ObjectiveTo investigate the present situation of input, output, outcome and impact of all registered community-based rehabilitation stations in Inner Mongolia in China, and analyze how the input predict the output, outcome and impact. MethodsFrom March 1st to April 30th, 2025, a questionnaire survey was conducted on all registered community-based rehabilitation stations in Inner Mongolia, covering four dimensions: input, output, outcome and impact. A total of 1 365 questionnaires were distributed. The input included four items: laws and policies, human resources, equipment and facilities, and rehabilitation information management. The output included two items: technical paths and benefits/effectiveness. The outcome included three items: coverage rates, rehabilitation interventions and functional results. The impact included two items: health and sustainability. Each item contained several questions, all of which were described in a positive way. Each question was scored from one to five. A lower score indicated that the situation of the community-based rehabilitation station was more in line with the content described in the question. Regression analysis was performed using the total score of each item of input dimension as independent variables, and the total scores of the output, outcome and impact dimensions as dependent variables. ResultsA total of 1 262 valid questionnaires were collected. The mean values of input, output, outcome and impact of community-based rehabilitation stations were 1.827 to 1.904, with coefficient of variation of 45.892% to 49.239%. The regression analysis showed that, rehabilitation information management, human resources, and laws and policies significantly predicted the output dimension (R² = 0.910, P < 0.001). Meanwhile, all four items in the input dimension predicted both the outcome (R² = 0.850, P < 0.001) and impact dimensions (R² = 0.833, P < 0.001). ConclusionInput, output, outcome and impact of the community-based rehabilitation stations in Inner Mongolia were generally in line with the content of the questions, although some imbalances were observed. Additionally, the input of community-based rehabilitation stations could significantly predict their output, outcome and impact.

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.

Background Diseases severely affect the efficiency of workers. Comorbidity refers to the coexistence of two or more chronic diseases or health problems in the same individual. Previous studies have primarily focused on occupational injuries caused by environmental exposures, while the analysis of the epidemiological characteristics of self-reported diseases and occupational injuries among manufacturing workers has been insufficient. Objective To analyze the distribution of self-reported diseases and occupational injuries among manufacturing workers, the strength of correlation between different diseases, and common disease combinations, and to preliminarily explore the relationship between self-reported diseases and occupational injuries. Methods A cross-sectional survey was conducted to investigate the occupational injuries of 2382 workers in 2 manufacturing enterprises over the past year, and 2355 questionnaires were valid after cleaning. The questionnaire included three parts: basic information, occupational injury occurrence, and disease prevalence. The self-reported diseases diagnosed by physicians included musculoskeletal diseases, cardiovascular diseases, respiratory diseases, mental health problems, neurological and sensory organ diseases, digestive organ diseases, reproductive and urinary organ diseases, skin diseases, tumors, endocrine and metabolic system diseases, blood diseases and birth defects, a total of 11 types. Log-binomial model was used to calculate the prevalence ratio (PR) value of the association between different diseases, and UpSet diagram was used to present the disease combination pattern. Results In total, 40.2% (946/2355) of the study participants reported at least one disease, while 8.6% (203/2355), 5.2% (122/2355), and 5.9% (140/2355) reported having two, three, and four or more diseases, respectively. A higher prevalence was observed for musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases, which accounted for 18.0% (423/2355), 13.8% (324/2355), 9.3% (218/2355), and 9.1% (214/2355), respectively. Workers with musculoskeletal disorders, cardiovascular diseases, or neurological and sensory organ diseases reported significantly higher incidence of occupational injuries compared with workers without the corresponding diseases (P<0.001, P=0.041, and P=0.006, respectively). Musculoskeletal diseases were strongly associated with comorbidities of neurological and sensory organ diseases (PR values were 1.86 and 1.98, respectively), and the other patters were musculoskeletal diseases and digestive organ diseases (PR and OR values were 1.57 and 2.35, respectively), and musculoskeletal diseases and cardiovascular diseases (PR and OR values were 1.46 and 2.22, respectively). The largest binomial comorbidity group involved musculoskeletal diseases and neurological and sensory organ diseases, accounting for 5.4% (25/465) of the comorbid workers. Conclusion Among the self-reported diseases of manufacturing workers, musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases are more common. Musculoskeletal diseases and neurological and sensory organ diseases are the most common in all comorbidities. Musculoskeletal diseases, cardiovascular diseases, and neurological and sensory organ diseases are associated with occupational injuries. In the prevention and control of occupational injuries, joint prevention strategies targeting multiple diseases should be strengthened.

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.

The application of artificial intelligence(AI)in the medical field, particularly for predicting, diagnosing and treating retinal detachment(RD), has made remarkable achievements. This paper reviews the advancements in AI applications for RD across multiple dimensions, including predicting RD incidence, assessing surgical success rates, forecasting postoperative visual outcomes, and evaluating recurrence rates. In diagnostic support, AI technology has demonstrated significant value, especially in ophthalmic imaging, with applications in the intelligent analysis of ultra-wide-angle fundus photography, optical coherence tomography(OCT), ophthalmologic ultrasound images, and AI chatbots models. Furthermore, AI has proven uniquely beneficial in surgical decision-making, robotic-assisted surgical systems, and the assessment of surgical complications. This paper provides a comprehensive overview of the current state of AI applications in RD, underscoring its potential to address numerous challenges in clinical practice. It also explores existing limitations and offers insights into future directions for development in this field.

With the development of science and technology, electronic devices have become an inevitable part of our daily life and work. There has been an increase of interest in the use of various video display terminals(VDT). The ocular surface is the first barrier of the visual system to resist the damage of the external environment. In recent years, the number of patients with dry eye has consistently increased with the excessive use of VDT. Blue light produced by VDT, with wavelengths ranging from 400 to 500 nm, has a high energy in visible light. Therefore, blue light may also be an important risk factor for dry eye. In particular, the outbreak of COVID-19 has left people worldwide suffering from increased blue light, which promotes further research into dry eye caused by blue light emitted from VDT. In this review, we summarize the recent studies on the role of blue light produced by VDT in dry eye to provide reference for future related research.

Hepatocellular carcinoma (HCC) is one of the most common cancers in clinical practice. Hepatectomy and liver transplantation are currently important treatment modalities for HCC. However, for patients with end-stage liver disease, liver transplantation is the optimal choice, as it can completely resect the tumor while restoring normal liver function. Nevertheless, clinical liver transplantation for HCC faces challenges such as a shortage of donor livers and a high risk of postoperative tumor recurrence and metastasis. How to select HCC patients for liver transplantation and effectively improve the prognosis of HCC liver transplantation has become a hot topic in clinical practice, involving multiple aspects from preoperative precise evaluation to long-term postoperative follow-up. Therefore, this article reviews the full-process management of HCC liver transplantation, including preoperative management, surgical management, postoperative management and the application of multidisciplinary comprehensive treatment in HCC liver transplantation, in order to provide references for improving the prognosis of HCC liver transplant recipients.

OBJECTIVE To investigate the improvement mechanism of hyperoside （HYP） on non-alcoholic fatty liver disease （NAFLD）. METHODS Male C57BL/6 mice were randomly divided into normal （NFD） group， model （HFD） group and HYP group， with 8 mice in each group. Except for NFD group， the mice in other groups were fed with HF60 high-fat diet to establish NAFLD model； HYP group was simultaneously given HYP 100 mg/kg intragastrically every day， for 16 consecutive weeks. The body weight and liver weight of mice in each group were recorded 16 h after the last medication； the histopathological changes and lipid accumulation in the liver were observed， and the contents of triglyceride （TAG） in liver tissue and serum contents of TAG， aspartate transaminase （AST） and alanine transaminase （ALT） were measured； LC-MS/MS method was adopted to detect lipid changes in the liver tissue of mice for lipidomics analysis， and protein expressions of lipid synthesis-associated proteins peroxisome proliferator-activated receptor α （PPARα） were also tested. Human hepatocellular carcinoma cell line HepG2 was divided into normal control group， model group， HYP low-concentration group （50 μmol/L）， HYP high-concentration group （100 μmol/L）， HYP low-concentration+GW6471 （PPARαinhibitor） group， and HYP high-concentration+GW6471 group. Except for normal control group， the remaining cells were induced with oleic acid and palmitic acid to establish a high-fat cell model. The accumulation of lipid droplets in each group of cells was observed， and the TAG content was detected. RESULTS Compared with HFD group， HYP group exhibited significant reductions in liver fat vacuoles， lipid accumulation， liver weight， and TAG content in liver tissue， as well as serum contents of ALT， AST and TAG （P＜0.05）. Additionally， the expression of PPARα protein in liver tissue was significantly increased （P＜0.05）， and the pathological morphological changes associated with NAFLD were alleviated. Lipidomic analysis revealed that HYP significantly reduced the levels of TAG， diacylglycerol and other lipids in the liver. Compared with model group， cellular lipid droplet accumulation and TAG content decreased significantly in HYP low- and high-concentration groups （P＜0.05）； GW6471 could significantly reverse the improvement effect of HYP on above indicators （P＜0.05）. CONCLUSIONS HYP can effectively ameliorate NAFLD induced by a high-fat diet in mice， and the mechanism may be related to the activation of PPARα to regulate hepatic lipid synthesis.

Background When live working line operators engage in upper limb operations, working for a long time with raising arms and the exposure to adverse ergonomic factors tend to increase muscle load, cause fatigue accumulation, and increase the risk of work-related musculoskeletal disorders (WMSDs). Objective To analyze work posture and associated muscle fatigue during executing breaking/connecting contact terminal, and identify adverse ergonomic factors of the work process. Methods This study recruited 10 volunteers to perform breaking/connecting contact terminal simulation. At a distance of 4.5, 3.5, and 2.5 m from the body to the wire, each performed the task 5 times. Visual 3D was used to analyze the kinematic data from motion capture. The surface electromyography (sEMG) signals of the deltoid, biceps, triceps, and brachioradialis were recorded during the simulation and analyzed for muscle fatigue using root mean square (RMS), median frequency (MF), and jointed EMG amplitude and spectrum analysis (JASA). After completion of each task, Borg scale was used to query the volunteers of their subjective fatigue. A 2-min rest was required between each distance. Results The kinematic data from motion capture showed that in the entire process of the task, the right upper limb was higher when lifting, with the right shoulder joint maintaining flexion and fluctuating periodically between abduction and adduction, external and internal rotation, the right elbow joint maintaining flexion and supination. The frequency of task cycle showed a significant effect on the Borg scale scores (P<0.001, partial \begin{document}$ {\eta }^{2} $\end{document}=0.464); the distance showed no significant effect on the Borg scale scores (P>0.05, partial \begin{document}$ {\eta }^{2} $\end{document}=0.002); their interaction effect was not significant (P>0.05, partial \begin{document}$ {\eta }^{2} $\end{document}=0.020). The results of the sEMG signals showed that at a distance of 4.5 m, the volunteers had the highest percentages of maximal voluntary electrical activation (MVE%) in the deltoid and right brachioradialis and the lowest MF values in the deltoid and left brachioradialis after completing 5 task cycles. The results of JASA showed that fatigue was observed in brachioradialis and deltoid after completing 5 task cycles at a distance of 4.5 m, the right deltoid and right brachioradialis at a distance of 3.5 m, in the brachioradialis, deltoid, and left bicep at a distance of 2.5 m. Conclusion The subjective fatigue of workers who engaged in breaking/connecting contact terminal elevates with more repetitive operations. Based on the sEMG and motion capture analysis, it can be found that improper distance between the workers and the target work area can increase the burden from poor posture and improper use of work equipment, and lead to muscle fatigue; the deltoid and brachioradialis are the key muscles of fatigue in this type of operation; changing the angle of the elbow joint and the shoulder joint during the process of the operation can affect the deltoid and brachioradialis exertion and loading.

Background Power grid is an important component of the national infrastructure. The occupational health issues among the workers in this industry are attracting great concern nationwide. Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in neck and shoulder among the power distribution workers of power supply enterprises, and analyze the related influencing factors. Method In April 2023, a total of 1244 workers in 50 municipal power supply bureaus were randomly selected from the three provinces under China Southern Power Grid using cluster sampling method. The questionnaire used in the study was based on a revised Musculoskeletal Disorders Questionnaire and added ergonomic load of upper limb work. \begin{document}$ {\chi }^{2} $\end{document} test and logistic regression model were used to explore the influencing factors of neck pain and shoulder pain among the subjects. Results A total of 1244 valid questionnaires were recovered and the effective recovery rate was 90.87%(1244/1369). The positive rates of neck pain and shoulder pain were 45.5% (566 cases) and 36.3% (452 cases) respectively. The logistic regression analysis results showed that more than 20 years working age (OR=2.27, 95%CI: 1.39, 3.96; OR=2.56, 95%CI: 1.53, 4.26), often (OR=2.08, 95%CI: 1.35, 3.20; OR=2.40, 95%CI: 1.50, 3.58)/quite often (OR=2.96, 95%CI: 1.73, 5.04; OR=2.72, 95%CI: 1.49, 4.94) maintaining a forced posture, and working immediately after break (OR=1.72, 95%CI: 1.04, 2.85; OR=2.14, 95%CI: 1.19, 3.88) were associated with a higher positive rate of neck pain and shoulder pain respectively. Feeling sufficient rest (OR=0.61, 95%CI: 0.47, 0.80; OR=0.63, 95%CI: 0.50, 0.83) and opportunity to decide when to take breaks (OR=0.72, 95%CI: 0.53, 0.98; OR=0.62, 95%CI: 0.41, 0.93) were associated with a lower positive rate of neck pain and shoulder pain respectively. Conclusion The positive rates of neck pain and shoulder pain are high among power distribution workers. The main influencing factors included long working age, quite often maintaining a forced posture, and working immediately after break.