Objective To investigate occupational exposure levels of lead, arsenic and cadmium in the lead smelting plant of Hunan Shui Kou Shan Nonferrous Metals Group Co. Ltd., analyze their effects on health of employees, and compare the applicability of different occupational health risk assessment methods, and to provide a basis for prevention and control of occupational exposure risks in enterprises. Methods According to systematic sampling method, 380 employees with lead, arsenic and cadmium exposure (exposure group) and 100 non-exposure employees (non-exposure group) were selected from 2022 to 2024 for on-site investigation of occupational health [concentration time-weighted average (C_TWA)] and physical examination. The risk was evaluated by qualitative assessment method, the U.S. Environmental Protection Agency (EPA) inhalation risk assessment method, and the Singapore Ministry of Manpower (MOM) semi-quantitative method. The consistency was analyzed by the Kappa test. Results C_TWA values of lead, arsenic, and cadmium in all positions were lower than the occupational exposure limit (OEL). The levels of blood lead, urine arsenic, and urine cadmium, as well as the prevalence of multiple systems in the exposure group were significantly higher than those in the non-exposure group (P<0.05). The proportions of chronic lead, arsenic, and cadmium poisoning were increasing year by year in the exposure group (P<0.05). The qualitative assessment method mainly indicated low and medium risk, while the EPA and MOM methods mainly indicated medium and high risk, with good agreement between the two methods (Kappa=0.676, P<0.05). Conclusion Although the enterprise meets the C_TWA standards, there are still occupational health risks of lead, arsenic, and cadmium. The EPA inhalation risk assessment method is more applicable.

ObjectiveTo analyze the comorbidity patterns of chronic metabolic diseases and their influencing factors among residents aged 35‒75 years old in Nantong City of Jiangsu Province, and to provide theoretical support for the prevention and control of comorbidities. MethodsThe permanent residents aged 35‒75 years from the Comprehensive Prevention and Control Project of Cardiovascular and Cerebrovascular Diseases in Nantong City from 2021 to 2024 were selected as the research subjects. Clustering analysis and association rule were used to investigate the comorbidity patterns of chronic metabolic diseases, and their influencing factors were identified through logistic regression analyses. ResultsThe prevalence of comorbidity of chronic metabolic diseases among residents aged 35‒75 years in Nantong City was 47.40%. Among comorbidity patterns based on disease counts, the prevalence of hypertension+dyslipidemia was highest in binary comorbidity patterns (6.25%), while that of hypertension+dyslipidemia+obesity was highest in ternary comorbidity patterns (4.01%). Association rules showed that in both binary and ternary comorbidity patterns, the confidence level was highest for obesity+hypertension (72.70%) and obesity+dyslipidemia+hypertension (74.54%). Renal insufficiency formed an independent cluster in cluster analyses. Logistic regression analyses revealed that, compared with the non-comorbidity group, males (OR=2.22, 95%CI: 1.69‒2.91), advanced age (45‒54 years, OR=1.38, 95%CI: 1.02‒1.88; 55‒64 years, OR=1.59, 95%CI: 1.14‒2.23; 65‒75 years, OR=2.34, 95%CI: 1.58‒3.47), and low physical activity (OR=1.26, 95%CI: 1.10‒1.65) were influencing factors for metabolic disease comorbidity. ConclusionIn the comorbidity patterns of chronic metabolic diseases among residents aged 35‒75 years in Nantong City, hypertension, diabetes mellitus, and dyslipidemia interact with each other. Individuals with obesity are more prone to diseases such as hypertension and dyslipidemia. Prevention and control of chronic metabolic diseases should be strengthened for males, individuals with low physical activity and advanced age.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

OBJECTIVE To screen and quantitatively analyze the quality marker （Q-Marker） associated with anti-renal fibrosis in Shenqi shenshuai mixture （SQSS）， so as to provide references for the analysis of pharmacodynamic substances and new drug transformation of SQSS. METHODS The chemical components of SQSS were characterized by untargeted metabolomics. Combined with network pharmacology， gene expression omnibus （GEO） and connectivity map （CMAP） databases， the anti-renal fibrosis Q-Markers of SQSS were screened. HPLC-MS/MS was applied to determine the contents of Q-Markers in 10 batches of SQSS. RESULTS A total of 1 319 compounds were identified from SQSS via untargeted metabolomics，and 84 active ingredients with anti-renal fibrosis activity were further screened out， such as formononetin. Nine anti-renal fibrosis Q-Markers were obtained by network pharmacology and GEO database， including berberine， quercetin， honokiol， nicotinamide， daidzein， coumarin， kaempferol， formononetin and amygdalin. The quantitative results showed that the average contents of the above components （excluding amygdalin） in 10 batches of SQSS were 2.523， 1.942， 26.848， 1.415， 0.692， 0.171， 0.374， 7.401 μg/mL， respectively. CONCLUSIONS Nine anti-renal fibrosis Q-Markers of SQSS were screened in this study， and the contents of eight among them were determined. The results can provide a basis for elucidating the pharmacodynamic material basis and promoting the new drug transformation of SQSS.

Hepatic stellate cells (HSCs) are the primary fibrogenic cells in the liver, and their activation plays a crucial role in the development and progression of hepatic fibrosis. Here, we report that retinoid X receptor-alpha (RXRα), a unique member of the nuclear receptor superfamily, is a key modulator of HSC activation and liver fibrosis. RXRα exerts its effects by modulating calcium/calmodulin-dependent protein kinase kinase β (CaMKKβ)-mediated activation of AMP-activated protein kinase-alpha (AMPKα). In addition, we demonstrate that K-80003, which binds RXRα by a unique mechanism, effectively suppresses HSC activation, proliferation, and migration, thereby inhibiting liver fibrosis in the CCl₄ and amylin liver NASH (AMLN) diet animal models. The effect is mediated by AMPKα activation, promoting mitophagy in HSCs. Mechanistically, K-80003 activates AMPKα by inducing RXRα to form condensates with CaMKKβ and AMPKα via a two-phase process. The formation of RXRα condensates is driven by its N-terminal intrinsic disorder region and requires phosphorylation by CaMKKβ. Our results reveal a crucial role of RXRα in liver fibrosis regulation through modulating mitochondrial activities in HSCs. Furthermore, they suggest that K-80003 and related RXRα modulators hold promise as therapeutic agents for fibrosis-related diseases.

OBJECTIVES: To investigate the mechanism by which Guijianyu ameliorates podocyte injury in a mouse model of diabetic kidney disease (DKD) induced by advanced glycation endproducts (AGEs). METHODS: Sixty db/db mouse models of DKD were randomized equally into 5 groups for treatment with saline, Guijianyu extract at 3 doses or irbesartan for 12 weeks, and the changes in renal pathology and structure were observed using transmission electron microscopy, and the expressions of related genes and key proteins were detected using RT-qPCR and immunohistochemistry. In cultured MPC-5 cells incubated with 50 mg/L AGEs-BSA for 24 h, the effect of different concentrations of Guijianyu extract on cell viability was examined with CCK-8 assay; Western blotting was performed to detect the protein expressions of RAGE, VEGFA, TNF-α, NF-κB(p65), IL-6 and caspase-3, and the mRNA expressions of RAGE, NF-κB (p65), VEGFA and IL-6 were detected with RT-qPCR. RESULTS: In mouse models of DKD, treatment with high-dose Guijianyu extract significantly reduced renal expressions of RAGE, VEGFA, NF-κB(p65), and IL-6 proteins and the mRNA expressions of RAGE, NF-κB, and IL-6. In MPC-5 cells, exposure to AGEs significantly reduced cell viability and increased the protein expressions of RAGE, NF‑κB (p65), VEGFA, TNF-α, IL-6 and caspase-3 (P<0.05) and mRNA expressions of RAGE, NF-κB (p65), VEGFA, and IL-6. Treatment with Guijianyu extract obviously improved cell viability and reduced the expressions of RAGE, NF-κB(p65), VEGFA, TNF-α, IL-6, and caspase-3. Furthermore, Guijianyu extract effectively reversed RAGE agonist-induced elevation of protein expressions of RAGE, VEGFA, TNF-α, IL-6, and caspase-3 and mRNA expressions of RAGE, NF-κB (p65), IL-6, and VEGFA in MPC-5 cells. CONCLUSIONS Guijianyu extract ameliorates AGEs-induced mouse renal podocyte injury in DKD by inhibiting the activation of AGEs-RAGE signaling pathway and reducing the expressions of pro-inflammatory cytokines and vascular endothelial growth factors.
Animals ; Glycation End Products, Advanced ; Drugs, Chinese Herbal/pharmacology* ; Mice ; Signal Transduction/drug effects* ; Podocytes/pathology* ; Diabetic Nephropathies/drug therapy* ; Receptor for Advanced Glycation End Products ; Vascular Endothelial Growth Factor A/metabolism* ; Interleukin-6/metabolism* ; Male

Aconitum (Ranunculaceae) has a long-standing history in traditional Chinese medicine (TCM), where it has been widely used to treat conditions such as rheumatoid arthritis (RA), myocardial infarction, and heart failure. However, the potency of Aconitum alkaloids, the primary active components of Aconitum, also confers substantial toxicity. Therefore, assessing the efficacy and toxicity of these Aconitum alkaloids is crucial for ensuring clinical effectiveness and safety. Metabolomics, a quantitative method for analyzing low-molecular-weight metabolites involved in metabolic pathways, provides a comprehensive view of the metabolic state across multiple systems in vivo. This approach has become a vital investigative tool for facilitating the evaluation of their efficacy and toxicity, identifying potential sensitive biomarkers, and offering a promising avenue for elucidating the pharmacological and toxicological mechanisms underlying TCM. This review focuses on the applications of metabolomics in pharmacological and toxicological studies of Aconitum alkaloids in recent years and highlights the significant role of metabolomics in exploring compatibility detoxification and the mechanisms of TCM processing, aiming to identify more viable methods for characterizing toxic medicinal plants.
Aconitum/metabolism* ; Metabolomics/methods* ; Alkaloids/metabolism* ; Humans ; Animals ; Drugs, Chinese Herbal/pharmacology* ; Medicine, Chinese Traditional

Rice is the world's largest food crop, and its yield and quality are directly related to food security and human health. Grain size, as one of the important factors determining the rice yield, has been widely concerned by breeders and researchers for a long time. To decipher the regulatory mechanism of rice grain size, we obtained a multi-tiller, dwarf, and small-grain mutant htd1 by ethyl methanesulfonate (EMS) mutation from the Japonica rice cultivar 'Zhonghua 11' ('ZH11'). Genetic analysis indicated that the phenotype of htd1 was controlled by a single recessive gene. Using the mutation site map (Mutmap) method, we identified the candidate gene OsHTD1, which encoded a carotenoid cleavage dioxygenase involved in the biosynthesis of strigolactone (SL). The SL content in htd1 was significantly lower than that in 'ZH11'. Cytological analysis showed that the grain size of the mutant decreased due to the reductions in the length and width of glume cells. The function of htd1 was further verified by the CRISPR/cas9 gene editing technology. The plants with the gene knockout exhibited similar grain size to the mutant. In addition, gene expression analysis showed that the expression levels of multiple grain size-related genes in the mutant changed significantly, suggesting that HTD1 may interact with other genes regulating grain size. This study provides a new theoretical basis for research on the regulatory mechanism of rice grain size and potential genetic resources for breeding the rice cultivars with high yields.
Oryza/growth & development* ; Mutation ; Edible Grain/growth & development* ; Alleles ; Plant Proteins/genetics* ; Dioxygenases/genetics* ; Lactones/metabolism* ; Gene Expression Regulation, Plant ; Genes, Plant ; Gene Editing ; CRISPR-Cas Systems ; Phenotype

Objective:To analyze the electroencephalogram features of visual working memory in the delay stage based on microstate analysis.Methods:In this cross-sectional study, ten healthy male subjects aged 19-29 years old from Tianjin Medical University were selected from January to July 2015. The 32-channel electroencephalogram experimental data were recorded from these subjects during the visual working memory eye-open state for 10 min (resting-state) and the delayed matching-to-sample (DMS) task (task-state) conditions, respectively. After data pre-processing, a short-time Fourier transform was applied for time-frequency analysis to extract the characteristic time periods and frequency bands, and electroencephalogram microstates of the resting and task states of visual working memory were computed separately, using an improved k-means clustering algorithm. The Mann-Whitney U test was used to analyze the statistical differences between resting-state and task-state microstate parameters, including global field power (GFP), global explained variance (GEV), time proportion, mean spatial correlation, frequency of occurrence and duration. Results:The time-frequency distribution of the Fz channel in the responsible brain region in DMS task visual working memory showed that the energy was mainly concentrated in the theta band (4-8 Hz) during the delay stage (4.039-7.039 s). The bipolar locations of microstates A, B, C, and D were prefrontal and occipital, central frontal and occipital, right occipital and left frontal, and left occipital and right frontal, respectively. In microstates A and C, the mean spatial correlation of the task-state was both higher than that of the resting state. The comparison results for microstate A were (0.632 5±0.105 8 vs 0.624 5±0.461 4, P<0.05), and the results for microstate C were (0.589 4±0.233 4 vs 0.561 3±0.066 8, P<0.01). The parameters of the task-state microstate D were lower than those of the resting-state, including GFP (1.125±0.061 vs 1.277±0.741, P<0.05), GEV (0.077±0.061 vs 0.101±0.057, P<0.05), and time proportion (0.191±0.165 vs 0.224±0.094, P<0.05) and mean spatial correlation (0.561 2±0.211 6 vs 0.612 1±0.315 2, P<0.01). Conclusions:The critical period of visual working memory is the delay stage and the critical frequency band is the theta band. Microstate D is the characteristic feature of visual working memory in the delay stage of the theta band, and microstates A and C can also serve as its potential features.

BackgroundNon-suicidal self-injury （NSSI） behaviors have become a serious global public health issue.The detection rate of NSSI behaviors among college students in China ranges from 9.8% to 13.53%. Integrated theoretical models suggest that distal family risk factors influence NSSI behaviors through emotional regulation mechanisms. However， existing researches have predominantly focused on single family risks， leaving the relationship between cumulative family risks and NSSI behaviors， as well as the underlying pathways， remain unclear. ObjectiveTo explore the effects of cumulative family risk on NSSI behaviors among college students， analyze the chain mediating roles of emotional regulation difficulties and depression， and examine the moderating effect of gender， so as to provide references for targeted interventions for NSSI behaviors in college students. MethodsOn March 1， 2024， a cluster sampling method was employed to select 518 college students from two universities in Heilongjiang Province. Assessments were conducted using Chinese version of the Childhood Trauma Questionnaire （CTQ）， the Difficulties in Emotion Regulation Scale （DERS）， the Patient Health Questionnaire Depression Scale-9 item （PHQ-9） and the Adolescent Self-Injury Questionnaire. Logistic regression analysis was used to examine the impact of cumulative family risk factors on NSSI behaviors among college students. Model 6 in Process 4.1 was applied to test the chain mediating roles of emotional regulation difficulties and depression in the relationship between cumulative family risk and NSSI behaviors， while model 83 was utilized to analyze the moderating effects of gender on the path "cumulative family risk → emotion regulation difficulties". ResultsA total of 475 （91.70%） college students completed valid questionnaires. Logistic regression analysis revealed that childhood abuse （OR=2.561， 95% CI： 1.566-2.561）， non-parental family structure （OR=2.108， 95% CI：1.102-4.029） and left-behind experience （OR=2.356， 95% CI： 1.021-5.439） were risk factors for NSSI behaviors among college students. Cumulative family risk positively predicted NSSI behaviors （β=0.345，95% CI：1.059-4.286， P<0.01）， and this relationship was mediated by a chain pathway involving emotional regulation difficulties （β=0.136，95% CI： 0.882-4.681， P<0.05） and depression （β=0.160， 95% CI： 0.316-1.073， P<0.01）. Gender moderated the relationship between cumulative family risk and emotional regulation difficulties （β=0.103， 95% CI： 1.567-8.316， P<0.01）， with cumulative family risk significantly predicting emotional regulation difficulties in female students （β=0.374， 95% CI： 0.099-0.084， P<0.01）. ConclusionCumulative family risk can directly influence college students' NSSI behaviors， and may also indirectly affect NSSI behaviors through the mediating roles of emotional regulation difficulties and depression. The path "cumulative family risk → emotional regulation difficulties" in this mediating model is moderated by gender.［Funded by Heilongjiang Philosophy and Social Sciences Research Planning Project （number， 24SHB007）］