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.

Myopia has become a significant eye health problem, which is thought to result from the complex interactions of genetic and environmental factors. This review focuses on two types of hereditary retinal diseases caused by mutations in photoreceptor genes, including rod-cone cell dystrophy(retinitis pigmentosa)and cone dysfunction syndromes(achromatopsia, blue cone monochromatism and Bornholm eye disease). It systematically explores the intrinsic connection between these diseases and the myopia phenotype, and elaborates on the core mechanisms by which pathogenic genes such as RPGR and OPN1LW/OPN1MW, which cause defects in ciliary structure and protein transport and interfere with the visual signal pathway, jointly induce choroidal thinning and scleral remodeling, ultimately driving the elongation of axial length and the occurrence of myopia. By tracing the association of photoreceptor gene mutations with myopia, this article provides a new perspective for in-depth understanding of the genetic mechanism of myopia and is of great significance for the development of early risk warning and targeted intervention strategies.

OBJECTIVE To predict and validate the mechanisms of Chaiqi yigan granules （CQYG） improving hepatocellular carcinoma （HCC）. METHODS The signaling pathways of CQYG intervention in HCC were predicted using network pharmacology. A mice model of transplanted hepatocellular carcinoma was established by injecting H22 hepatoma cells into the axilla. Successfully modeled mice were randomly divided into model group （normal saline）， sorafenib group （positive control， 50 mg/kg）， and CQYG low-， medium- and high-dose groups （24.83， 49.66， 99.32 g/kg）， with 10 mice in each group. Mice in each group were administered the corresponding drug solution or normal saline intragastrically， once a day， for 14 consecutive days. After last administration， pathological morphological changes in the tumor tissues of mice were observed in each group. Immunohistochemical staining was performed to detect the expression of the nuclear proliferation antigen Ki-67 in tumor tissues of mice. Western blot assay was used to measure the expression of proteins related to epithelial-mesenchymal transition （EMT） [N-cadherin， E-cadherin， Vimentin， matrix metalloproteinase 7 （MMP7）] and the mitogen-activated protein kinase （MAPK） signaling pathway [p38 MAPK， phosphorylated p38 MAPK， c-Jun N-terminal kinase （JNK）， phosphorylated JNK， extracellular regulated protein kinase 1/2 （ERK1/2）， phosphorylated ERK1/2] in tumor tissue of mice. RESULTS Network pharmacology analysis revealed that metabolic pathways， pathways in cancer， and the MAPK signaling pathway were key signaling pathways through which CQYG exert their anti-hepatocellular carcinoma effects. In animal experiments， the tumor tissues of mice in the model group exhibited dense tumor cells and vigorous growth. Compared with model group， CQYG high-dose group showed a decreased density of tumor cells in the tumor tissues of mice. Moreover， the expression levels of Ki-67， N-cadherin， MMP7 and Vimentin proteins， along with the phosphorylation levels of ERK1/2 and JNK proteins， were all significantly reduced （ P ＜0.05）. The expression level of E-cadherin protein was significantly increased （ P ＜0.05）， the phosphorylation level of p38 MAPK protein was increased， the difference was not statistically significant （ P ＞0.05）. CONCLUSIONS CQYG can inhibit EMT by regulating the MAPK signaling pathway， thereby suppressing tumor cell invasion and metastasis and ultimately exerting a therapeutic effect in improving HCC.

Background Fatigue among distribution network live-line workers in complex operational environments has become increasingly severe and requires widespread attention. Objective To investigate the positive rates of fatigue and associated influencing factors of live-line power distribution workers, and to make a reasonable strategy to reduce the fatigue of front-line workers. Methods Power supply companies in Guangdong, Guangxi, and Yunnan provinces were selected by cluster sampling in 2023, and all front-line live-line workers in the selected companies were recruited. The questionnaire used in this study consisted of two parts: one was the Fatigue Scale-14 (FS-14) for investigating fatigue status and the other was for associated influencing factors. A FS-14 score greater than 3 points was defined as fatigue. \begin{document}$ {\chi }^{2} $\end{document} test and logistic regression were employed to analyze the factors affecting fatigue. Results A total of 1341 questionnaires were distributed, and 1217 valid questionnaires were recovered, with a valid response rate of 90.75%. The average fatigue score of the participants was (6.84±3.79) points, and a total of 1054 participants scored over 3, resulting a fatigue positive rate of 86.6%. The logistic regression model showed that working under extreme weather (OR=2.03, 95%CI: 1.38, 2.98), overtime 2-3 times a week (OR=5.24, 95%CI: 1.28, 21.40), overtime everyday (OR=6.95, 95%CI: 1.71, 28.27), frequent wrist rotation (OR=1.95, 95%CI: 1.08, 3.51), and leaning back slightly (OR=2.94, 95%CI: 1.19, 7.28) associated with higher positive rates of fatigue. Conclusion The high positive rate of fatigue among live-line power distribution workers suggests severe fatigue issues. Extreme weather conditions, working overtime frequency, and maintaining wrist rotation and backward bending postures during work are main factors affecting their fatigue.

Implementation science (IS) aims to systematically analyze and address the real-world gaps from evidence to practice and the influencing factors of the context. It is necessary to carry out qualitative research to gather relevant implementation outcomes. Nevertheless, traditional qualitative analysis has issues such as consuming a great deal of time and energy, and it is unable to promptly provide the crucial data required for implementation science research. The Rapid Qualitative Analysis (RQA) method, through semi-structured interviews and the adoption of techniques such as immediate data condensation and matrix analysis, can effectively shorten the cycle of qualitative data collection and data processing. RQA can promptly identify social determinants of health such as structural barriers, facilitators, and the behavioral characteristics of target groups. It provides a real-time basis for public health decision-making, the interpretation of complex social phenomena, and the process and effectiveness evaluation of research projects. Although RQA is difficult to conduct in-depth theoretical analysis based on grounded theory, its efficiency and flexibility make it the preferred tool for large-scale and time-sensitive research. Thus, it has been widely applied in implementation science research. This paper sorts out the core concepts and commonly used technical methods of RQA, as well as the differences between RQA and traditional qualitative analysis. It also explores the applications of RQA in intervention optimization, process evaluation, and implementation outcome evaluation. By integrating specific cases, this paper clarifies its application value in the field of implementation science. In the future, it is advisable to explore the integration of RQA with technologies such as artificial intelligence and big data, in order to bridge the gap between the transformation of scientific research achievements into practice. Under circumstances of limited resources or tight time constraints, RQA can be used to efficiently conduct implementation science research, providing convenient and scientific methodological and technical support for accelerating evidence-based practice.

OBJECTIVE To investigate the effects of safflower polysaccharide （SPS） on ischemic stroke （IS） in rats by regulating the growth arrest-specific protein 6 （Gas6）/Axl receptor tyrosine kinase （Axl） signaling pathway. METHODS The modified suture-occluded method was employed to establish a rat model of middle cerebral artery occlusion （MCAO） for IS. The rats were then randomly divided into the model （Model） group， SPS low- and high-dose （SPS-L， SPS-H， 50 and 100 mg/kg） groups， and integrated traditional Chinese and Western medicine （SPS-H+Nim， SPS 100 mg/kg+Nim 15 mg/kg） group， with 10 rats in each group. Another 10 rats were selected as the sham operation （Sham） group. Rats in each group were administered corresponding doses of medication or an equal volume of normal saline intragastrically， with continuous intervention for 14 days. The neurological function of rats in each group was evaluated 24 hours after drug administration. The morphological changes in hippocampal tissue were observed. The contents of interleukin-6 （IL-6）， IL-1β， and tumor necrosis factor-α （TNF-α） in serum， the percentage of cerebral infarction area， the neuronal apoptosis rate， as well as the contents of malondialdehyde （MDA）， superoxide dismutase （SOD）， and brain-derived neurotrophic factor （BDNF） in hippocampal tissue， and the relative protein expression levels of Gas6， phosphorylated Axl （p-Axl）， Axl， B-cell lymphoma-2 （Bcl-2）， and Bcl-2 associated X protein （Bax） were measured. RESULTS Compared with Model group， the neurological function of rats in SPS-L group， SPS-H group and SPS-H+Nim group improved significantly， while serum contents of IL-6， TNF-α， and IL-1β， the percentage of cerebral infarction area， the apoptotic rate of neurons as well as MDA content and relative protein expression of p-Axl and Bax were decreased significantly （ P ＜0.05 or P ＜0.01）. The contents of SOD and BDNF， as well as the relative protein expression of Gas6， Axl， and Bcl-2 in hippocampal tissue， were significantly increased （ P ＜0.05 or P ＜0.01）， and the ischemic injury in hippocampal tissue imp roved to varying degrees. CONCLUSIONS SPS can reduce neuroinflammation， oxidative stress， and neuronal apoptosis in IS rats， alleviate nerve injury， and improve neurological function， which may be achieved by activating the Gas6/Axl signaling pathway.

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.

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.