BDD)group and the bipolar disorder mania(BDM)group.The logistic regression algorithm was used to train and validate the prediction model,and interpretability methods were used to analyze the contribution of each feature to individuals and the effect of the features on specific target prediction decisions.Results The logistic regression model demonstrated robust predictive performance across the BD,BDD,and BDM cohorts,with areas under the curve(AUC)of the receiver operating characteristic curves always exceeding 81.6%.The core predictive features included platelet distribution width(PDW),fibrinogen(FIB),platelet large cell ratio(P-LCR),activated partial thromboplastin time(APTT),prothrombin time(PT),and triglyceride(TG).The logistic regression model exhibited strong interpretability and was combined with nomograms for intuitive risk quantification and individualized prediction.Conclusion The logistic regression model enables rapid and simple screening of BD patients with psychotic symptoms.Distinct patterns of changes observed in blood biomarkers of BDD and BDM subgroups enrich the understanding of the underlying pathophysiological mechanisms and highlight the importance of considering subtypes in the intervention and management of patients.

Objective: To explore the association of tobacco/alcohol-excessive Internet usage and insufficient sleep with depressive symptoms among middle school students, so as to provide a reference for improving mental health of middle school students. Methods: In accordance with the cluster random sampling method, a total of 18 484 middle school students in Shanghai were surveyed from September to November 2022. Tobacco/alcohol-excessive Internet usage and sleep duration with depressive symptoms were assessed using the relevant scale items included in the questionnaire of Surveillance for Common Disease and Health Risk Factors among Students. The χ 2 test was used for inter group comparison, Logistic regression analysis and likelihood ratio test were used to analyze the independent and aggregated associations of tobacco/alcohol-excessive Internet use and insufficient sleep wiht depressive symptoms. Results: Self reported rates of tobacco/alcohol-excessive Internet usage, insufficient sleep and depressive symptoms among adolescents were 14.7%, 73.5% and 16.3%, respectively. Tobacco/alcohol-excessive Internet usage ( OR=2.69, 95%CI =2.44-2.97) and insufficient sleep ( OR=1.76, 95%CI =1.58-1.95) were associated with depressive symptoms ( P <0.05). Compared to middle school students with no tobacco/alcohol-excessive Internet usage and sufficient sleep, those with both tobacco/alcohol-excessive Internet usage and insufficient sleep showed the higher rate of depressive symptoms ( OR=4.71, 95%CI =4.08-5.44, P <0.05). Further stratified analysis results showed that, compared to the boys and the high school students, the separate and joint association of tobacco/alcohol-excessive Internet usage and insufficient sleep with depressive symptoms were more pronounced in the girls and the middle school students [ OR (95% CI ) for tobacco/alcohol-excessive Internet usage were 3.09 (2.68-3.56) and 4.74 (3.86-5.83), respectively; OR (95% CI ) for insufficient sleep were 1.86 (1.60-2.17) and 2.00 (1.58-2.53), respectively; and the OR (95% CI ) for the joint association were 6.05 (5.01-7.31) and 9.15 (6.98-11.99), respectively, P <0.05]. Conclusions Tobacco/alcohol-excessive Internet usage and insufficient sleep are associated with depressive symptoms in middle school students. Prevention and control strategies for adolescent mental health should be developed with consideration of health related behaviors, and also need to be tailored by focusing on gender and grade differences.