Background The prevalence of low back pain among workers using vibrating tools in the automobile manufacturing industry is high; however, research on associated risk factors remains limited. Objective To investigate the association between use of vibrating tools and low back pain among automobile manufacturing workers, and to estimate related population attributable risk percentage (PAR%). Methods A cross-sectional survey was conducted using the Chinese Musculoskeletal Disorders Questionnaire among workers with over one year of service in an automobile manufacturing enterprise. Workers were categorized into an exposed group (vibrating tool users) and a control group (non-users) based on their use of vibrating tools during work. The variables showing statistically significant differences between the two groups were selected as covariates for matching by 1∶2 nearest-neighbor propensity score. Chi-square test was used to compare the prevalence of low back pain between the matched exposed and control groups. Log-binomial regression model was employed to calculate the prevalence ratio (PR), and the PAR% of low back pain attributable to vibrating tool use was subsequently determined. Results A total of 6973 valid questionnaires were collected, comprising 5676 males and 1297 females, with an overall low back pain prevalence of 40.3% (2809/6973). The exposed group included 1255 workers (1134 males, 121 females), with a mean age of (44.2 ± 8.7) years and a mean tenure in the current position of (23.5 ± 9.9) years; the matching control group consisted of 2510 workers (2279 males, 231 females), with a mean age of (44.7 ± 8.6) years and a mean tenure in the current position of (24.0 ± 10.0) years. The prevalence of low back pain was 76.7% (963/1255) in the exposed group, significantly higher than the 29.9% (750/2510) in the control group (P<0.001). The log-binomial regression analysis showed a PR of 2.57 (95%CI: 2.28, 2.90) for the exposed group, with a PAR% of 22.03%. Conclusion The use of vibrating tools among automobile manufacturing workers is positively associated with reporting low back pain. Implementing effective measures to mitigate vibration hazards is crucial for reducing the burden of low back pain in this population.

Objective To investigate the renal protective effect and mechanism of sodium acetate(Ace)on hyperuricemic nephropathy(HN)in mice.Methods Uric acid nephropathy mice model was prepared by intraperitoneal injection of potassium oxonate combined with adenine gavage.Mice were divided into blank control group(0.9％NaCl+0.5％carboxymethyl cellulose sodium),Ace group(200 mmol·L-1 Ace+0.5％carboxymethyl cellulose sodium),model group(0.9％NaCl+350 mg·kg-1 potassium oxonate+70 mg·kg-1 adenine),and experimental group(based on model group with additional 200 mmol·L-1 Ace).Serum and urine uric acid(UA)and serum creatinine(SCr)levels were observed in each group.Real-time fluorescence quantitative reverse transcription-polymerase chain reaction(qRT-PCR)was used to detect the expression levels of kidney injury molecule-1(Kim-1)and anti-aging gene Klotho,renal fibrosis markers Collagen Ⅰ and Fibronectin,intestinal inflammation-related factors interleukin-1 β(IL-1 β),and mRNA expression levels of tight junction proteins Zo-1.Results The serum UA levels of blank control group,Ace group,model group,and experimental group mice were(259.52±24.40),(227.71±35.91),(604.06±73.55),and(496.24±30.16)μmol·L-1,respectively;SCr levels were(16.85±0.40),(16.18±0.94),(22.38±1.56),and(19.78±1.43)μmol·L-1;Kim-1 mRNA relative expression levels were 1.04±0.25,1.17±0.28,13.00±2.87,and 4.24±3.92;Klotho mRNA relative expression levels were 1.04±0.15,1.02±0.18,0.43±0.12,and 0.69±0.12;Collagen Ⅰ mRNA relative expression levels were 1.05±0.15,1.02±0.18,3.19±1.09,and 1.61±0.55;Fibronectin mRNA relative expression levels were 1.07±0.18,1.02±0.25,7.86±2.40,and 3.34±2.10;intestinal IL-1β mRNA relative expression levels were 1.00±0.01,1.01±0.03,2.55±0.63,and 1.21±0.28;intestinal Zo-1 mRNA relative expression levels were 1.00±0.07,1.07±0.09,0.54±0.20,and 0.92±0.17.The above indicators in blank control group compared with model group,and experimental group compared with model group,all showed statistically significant differences(P＜0.05,P＜0.01,P＜0.001).Conclusion Sodium acetate can effectively reduce UA levels in HN mice,significantly improve renal injury and fibrosis,and its mechanism may be related to the improvement of intestinal inflammatory response and up-regulation of intestinal Zo-1/Occuludin pathway to reduce intestinal mucosal permeability.

Objective To investigate the influence of individual factors and labor organization factors on work-related musculoskeletal disorders (WMSDs) in automobile manufacturing workers, and to provide a scientific basis for the prevention and treatment of WMSDs in automobile manufacturing workers. Methods In April 2020, 5564 workers in an automobile factory were selected by cluster sampling method. The prevalence of WMSDs was investigated by using the Musculoskeletal Disorders Questionnaire, and the influence of individual factors and labor organization factors on WMSDs was investigated by using generalized estimation equation. Results The prevalence rate of WMSDs was 79.00% (4396/5564), and the prevalence rate of multisite WMSDs was 67.95% (3781/5564). The analysis of generalized estimation equation showed that doing the same job every day (OR= 1.478, P < 0.05), age ≥40 years (OR=1.416, P< 0.05), personnel shortage (OR= 1.356, P < 0.05), and work length of 6～10 years and 11～15 years (OR= 1.349, P< 0.05) were the main risk factors for WMSDs in automobile manufacturing workers. Shift work and working time > 40 hours per week increased the risk of WMSDs (P< 0.05). Male and adequate rest time were protective factors for WMSDs. The job correlation matrix showed that WMSDs in most parts had a positive correlation. Conclusions The prevalence of multisite WMSDs of workers in automobile manufacturing industry is high, and unreasonable labor organization is the main risk factor of WMSDs. Appropriate work breaks can effectively reduce the risk of WMSDs, and effective intervention measures should be carried out to prevent the occurrence of WMSDs in workers in automobile manufacturing industry. The generalized estimation equation can better analyze the influencing factors of WMSDs.

ObjectiveTo explore the impact of overtime work on work-related musculoskeletal disorders in male employees in the automobile manufacturing industry. Methods A total of 1 731 male employees with more than one year of working experience from an automobile manufacturing industry were selected as the research subjects using judgment sampling method. The Musculoskeletal Disorder Questionnaire was used to investigate the prevalence of musculoskeletal disorder. Employees were divided into control group and overtime group, and a 1∶1 matching was performed using propensity score matching method, and 573 pairs were successfully matched. The prevalence of WMSDs in various body parts was compared between the two groups. Results The overtime working rate of the research subjects was 34.2%, and the prevalence of WMSDs was 57.1%. Overtime work increased the risk of WMSDs in the neck, shoulders, upper back, lower back, ankle/feet, and overall body of the workers (all P<0.05), with the odd ratio and 95% confidence interval of 1.43 (1.10-1.85), 1.38 (1.06-1.80), 1.42 (1.07-1.89), 1.28 (1.01-1.62), 1.37 (1.01-1.87), and 1.49 (1.17-1.89), respectively. However, there was no association between overtime work and the risk of WMSDs in the elbows, hands/wrists, hips, and knees of the subjects (all P>0.05). Conclusion Overtime work increases the risk of WMSDs in the neck, shoulders, upper back, lower back, ankles/feet, and overall body of male employees in the automobile manufacturing industry. Enterprises should improve labor organization, reduce overtime work, and protect the health of workers.

ObjectiveGastric cancer (GC) seriously affects human health and life, and research has shown that it is closely related to the serine/glycine metabolism. The proliferation ability of tumor cells is greatly influenced by the metabolism of serine and glycine. The aim of this study was to investigate the molecular mechanism of serine/glycine metabolism can affect the proliferation of gastric cancer cells. MethodsIn this work, a stable metabolic dynamic model of gastric cancer cells was established via a large-scale metabolic network dynamic modeling method in terms of a potential landscape description of stochastic and non-gradient systems. Based on the regulation of the model, a quantitative analysis was conducted to investigate the dynamic mechanism of serine/glycine metabolism affecting the proliferation of gastric cancer cells. We introduced random noise to the kinetic equations of the general metabolic network, and applied stochastic kinetic decomposition to obtain the Lyapunov function of the metabolic network parameter space. A stable metabolic network was achieved by further reducing the change in the Lyapunov function tied to the stochastic fluctuations. ResultsDespite the unavailability of a large number of dynamic parameters, we were able to successfully construct a dynamic model for the metabolic network in gastric cancer cells. When extracellular serine is available, the model preferentially consumes serine. In addition, when the conversion rate of glycine to serine increases, the model significantly upregulates the steady-state fluxes of S-adenosylmethionine (SAM) and S-adenosyl homocysteine (SAH). ConclusionIn this paper, we provide evidence supporting the preferential uptake of serine by gastric cancer cells and the important role of serine/glycine conversion rate in SAM generation, which may affect the proliferation ability of gastric cancer cells by regulating the cellular methylation process. This provides a new idea and direction for targeted cancer therapy based on serine/glycine metabolism.

Objective:To investigate the occurrence of low back work-related musculoskeletal disorders (WMSDs) among workers in a container manufacturing factory, and to explore the influencing factors.Methods:In June 2022, 952 workers from a container factory were selected as the research objects by cluster random sampling. Through questionnaire survey, the incidence of low back WMSDs symptoms among workers in the past one year was collected, and the influencing factors of low back WMSDs were analyzed by logistic regression.Results:The incidence rate of low back WMSDs was 46.7% (445/952). The factors with higher exposure at work were frequent slight bending (77.0%, 733/952), frequent overtime (74.1%, 705/952), and the need to turn around while working (62.3%, 593/952). Multivariate logistic regression analysis showed that age over 40 years old, smoking, drinking, often bending over slightly, sitting for a long time, maintaining a large bending posture for a long time, often working overtime, limited operating space, and there was always a need to complete conflicting things in the container manufacturing factory workers were the risks of increasing the low back WMSDs ( OR=1.68, 1.96, 2.47, 1.49, 1.84, 2.11, 1.90, 1.82, 2.00, P<0.05). Standing at work, always friendly colleagues, and always supportive and helpful leaders were protective factors for low back WMSDs ( OR=0.60, 0.32, 0.40, P<0.05) . Conclusion:The incidence of low back WMSDs symptoms in container manufacturing workers is high, and work-related factors such as frequent slight bending, long time holding large bending posture and limited operating space are the focus of ergonomic intervention in container manufacturing enterprises.

Objective:To explore the risk factors of neck work-related musculoskeletal disorders (WMSDs) among automobile manufacturing enterprise workers, and construct the risk prediction model.Methods:In May 2022, a cluster convenience sampling method was used to selet all front-line workers from an automobile manufacturing factory in Xiangyang City as the research objects. And a questionnaire survey was conducted using the modified Musculoskeletal Disorders Questionnaire to analyze the occurrence and exposure to risk factors of neck WMSDs. Logistic regression was used to analyze the influencing factors of workers' neck WMSDs symptoms, and Nomogram column charts was used to construct the risk prediction model. The accuracy of the model was evaluated by the receiver operating characteristic (ROC) curve, the Bootstrap resampling method was used to verify the model, Hosmer-Lemeshow goodness of fit test was used to evaluate the model, and the Calibration curve was drawn.Results:A total of 1783 workers were surveyed, and the incidence of neck WMSDs symptoms was 24.8% (442/1783). Univariate logistic regression showed that age, female, smoking, working in uncomfortable postures, repetitive head movement, feeling constantly stressed at work, and completing conflicting tasks in work could increase the risk of neck WMSDs symptoms in automobile manufacturing enterprise workers ( OR=1.37, 95% CI: 1.16-1.62; OR=2.85, 95% CI: 1.56-5.20; OR=1.50, 95% CI: 1.18-1.91; OR=1.18, 95% CI: 1.02-1.37; OR=1.34, 95% CI: 1.04-1.72; OR=1.62, 95% CI: 1.21-2.17; OR=1.48, 95% CI: 1.13-1.92; P<0.05). While adequate rest time could reduce the risk of neck WMSDs symptoms ( OR=0.56, 95% CI: 0.52-0.86, P<0.05). The risk prediction model of neck WMSDs of workers in automobile manutacturing factory had good prediction efficiency, and the area under the ROC curve was 0.72 (95% CI: 0.70-0.75, P<0.001) . Conclusion:The occurrence of neck WMSDs symptoms of workers in automobile manufacturing factory is relatively high. The risk prediction model constructed in this study can play a certain auxiliary role in predicting neck WMSDs symptoms of workers in automobile manufacturing enterprise workers.

Objective:To investigate the occurrence of low back work-related musculoskeletal disorders (WMSDs) among workers in a container manufacturing factory, and to explore the influencing factors.Methods:In June 2022, 952 workers from a container factory were selected as the research objects by cluster random sampling. Through questionnaire survey, the incidence of low back WMSDs symptoms among workers in the past one year was collected, and the influencing factors of low back WMSDs were analyzed by logistic regression.Results:The incidence rate of low back WMSDs was 46.7% (445/952). The factors with higher exposure at work were frequent slight bending (77.0%, 733/952), frequent overtime (74.1%, 705/952), and the need to turn around while working (62.3%, 593/952). Multivariate logistic regression analysis showed that age over 40 years old, smoking, drinking, often bending over slightly, sitting for a long time, maintaining a large bending posture for a long time, often working overtime, limited operating space, and there was always a need to complete conflicting things in the container manufacturing factory workers were the risks of increasing the low back WMSDs ( OR=1.68, 1.96, 2.47, 1.49, 1.84, 2.11, 1.90, 1.82, 2.00, P<0.05). Standing at work, always friendly colleagues, and always supportive and helpful leaders were protective factors for low back WMSDs ( OR=0.60, 0.32, 0.40, P<0.05) . Conclusion:The incidence of low back WMSDs symptoms in container manufacturing workers is high, and work-related factors such as frequent slight bending, long time holding large bending posture and limited operating space are the focus of ergonomic intervention in container manufacturing enterprises.

Objective:To explore the risk factors of neck work-related musculoskeletal disorders (WMSDs) among automobile manufacturing enterprise workers, and construct the risk prediction model.Methods:In May 2022, a cluster convenience sampling method was used to selet all front-line workers from an automobile manufacturing factory in Xiangyang City as the research objects. And a questionnaire survey was conducted using the modified Musculoskeletal Disorders Questionnaire to analyze the occurrence and exposure to risk factors of neck WMSDs. Logistic regression was used to analyze the influencing factors of workers' neck WMSDs symptoms, and Nomogram column charts was used to construct the risk prediction model. The accuracy of the model was evaluated by the receiver operating characteristic (ROC) curve, the Bootstrap resampling method was used to verify the model, Hosmer-Lemeshow goodness of fit test was used to evaluate the model, and the Calibration curve was drawn.Results:A total of 1783 workers were surveyed, and the incidence of neck WMSDs symptoms was 24.8% (442/1783). Univariate logistic regression showed that age, female, smoking, working in uncomfortable postures, repetitive head movement, feeling constantly stressed at work, and completing conflicting tasks in work could increase the risk of neck WMSDs symptoms in automobile manufacturing enterprise workers ( OR=1.37, 95% CI: 1.16-1.62; OR=2.85, 95% CI: 1.56-5.20; OR=1.50, 95% CI: 1.18-1.91; OR=1.18, 95% CI: 1.02-1.37; OR=1.34, 95% CI: 1.04-1.72; OR=1.62, 95% CI: 1.21-2.17; OR=1.48, 95% CI: 1.13-1.92; P<0.05). While adequate rest time could reduce the risk of neck WMSDs symptoms ( OR=0.56, 95% CI: 0.52-0.86, P<0.05). The risk prediction model of neck WMSDs of workers in automobile manutacturing factory had good prediction efficiency, and the area under the ROC curve was 0.72 (95% CI: 0.70-0.75, P<0.001) . Conclusion:The occurrence of neck WMSDs symptoms of workers in automobile manufacturing factory is relatively high. The risk prediction model constructed in this study can play a certain auxiliary role in predicting neck WMSDs symptoms of workers in automobile manufacturing enterprise workers.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.