Background As a pillar industry in China, the manufacturing sector has a high incidence of non-fatal occupational injuries. The factors influencing non-fatal occupational injuries in this industry are closely related at various levels, including individual, equipment, environment, and management, making the analysis of these influencing factors complex. Objective To identify influencing factors of non-fatal occupational injuries among manufacturing workers, providing a basis for targeted interventions and surveillance. Methods A total of 2243 frontline workers from cable and shipbuilding enterprises were selected as study subjects to investigate the incidence of non-fatal occupational injuries and collect information at four levels: individual, equipment, management, and environment in past 12 months. Data balancing was performed using resampling, and LASSO regression was used to select factors of non-fatal occupational injuries. The influence degree and type of variables were judged based on the magnitude of the estimated coefficients of each variable, where variables with estimated coefficients > 0 are risk factors, and those <0 are protective factors. The area under the receiver operating characteristic (ROC)curve (AUC) was used to test the performance of the model, with an AUC value > 0.7 indicating good model performance. Results Among the 2243 frontline workers, males accounted for 77.7% (1742 out of 2243), with the main age range being 40-49 years old, representing 29.5% (661 out of 2243), 82.7% of the workers (1854 out of 2243) were married, and 55.6% (1248 out of 2243) had a junior middle school education level. The average monthly income for 51.0% (1144 out of 2243) of the workers was between 5000 and 6999 Chinese Yuan. The incidence of non-fatal occupational injuries among the manufacturing workers was 8.4% (189/2243) in the past 12 months. Among the 22 factors associated with the occurrence of non-fatal occupational injuries (P<0.05), 10 were individual-level factors, including gender, smoking, alcohol consumption, colleague relationships, average exercise duration, job burnout, work fatigue, musculoskeletal disorders, cardiovascular diseases, and neurological and sensory organ diseases; 3 were equipment-level factors, including equipment operability, hazardous workpieces, and safety hazards; 5 were environmental-level factors, including low temperatures, special operations, noise, workspace size, and dirty and disorderly environment; and 4 were management-level factors, including daily working hours, weekly working days, overtime, and pre-job technical training. The AUC value of the LASSO regression model was 0.704 and the final model retained a total of 10 variables. Among them, there were 7 risk factors for non-fatal occupational injuries (coefficient > 0), including safety hazards, musculoskeletal disorders, dangerous workpieces, job burnout, dirty and disorderly environment, smoking, and male gender; and 3 protective factors (coefficient < 0), including pre-job technical training, good colleague relationship, and long working days per week. Conclusion Manufacturing enterprises need to focus on the incidence of non-fatal occupational injuries and conduct targeted interventions for non-fatal occupational injuries by controlling potential safety hazards, providing pre-job technical training, reducing dangerous workpieces, rectifying working environment, and reasonably arranging working hours.

Objective To analyze the effect of residual cholesterol (RC) on hearing loss in noise-exposed workers. Methods A total of 3 412 workers engaged in noise operation work in an underground railway enterprise were selected as the research subjects using the judgment sampling method. Their occupational health examination data were collected to analyze the relationship between RC and hearing loss. Results The noise intensity of workplace in the underground rail enterprise was 80.0-85.0 (81.4±3.2) dB(A). The detection rate of hearing loss was 20.2% (691/3 412). The rates of abnormal total cholesterol, triacylglycerol, high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol were 35.6%, 25.7%, 9.5% and 42.4%, respectively. The median and the 25th and 75th percentiles [M(P₂₅,P₇₅)] of RC level were 0.24 (0.15, 0.37) mmol/L. The levels of total cholesterol, triacylglycerol and RC of workers in hearing loss group were higher than those in normal hearing group [M(P₂₅,P₇₅): 4.91(4.37, 5.58) vs 4.84(4.30, 5.46) mmol/L, 1.29(0.91, 1.93) vs 1.16(0.82, 1.67) mmol/L, 0.26(0.16, 0.41) vs 0.24(0.14, 0.37) mmol/L, all P<0.05]. The detection rate of hearing loss in abnormal triglyceride group was higher than that in normal triglyceride group (24.8% vs 18.7%, P<0.01), and the detection rate of hearing loss in abnormal HDL-C group was higher than that in normal HDL-C group (25.0% vs 19.8%, P<0.05). The higher the serum RC level, the higher the detection rate of hearing loss (P<0.01). Multivariate logistic regression result showed that individual with older age, longer work time and higher serum RC level had higher risk of hearing abnormality (all P<0.05), and the risk of hearing abnormality was higher in patients with abnormal fasting blood glucose than patients with normal faseing blood glucose (P<0.05) after controlling for confounding factors such as gender, alcohol consumption, body mass index, and elevated blood pressure. However, abnormal triacylglycerol and HDL-C levels were not significantly related to the risk of hearing abnormality (both P>0.05). Conclusion Serum RC levels are an independent risk factor for hearing loss among noise-exposed workers exposed to noise level of 80.0-85.0 dB(A) in the workplace.

ObjectiveTo investigate and analyze an outbreak of rotavirus infectious diarrhea in a prison in Chongqing Municipality, to provide a basis for adult rotavirus surveillance and prevention, and to explore the public health problems in special settings. MethodsA retrospective survey was conducted to collect and analyze data on individual cases with diarrheal disease on-site. The clinical characteristics, as well as the temporal, spatial and geographical distribution patterns of the epidemic were described. Multi-pathogen detection tests were conducted both on diarrhea cases and environmental samples, with viral genotyping performed on positive samples. A case-control analysis was performed to identify the causes of the outbreak, and an SEIR model was adopted to predict the outbreak trend and evaluate the effectiveness of interventions. ResultsA total of 65 cases were found among the inmates, with an attack rate of 2.03%. The predominant clinical manifestations included diarrhea (89.23%), watery stool (73.85%), and dehydration (18.46%). The epidemic curve indicated a “human-to-human” transmission pattern, with an average incubation period of 5‒6 days. The attack rates among chefs in the main canteen (80.00%, 8/10) and caterers (28.33%, 17/60) were significantly higher than those of other inmates （P<0.05）. Multi-pathogen polymerase chain reaction (PCR) testing detected positive for group A rotavirus, with the viral genotyping identified as G9P [8] strain. Factors such as unprotected "bare-handed" food distribution among cases with diarrhea (OR=9.512, 95%CI: 4.261‒21.234) and close contact with diarrhea cases (OR=3.656, 95%CI: 1.719‒7.778) were the possible cause of the outbreak. The SEIR model (r₀=5, α=0.3, β₁=0.08, β₂=0.04) was constructed using prison inmates as susceptible population, aiming at fitting the initial transmission trend of the outbreak, and the epidemic rate declined rapidly after intervention measures were implemented (r_t≈0). ConclusionThis rare rotavirus infection diarrhea outbreak among adults in confined settings suggests that the construction of public health prevention and control systems in prison may be overlooked. Cross infection during meal processing and distribution in the canteens of such settings is likely to be the cause of the outbreak. Given the potential neglect of public heath system construction in special settings, it is imperative to enhance the surveillance and monitoring of rotavirus and other intestinal multi-pathogens among adults, as well as the construction of public health prevention and control systems in these special settings.

Background With the progression of industrialization, an increasing number of emerging contaminants are entering aquatic environments, posing significant threats to the safety of drinking water. Therefore, establishing a system for identifying unknown hazardous factors and implementing safety warning mechanisms for drinking water is of paramount importance. Among these efforts, non-target screening plays a critical role, but its effectiveness is largely constrained by the scope of coverage of sample pre-treatment methods. Objective To integrate modern chromatography/mass spectrometry techniques with advanced data mining methods to develop a non-discriminatory sample pre-treatment method for comprehensive enrichment of unknown contaminants in drinking water, laying a technical foundation for the discovery and identification of unknown organic hazardous factors in drinking water. Methods A non-discriminatory pre-treatment method based on supramolecular and solid-phase extraction was developed. The final target compounds including 333 pesticides, 194 pharmaceuticals and personal care products (PPCPs), and 59 per- and polyfluoroalkyl substances (PFASs) were used for optimizing the pre-treatment method, confirming its coverage. The impacts of different eluents on the absolute recovery rates of target compounds were compared to select the conditions with the highest recovery for sample pre-treatment. The effects of different supramolecular solvents and salt concentrations on target compound recovery were also evaluated to determine the most suitable solvent and salt concentration. Results The solid-phase extraction elution solvents, supramolecular extraction solvents, and salt concentrations were optimized based on the target compound recovery rates. The optimal recovery conditions were achieved using 2 mL methanol, 2 mL methanol (containing 1% formic acid), 2 mL ethyl acetate, 2 mL dichloromethane, hexanediol supramolecular solvent, and 426 mg salt. The detection method developed based on these conditions showed a good linear relationship for all target compounds in the range of 0.1-100.0 ng·mL⁻¹, with R² > 0.99. The method’s limit of detection ranged from 0.01 ng⁻¹ to 0.95 ng⁻¹, and 95% of target compounds were recovered in the range of 20%-120%, with relative standard deviation (RSD) less than 30%, indicating good precision. Conclusion The combined pre-treatment method of solid-phase extraction and supramolecular solvent extraction can effectively enrich contaminants in drinking water across low, medium, and high polarities, enabling broad-spectrum enrichment of diverse trace contaminants in drinking water. It provides technical support for broad-spectrum, high-throughput screening and identification of organic pollutants in drinking water, and also serves as a reference for establishing urban drinking water public safety warning systems.

Objective To study the chemical constituents of Fallopia aubertii L.Henry Holub. Methods The chemical constituents of Fallopia aubertii L.Henry Holub. were separated and purified by online two-dimensional preparative liquid chromatography and identified by physical and chemical constants and spectral analysis. The inhibitory activities on xanthine oxidase were determined by ultraviolet spectrophotometry. Results Ten compounds were isolated from the extract of Fallopia aubertii L.Henry Holub, including isotachioside（1）, 3,4,5-trimethoxyphenyl-（6'-O-galloyl）-O-β-D-Glucopyranoside（2）, 1-hydroxy-,4,5-1-O-[6'-O-（4''-carboxy-1'',3'',5'trihydrotrimethoxyphenylxy）-phenyl]-β-D-glucopyranoside（3）, myricetrin（4）, myricetin（5）, rutin（6）, quercetin-3-O-β-D-galactoside（7）, quercetin-3-O-β-D-glucopyranoside（8）, lyciumideA（9）, and N-trans-Feruloyltyramine（10）. The inhibitory activity test results showed that the IC₅₀ of compound 5 was 15.92 μmol/L, and the IC₅₀ of compound 6 was 87.36 μmol/L. Conclusion Compounds 1,2,3,4 and 8 were isolated from Medicago polymorpha for the first time. Compounds 5 and 6 had xanthine oxidase inhibitory activity.

Tujia ethnic group medicine Xuetong is derived from Kadsura heteroclita, the stem of which has the medicinal value for anti-rheumatoid arthritis, liver protection, anti-tumor, anti-oxidation effects, and has been widely used in Hunan and Guangdong in China. The selection of reliable and stable reference genes is the basis for subsequent molecular research on K. heteroclita. In this study, GAPDH, TUA, Actin, UBQ, EF-1α, 18S-rRNA, CYP, UBC, TUB, H2A, and RPL were selected as candidate reference genes in Kadsura heteroclita. The gene expression levels of the 11 candidate reference genes of K. heteroclita in its 6 different parts(stem-inside of the cambium, stem-outside of the cambium, fruit, flower, root, and leaf) and under different intervention conditions [drought stress, salt stress, and methyl jasmonate(MeJA) treatment] were detected by quantitative real-time polymerase chain reaction(qRT-PCR). The expression stability of the 11 candidate reference genes was comprehensively analyzed and evaluated by geNorm, NormFinder, ΔCT algorithm, and RefFinder software. The results showed that the expression of UBC and RPL was relatively stable in 6 different parts, and UBC and GAPDH genes were relatively stable under different intervention conditions. To verify the reliability of reference genes for K. heteroclita, this study further examined the relative expression levels of KhFPS, KhIDI, KhCAS, KhSQE, KhSQS, KhSQS-2, KhHMGS, KhHMGR, KhMVD, KhMVK, KhDXR, KhDXS, KhPMVK, and KhGGPS in different parts and under different intervention conditions, which might relate to the synthesis of the main component(Xuetongsu) of K. heteroclita. The results showed that with UBC and RPL or UBC and GAPDH as the reference genes, the expression trends of these 14 genes were basically consistent in different parts or under different intervention conditions for K. heteroclita. In conclusion, UBC can be used as a reference gene of K. heteroclita for its different parts and different intervention conditions, which lays a foundation for further research on the biosynthetic pathway of main components in K. heteroclita.
Real-Time Polymerase Chain Reaction/methods* ; Reference Standards ; Gene Expression Regulation, Plant ; Gene Expression Profiling ; Plant Proteins/metabolism* ; Drugs, Chinese Herbal

In this study, the reductive amination method was used to label IR783 on Astragalus polysaccharides(APS) for the first time, which was verified by ultraviolet-visible spectroscopy and infrared spectroscopy. Quantitative analysis methods of APS-IR783 in plasma and various tissue were established using a multifunctional microplate reader. The pharmacokinetics and tissue distribution of APS-IR783 in mice were investigated after a single intravenous injection of 30 mg·kg~(-1) APS-IR783, and pharmacokinetic parameters were calculated using DAS 2.0 software. The results showed that the APS used had a mass fraction of 93.69%, a relative molecular weight of 1.55×10~5, and a polydispersity index(PDI, M_w/M_n) of 1.73, close to a homogeneous polysaccharide. The IR783 labeling yield reached 86.50%, and the content of IR783 in APS-IR783 was 0.72%. After a single intravenous injection of 30 mg·kg~(-1), the pharmacokinetic parameters of APS in mouse plasma were as follows: T_(max) was(0.67±0.26) h; C_(max) was(1 599.29±159.30) mg·L~(-1); T_(1/2α) and T_(1/2β) were(2.29±3.06) h and(0.44±0.05) h, respectively; AUC_(0-t) was(23 398.91±2 907.03) mg·h·L~(-1); AUC_(0-∞) was(27 710.55±3 506.55) mg·h·L~(-1); MRT_(0-∞) was(34.38±12.59) h; CL was 0.001 L·h~(-1)·kg~(-1); V_z was(0.042±0.017) L·kg~(-1). The in vivo biodistribution study demonstrated that the in vivo exposure ratios of APS in different tissue were in the following order: spleen > liver > kidney > lung > heart > small intestine > muscle > large intestine > brain > stomach, where the top five tissue accounted for 87.54% of the total area under the curve(AUC). This study successfully labeled APS with a water-soluble near-infrared fluorescent probe of IR783 for the first time and revealed the pharmacokinetics and tissue distribution of APS in mice. The paper provides detailed in vivo behavior of APS after intravenous injection, which lays the foundation for the development and utilization of APS and related natural medicines.
Animals ; Mice ; Polysaccharides/chemistry* ; Tissue Distribution ; Astragalus Plant/chemistry* ; Male ; Drugs, Chinese Herbal/chemistry* ; Fluorescent Dyes/pharmacokinetics* ; Female

OBJECTIVES: To construct a Z-score regression model for coronary artery diameter based on echocardiographic data from children in Sichuan Province and to establish a Z-score calculation formula. METHODS: A total of 744 healthy children who underwent physical examinations at Sichuan Provincial People's Hospital from January 2020 to December 2022 were selected as the modeling group, while 251 children diagnosed with Kawasaki disease at the same hospital from January 2018 to December 2022 were selected as the validation group. Pearson correlation analysis was conducted to analyze the relationships between coronary artery diameter values and age, height, weight, and body surface area. A regression model was constructed using function transformation to identify the optimal regression model and establish the Z-score calculation formula, which was then validated. RESULTS: The Pearson correlation analysis showed that the correlation coefficients for the diameters of the left main coronary artery, left anterior descending artery, left circumflex artery, and right coronary artery with body surface area were 0.815, 0.793, 0.704, and 0.802, respectively (P<0.05). Among the constructed regression models, the power function regression model demonstrated the best performance and was therefore chosen as the optimal model for establishing the Z-score calculation formula. Based on this Z-score calculation formula, the detection rate of coronary artery lesions was found to be 21.5% (54/251), which was higher than the detection rate based on absolute values of coronary artery diameter. Notably, in the left anterior descending and left circumflex arteries, the detection rate of coronary artery lesions using this Z-score calculation formula was higher than that of previous classic Z-score calculation formulas. CONCLUSIONS The Z-score calculation formula established based on the power function regression model has a higher detection rate for coronary artery lesions, providing a strong reference for clinicians, particularly in assessing coronary artery lesions in children with Kawasaki disease.
Humans ; Male ; Female ; Child, Preschool ; Child ; Coronary Artery Disease/diagnostic imaging* ; Infant ; Mucocutaneous Lymph Node Syndrome ; Regression Analysis ; Coronary Vessels/diagnostic imaging* ; Echocardiography ; Adolescent

OBJECTIVE: To assess the cardioprotective effect and impact of Qishen Granules (QSG) on different ischemic areas of the myocardium in heart failure (HF) rats by evaluating its metabolic pattern, substrate utilization, and mechanistic modulation. METHODS: In vivo, echocardiography and histology were used to assess rat cardiac function; positron emission tomography was performed to assess the abundance of glucose metabolism in the ischemic border and remote areas of the heart; fatty acid metabolism and ATP production levels were assessed by hematologic and biochemical analyses. The above experiments evaluated the cardioprotective effect of QSG on left anterior descending ligation-induced HF in rats and the mode of energy metabolism modulation. In vitro, a hypoxia-induced H9C2 model was established, mitochondrial damage was evaluated by flow cytometry, and nuclear translocation of hypoxia-inducible factor-1 α (HIF-1 α) was observed by immunofluorescence to assess the mechanism of energy metabolism regulation by QSG in hypoxic and normoxia conditions. RESULTS: QSG regulated the pattern of glucose and fatty acid metabolism in the border and remote areas of the heart via the HIF-1 α pathway, and improved cardiac function in HF rats. Specifically, QSG promoted HIF-1 α expression and entry into the nucleus at high levels of hypoxia (P<0.05), thereby promoting increased compensatory glucose metabolism; while reducing nuclear accumulation of HIF-1 α at relatively low levels of hypoxia (P<0.05), promoting the increased lipid metabolism. CONCLUSIONS QSG regulates the protein stability of HIF-1 α, thereby coordinating energy supply balance between the ischemic border and remote areas of the myocardium. This alleviates the energy metabolism disorder caused by ischemic injury.
Animals ; Myocardial Infarction/physiopathology* ; Male ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Rats, Sprague-Dawley ; Glucose/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Energy Metabolism/drug effects* ; Rats ; Fatty Acids/metabolism* ; Myocardium/pathology*