Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

Objective To analyze the increase in hearing thresholds in different frequency bands of workers exposed to different characteristic noises and the influencing factors of binaural high-frequency hearing loss, and to provide theoretical support for occupational health monitoring in enterprises. Methods In 2021, noise-exposed workers were selected from typical noise-exposing enterprises as research subjects, and their occupational health examination data were tracked for three consecutive years. According to the on-site detection from 2021 to 2023, the cumulative noise exposure (CNE) was calculated. The chi-square test was used to compare the increase of the hearing threshold of workers exposed to different characteristic noises in different frequency bands. A generalized estimation equation was constructed to explore the influencing factors of high-frequency hearing loss in the research subjects. Results The age of the study subjects was 23-54 years old, with 1.6-20.1 years of working experience, mainly distributed in manufacturing workshops, technical workshops and public works workshops. The median LAeq,8h was 85.90 (84.5, 86.1) dB(A), and the average CNE was 94.3±2.6 dB(A). The number of people with increased hearing thresholds in each frequency band was 0.5kHz>6kHz>4kHz>3kHz>1kHz>2kHz. There were statistically significant differences in the increase of hearing thresholds in each frequency band, binaural speech frequency impairment, and high-frequency hearing loss among subjects with different characteristics (P<0.05). The detection rate of binaural speech frequency hearing loss was the highest in subjects aged>45 years, with a length of service of>15 years, and with a CNE>96dB(A). The detection rate of binaural high-frequency hearing loss was the highest in subjects aged 35-40 years, with a length of service of 5-10 years, and with a CNE>96dB(A).In addition, the detection rate of binaural speech frequency and high-frequency hearing loss increased with the increase of CNE(P<0.05). The GEE model showed that age>40 years and CNE>96dB(A) were risk factors for high-frequency hearing loss in both ears. Conclusion With increasing age and CNE, hearing thresholds rise across all frequency bands, elevating the risk of binaural speech-frequency and high-frequency hearing loss, thereby increasing the likelihood of occupational noise-induced deafness.

To analyze the prevalence, drug resistance and whole genome characteristics of Mycoplasma pneumoniae (MP) in respiratory throat swab samples of hospitalized children with pneumonia in Suzhou City from 2023 to 2024. Throat swab samples of hospitalized children aged 0-14 years old with pneumonia in Suzhou were collected from September 2023 to September 2024. Real-time fluorenscence quantitative PCR technology was used to detect MP nucleic acid. The results showed that the positive rate of MP in 3 235 samples was 22.44% (726/3 235), with a rate of 55.00% in week 47 of 2023. The positive rate of MP increased with age ( χ2=45.842, P<0.001). The study selected MP nucleic acid test positive samples from week 20 (5.13-5.19) to week 23 (6.3-6.9) of 2024 for isolation, culture and resistance phenotype detection. About 31 MP strains were successfully isolated and cultured, all of which were resistant to macrolides. The next-generation sequencing technology and nanopore sequencing technology were used for genome sequencing. All 31 strains carried the A2063G mutation, with the main prevalent genotype being the P1-1, and the main mlST type being the ST3. Despite the overall genomic similarity between strains being over 99%, there were significant differences between the P1-1 and P1-2 strains in the P1 gene region. In summary, from 2023 to 2024, the main MP type prevalent in Suzhou City is the P1-1 genotype. All isolated MP strains carry an A2063G resistance site mutation and are resistant to macrolides, requiring continuous monitoring and further research.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

Bongkrekic acid(BA)is a toxin with stable properties and no distinctive smell.It exists in common foods such as fermented edible grain products,potato products,spoiled tremella fuciformis and auricularia polytricha,as well as auricularia polytricha that has been soaked too long.It can easily cause food poisoning.At present,there is still a lack of complete method to detect BA,and no spe-cific antidote of BA has been found.Therefore,BA poisoning is easy to be misdiagnosed or missed diagnosed,and its mortality rate remains high.In recent years,studies have revealed the toxic mecha-nism of BA and found that BA can inactivate some enzymes containing thiol groups(-SH)and in-hibit the synthesis and transport of adenosine triphosphate(ATP),causing damage to liver,kidney,brain and other parenchymal organs.This article reviews the autopsy cases and literature of deaths caused by BA poisoning at home and abroad,systematically summarizes the epidemiology,clinical manifestations,pathological changes,toxicological mechanisms,detection methods,forensic diagnostic key points and challenges of BA in forensic medicine,with the aim of providing a reference for foren-sic identification of related cases.

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

Traditional Chinese medicine(TCM) decoction pieces are a core carrier for the inheritance and innovation of TCM, and their quality and safety are critical to public health and the sustainable development of the industry. Conventional quality control models, while having established a well-developed system through long-term practice, still face challenges such as relatively long inspection cycles, insufficient objectivity in characterizing complex traits, and urgent needs for improving the efficiency of integrating multidimensional quality information when confronted with the dual demands of large-scale production and precision quality control. With the rapid development of artificial intelligence, machine learning can deeply analyze multidimensional data of the morphology, spectroscopy, and chemical fingerprints of decoction pieces by constructing high-dimensional feature space analysis models, significantly improving the standardization level and decision-making efficiency of quality evaluation. This article reviews the research progress in the application of machine learning in the processing, production, and rapid quality evaluation of TCM decoction pieces. It further analyzes current challenges in technological implementation and proposes potential solutions, offering theoretical and technical references to advance the digital and intelligent transformation of the industry.
Machine Learning ; Drugs, Chinese Herbal/standards* ; Quality Control ; Medicine, Chinese Traditional/standards* ; Humans

Guided by Academician Zhang Boli's theory of "dampness， turbidity， phlegm， and fluid-related diseases"，this paper elaborated on the pathogenesis and syndrome differentiation treatment of heart failure from the perspective of the "spleen-mitochondria". It analyzed the essential similarities between "spleen-mitochondria" and "dampness， turbidity， phlegm， and fluid-related diseases"， as well as their close association with the onset of heart failure. Furthermore，it explored the connection between spleen function and mitochondrial function in traditional Chinese medicine （TCM），positing that the spleen's role in transportation and transformation is analogous to mitochondrial material metabolism and energy conversion，with spleen deficiency closely related to mitochondrial dysfunction. It thus concluded that mitochondrial material metabolism and energy conversion represent the microscopic essence of the spleen's role in transportation and transformation，and mitochondrial dysfunction is a contributing factor to pathological products like dampness and turbid phlegm，which are closely associated with the occurrence of heart failure. The four elements of dampness，turbidity，phlegm，and fluid are a series of related symptoms resulting from abnormal fluid transportation and transformation，serving as both factors in the onset of heart failure and the core pathological basis for its deterioration. Therefore，during the treatment of heart failure，it is essential to regulate mitochondrial function. Early intervention should focus on eliminating dampness and turbidity to improve mitochondrial function and restore normal energy metabolism. In the middle and late stages，emphasis should be placed on resolving phlegm，promoting blood circulation，warming Yang，and reducing water retention to alleviate mitochondrial damage and improve cardiac function. Supporting Qi and strengthening the spleen should be a continuous approach，and treatment should be adjusted to enhance mitochondrial function and stabilize the condition，thereby improving prognosis. This paper discussed the role of the spleen and mitochondria in the pathogenesis of heart failure，examined the evolution of heart failure mechanisms from the perspective of dampness， turbidity， phlegm， and fluid-related diseases，and proposed a phased treatment strategy. It enriched the theory of dampness， turbidity， phlegm， and fluid-related diseases and offered new strategies for heart failure treatment. However，in practical application，TCM strategies for treating heart failure need to be integrated with modern medical approaches to provide a more solid scientific foundation for treatment.

Objective To explore the mechanism of Shengmai Decoction in improving heart failure by regulating mitochondrial apoptosis based on network pharmacology and experimental verification;To provide a basis for its clinical application.Methods The active components and targets of Shengmai Decoction were obtained through TCMSP and TCMID databases.Heart failure and mitochondrial apoptosis related targets were retrieved from GeneCards,OMIM,DrugBank,PharmGKB and TTD databases.A protein-protein interaction(PPI)network at the intersection of drugs and diseases was constructed using the STRING database,and a component-target network was constructed using Cytoscape 3.8.2 software.GO and KEGG pathway enrichment analysis was performed on intersecting targets using the DAVID database.Molecular docking was conducted to assess the binding affinity of key components to core target proteins.A rat model of heart failure was established,and the cardiac function of rats were detected by echocardiogram,ELISA was used to detect serum contents of BNP and NT-proBNP,mitochondrial ultrastructure was observed by transmission electron microscope,and Western blot was used to detect protein expressions of Bcl-2/Bax/Caspase-3 signaling pathway.Results A total of 66 active components and 146 targets of Shengmai Decoction were identified,and 22 intersecting targets with heart failure and mitochondrial apoptosis,including key proteins such as TNF,Bcl-2,Bax and Caspase-3.GO enrichment analysis revealed that the intersecting targets were closely associated with inflammation and cell signaling,while KEGG pathway analysis showed that the targets were primarily involved in the TNF signaling pathway,IL-17 signaling pathway,and mitochondrial function regulation.Molecular docking results indicated that Ginsenoside rh2,Beta-sitosterol and other components of Shengmai Decoction exhibited strong binding affinities with Bcl-2,Bax and Caspase-3.Animal experiments demonstrated that Shengmai Decoction significantly improved cardiac function(P<0.05,P<0.01),reduced serum BNP and NT-proBNP contents(P<0.01),alleviated mitochondrial damage,and inhibited mitochondrial apoptosis by upregulating Bcl-2 and downregulating Bax and Caspase-3 protein expression(P<0.01),thereby protecting cardiomyocytes.Conclusion Shengmai Decoction can target and regulate the Bcl-2/Bax/Caspase-3 signaling pathway,improving pathological processes associated with heart failure,which can provide a foundation for clinical optimization of Shengmai Decoction.