During the career life cycle, workers may face various health problems such as occupational injuries, occupational diseases, and work-related diseases. How to comprehensively protect the health of workers is a crucial scientific issue that needs to be solved urgently. Workers show the characteristics of co-exposure to multiple occupational risks or co-existence of multiple health conditions in their occupational activities. Occupational injuries are closely related to occupational diseases and work-related diseases. To carry out prevention and control of occupational injuries in the context of "big health", we should further strengthen the systematic approach and highlight the concept of "overall process" and "all-round". That is to establish an occupational injury surveillance system covering the whole process of surveillance-assessment-intervention and the evaluation of intervention effects, and to set up the joint prevention and control strategy of occupational injuries, occupational diseases, and work-related diseases. This will promote the implementation of efficient and intensive health management at government, society, employers, workers and other levels to achieve all-round protection of workers' health. When exploring the possible effects of job burnout, occupational stress, comorbidity, and other factors on occupational injuries, the introduction of machine learning methods provides a new approach to identifying and analyzing the influencing factors of occupational injuries and to exploring potential underlying mechanisms.

Background Workers in the cable manufacturing industry are exposed to high-speed machinery and equipment for a long time, coupled with heavy workload, which poses significant risks to their physical health. However, the issue of occupational injuries in this industry has not received enough attention yet. Objective To understand the incidence of occupational injury of workers in cable manufacturing industry and to analyze the influencing factors. Method A basic information questionnaire and an occupational injury questionnaire were developed to investigate the occupational injuries of 1 343 workers in a cable manufacturing enterprise in the past year, and a total of 1 225 valid questionnaires were recovered, with an effective rate of 91.2%. Descriptive statistics were used to characterize the causes, injury locations, injury types, and other characteristics of employees’ occupational injuries. Chi-square test was used to analyze the occupational injury status of groups with different demographic characteristics, occupational characteristics, lifestyles, and interpersonal relationships. Logistic regression was used to analyze the influencing factors of occupational injuries. Result The incidence of occupational injuries among workers in a cable manufacturing enterprise in the past year was 8.6%, which mainly happened in male workers (80.0%) and occurred from May to July in summer (45.7%). The main causes were mechanical injuries (32.4%) and object blows (27.6%). The main sources of damage were machinery and equipment (36.2%) as well as raw materials and products (15.2%). The main injuries were located in upper limbs (53.3%) and lower limbs (22.9%). The main types of injuries were fractures (33.3%) and abrasions/contusions/puncture wounds (19.0%). The results of univariate analysis showed that there were statistically significant variations in the incidence of occupational injuries by gender, overtime, pre-job training, years of service in current position, alcohol consumption, physical exercise per week, and co-worker relationship (P<0.05). The logistic regression model showed that workers who exercised less than twice a week, did not participate in pre-job training, worked overtime, and had fair/poor/very poor colleague relationship had a higher risk of occupational injury, while women had a lower risk of occupational injury. Conclusion The distribution of occupational injury population is mainly male, and the time distribution is mainly from May to July. Gender, physical exercise, pre-job training, overtime, and colleague relationship are the influencing factors of occupational injuries. We should strengthen pre-job training, arrange work hours reasonably, and create a good working atmosphere to reduce the occurrence of occupational injuries.

Background Social psychological factors have emerged as a key area of research in occupational injury prevention. Occupational stress, a significant component of social psychology, has garnered widespread attention due to its potential impact on occupational injury. Objective To analyze the factors influencing occupational stress among cable manufacturing workers and explore the relationship between occupational stress and occupational injury, and to provide scientific evidence for reducing occupational stress and injury. Methods A questionnaire on basic demographics, occupational injury, and occupational stress (Effort-Reward Imbalance, ERI) was used to investigate 1343 workers in a cable enterprise. Chi-square test was employed to analyze the distribution of occupational stress across different worker characteristics. Logistic regression was used to identify factors influencing occupational stress, and a decision tree model was applied to assess the impact of occupational stress on injury risk. Results A total of 1225 valid questionnaires were collected, yielding a response rate of 91.2%. The positive rate of occupational stress was 28.7%, while the incidence of occupational injury in the past year was 8.6%. The results of univariate analysis revealed that workers who had experienced occupational injuries had a higher positive rate of occupational stress compared to those without injuries (P<0.05), and there were significant differences in the distribution of occupational stress by genders, overtime work, shift work, daily working hours, fatigue levels, sleep duration, family relationships, and colleague relationships (P<0.05). The logistic regression results showed that individuals who worked shifts, had fair/poor/very colleague relationships, and frequently worked overtime had a higher risk of occupational stress (P<0.05). The final decision tree model confirmed that occupational stress was a risk factor for occupational injury. Additional factors influencing occupational injury included physical exercise, colleague relationships, pre-job training participation, and gender. Workers who exercised less than twice per week and experienced occupational stress had a significantly higher risk of injury (23.6%) compared to those without occupational stress (10.9%). Conclusion Shift work, colleague relationships, and overtime work are correlated with the positive rate of occupational stress among cable manufacturing workers. Implementing a reasonable work schedule and fostering a positive work environment are recommended. Reducing occupational stress may help lower the risk of occupational injuries in this industry.

Background Light gradient boosting machine (LightGBM) has become a popular choice in prediction models due to its high efficiency and speed. However, the "black box" issues in machine learning models lead to poor model interpretability. At present, few studies have evaluated the severity of occupational injuries from the perspective of LightGBM model and model interpretability. Objective To evaluate the application value of LightGBM models and model interpretability methods in occupational injury prediction. Methods The Mine Safety and Health Administration (MSHA) occupational injury data set of mining industry workers from 1983 to 2022 was used. Injury severity (death/fatal occupational injury and permanent/partial disability) was used as the outcome variable, and the predictor variables included the month of occurrence, age, sex, time of accident, time since beginning of shift, accident time interval from shift start, total experience, total mining experience, experience at this mine, cause of injury, accident type, activity of injury, source of injury, body part of injury, work environment type, product category, and nature of injury. Feature sets were screened using least absolute shrinkage and selection operator (Lasso) regression. A LightGBM model was then employed to predict occupational injury, with area under curve (AUC) of the model serving as the primary evaluation metric; an AUC closer to 1 indicates better predictive performance of the model. The interpretability of the model was evaluated using Shapley additive explanations (SHAP). Results Through Lasso regression, 7 key influencing factors were identified, including accident time interval from shift start, experience at this mine, cause of injury, accident type, body part of injury, nature of injury, and work environment type. A LightGBM model, constructed based on feature selection via Lasso regression, demonstrated good predictive performance with an AUC value of 0.9941 (95%CI: 0.9917, 0.9966), accuracy of 0.9743, specificity of 0.9781, and sensitivity of 0.9640. The predicted probability of fatal occupational injuries showed high consistency with the actual probability of fatal occupational injuries. In the occupational injury prediction model, the importance of each indicator was analyzed through its SHAP value, and it was found that the body part of injury and the nature of injury were the two main features that affected the prediction results of the model, and the impacts of other features were relatively small. The distribution of SHAP values across body part of injury was broad, with significant impacts on the model's prediction of fatal risk, particularly for injuries to the head and neck, as well as multi-part injuries. The nature of injury also exerted influences on the model in different directions, with suffocation/drowning, crushing, and multi-part injuries having a greater impact on the risk of fatal occupational injuries. Conclusion LightGBM model is capable of efficiently processing large-scale data and providing high-precision prediction results. Research on model interpretability aids in more accurately exploring and analyzing various key risk factors for fatal occupational injuries among mining workers, and further reveals the complex interactions among these factors. This, in turn, enables better preventive intervention and protection measures, as well as optimal resource allocation for labor workers.

Objective: To assess the dynamic changes of microcirculation at acupoints in patients with primary dysmenorrhea and cold congelation and blood stasis syndrome using laser speckle blood flow imaging. Methods: Patients with primary dysmenorrhea and cold coagulation and blood stasis syndrome (primary dysmenorrhea group, n=53) and healthy female college students(control group, n=57) who met the inclusion and exclusion criteria from October 2020 to July 2022 were enrolled at Hebei University of Chinese Medicine. On the premenstrual and first day of menstruation, a laser speckle blood flow imaging system was used to measure the microcirculation blood flow perfusion on the surface of acupoints related to the conception, thoroughfare, and governor vessels, and stomach, spleen, and bladder meridians in the abdomen and lumbosacral regions. The dynamic changes in microcirculation were calculated based on the difference in average blood flow perfusion at each acupoint before and after menstruation. Receiver operating curve (ROC) analysis was used to analyze the diagnostic efficacy of dynamic changes in microcirculation on the surface of each acupoint. The microcirculation sensitization rate of acupoints was calculated. Results: Compared with the control group, the dynamic changes in microcirculation at the following acupoints in the primary dysmenorrhea group were increased (P<0.05): conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]); left thoroughfare vessel (left Huangshu[KI16], left Zhongzhu[KI15], left Siman[KI14], left Qixue[KI13], left Dahe[KI12], left Henggu[KI11]); left stomach meridian (left Tianshu[ST25], left Wailing[ST26], left Qichong[ST30]); left spleen meridian (left Daheng[SP15], left Fujie[SP14]); right thoroughfare vessel (right Huangshu[KI16], right Zhongzhu[KI15], right Siman[KI14], right Qixue[KI13], right Dahe[KI12], right Henggu[KI11]); right stomach meridian (right Wailing[ST26], right Daju[ST27], right Shuidao[ST28], right Guilai[ST29], right Qichong[ST30]); and right spleen meridian (right Fujie[SP14]). The area under the ROC curve of conception vessel (Yinjiao[CV7], Qihai[CV6], Shimen[CV5], Guanyuan[CV4]), thoroughfare vessel (right Siman[KI14], left Huangshu[KI16], right Qixue[KI13], right Zhongzhu[KI15], right Dahe[KI12], left Zhongzhu[KI15], left Siman[KI14], right Huangshu[KI16], left Qixue[KI13], right Henggu[KI11], left Henggu[KI11], left Dahe[KI12]); stomach meridian (left Tianshu[ST25], right Guilai[ST29], left Wailing[ST26], right Shuidao[ST28], right Daju[ST27], right Wailing[ST26], right Qichong[ST30], left Qichong[ST30]), and spleen meridian (left Daheng[SP15], left Fujie[SP14], right Fujie[SP14]) was 0.610-0.682 (P<0.05). Compared with the control group, the sensitization rate of some acupoints in the primary dysmenorrhea group increased (P<0.05). Conclusion With the onset of menstruation, the blood flow perfusion of some acupoints in the abdomen (thoroughfare, and conception vessels, and stomach and spleen meridians) of patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome increased, and the status of acupoints changed from a resting state to an active state. These acupoints are sensitive in patients with primary dysmenorrhea and cold blood coagulation and blood stasis syndrome and have a certain diagnostic efficacy, providing a basis for further analyzing the efficacy and mechanism of acupuncture and moxibustion to treat primary dysmenorrhea with cold blood coagulation and blood stasis syndrome.

ObjectiveTo explore the effect of Yishen Tongluo prescription on sperm DNA fragmentation index （DFI） and sperm mitochondrial membrane potential （MMP） in patients with asymptomatic idiopathic asthenospermia infertility. MethodsA total of 128 patients with asymptomatic idiopathic asthenospermia were randomly assigned to an experimental group （64 cases） and a control group （64 cases）. The experimental group received Yishen Tongluo prescription， while the control group was treated with Wuzi Yanzongwan combined with L-carnitine oral solution. One treatment course lasted 12 weeks. Spouse pregnancy rate， sperm progressive motility （PR）， total sperm motility （PR+NP）， sperm function （sperm tail hypotonic swelling rate， sperm acrosin activity）， sperm DFI， and sperm MMP were compared between the two groups before and after treatment. Adverse reactions were observed and recorded during the study， and clinical efficacy and safety were systematically evaluated. ResultsA total of 121 patients completed the study， including 61 in the experimental group and 60 in the control group. The spouse pregnancy rate in the experimental group was 14.75% （9/61）， higher than that in the control group at 6.67% （4/60）， though the difference was not statistically significant. Clinical efficacy in the experimental group was superior to that in the control group （P<0.05）. Compared with the results before treatment， sperm PR， PR + NP， sperm tail hypotonic swelling rate， sperm acrosin activity， sperm DFI， and sperm MMP were significantly improved in both groups after treatment （P<0.05）， with greater improvements in the experimental group （P<0.05）. However， there was no significant change in sperm concentration in either group after treatment. During the study， no abnormal safety indicators or significant adverse reactions occurred in either group. ConclusionThe kidney-tonifying and collateral-dredging method shows good clinical efficacy in the treatment of asymptomatic idiopathic asthenospermia infertility. Yishen Tongluo prescription can improve sperm motility， increase spouse pregnancy rate， enhance sperm function， and demonstrates good safety. Its mechanism may be related to reducing sperm DFI and increasing sperm MMP.

Environmental toxicants have been linked to aging and age-related diseases. The emerging evidence has shown that the enhancement of detoxification gene expression is a common transcriptome marker of long-lived mice, Drosophila melanogaster, and Caenorhabditis elegans. Meanwhile, the resistance to toxicants was increased in long-lived animals. Here, we show that farnesoid X receptor (FXR) agonist obeticholic acid (OCA), a marketed drug for the treatment of cholestasis, may extend the lifespan and healthspan both in C. elegans and chemical-induced early senescent mice. Furthermore, OCA increased the resistance of worms to toxicants and activated the expression of detoxification genes in both mice and C. elegans. The longevity effects of OCA were attenuated in Fxr ^-/- mice and Fxr homologous nhr-8 and daf-12 mutant C. elegans. In addition, metabolome analysis revealed that OCA increased the endogenous agonist levels of the pregnane X receptor (PXR), a major nuclear receptor for detoxification regulation, in the liver of mice. Together, our findings suggest that OCA has the potential to lengthen lifespan and healthspan by activating nuclear receptor-mediated detoxification functions, thus, targeting FXR may offer to promote longevity.

OBJECTIVES: To establish a three-dimensional (3D) visualization-based classification of the left hepatic portal vein (LHPV) and left hepatic vein (LHV) systems using 3D reconstruction technology to facilitate precise segmental/subsegmental resection of left liver lesions. METHODS: Thin-slice contrast-enhanced CT datasets from 244 patients were reconstructed using MI-3DV Works software. The spatial anatomy (origins, branching patterns, and spatial relationships) of the LHPV and LHV branches was analyzed to determine their 3D classifications and segmental liver divisions for guiding surgical planning for anatomical left liver resections. RESULTS: The 3D models of the third- and fourth-order branches of the LHPV and LHV were successfully reconstructed for all the 244 patients. Two types of the LHPV system were identified, where the LHPV either had independent origins [242 cases (99.1%)] or had right anterior portal branches arising from the LHPV trunk [2 cases (0.9%)]. 3D classifications identified two types of the Segment II of the LHPV (based on branch number), 3 types of the Segment III (by spatial distribution of the branches), compact vs dispersed types of the left lateral lobe (determined by Segment II/III branches proximity), 3 types of the Segment IV (by branch number and origin), and 3 types the fourth hilar vessels (transverse branches of the left portal vein) for their supplied segments. The LHV system had two drainage types into the inferior vena cava, and the umbilical fissure veins were classified into 3 types by drainage patterns and distance to the venous roots. These classifications combined with liver segmentations allowed individualized surgical planning for segment-specific resections. CONCLUSIONS The 3D classification of the LHPV and LHV provides valuable clinical guidance for precise anatomical resections of left liver lesions using liver segments or subsegments as anatomical units to enhance surgical accuracy and improve the outcomes of hepatobiliary surgery.
Humans ; Hepatectomy/methods* ; Imaging, Three-Dimensional ; Hepatic Veins/anatomy & histology* ; Portal Vein/anatomy & histology* ; Liver/surgery* ; Liver Neoplasms/blood supply* ; Tomography, X-Ray Computed ; Female