BackgroundSleep disorder in the first trimester is a fairly common health problem， and previous studies have mainly reflected the overall sleep quality through scale assessments， which may not accurately capture the differences among various subtypes. ObjectiveTo explore the latent profiles of sleep quality in first-trimester pregnant women and identify the physiological， psychological and social factors， in order to provide practical references for the development of personalized interventions for sleep disorders in first-trimester pregnant women. MethodsA total of 1 066 first-trimester pregnant women who visited the obstetric outpatient clinic of a tertiary A hospital in Shenzhen from October 2021 to October 2022 were investigated using the general information questionnaire， Pittsburgh Sleep Quality Index （PSQI）， Edinburgh Postnatal Depression Scale （EPDS）， Chinese version of short International Physical Activity Questionnaire （IPAQ-S-C） and Social Capital Assessment Tool in Pregnancy for Maternal Health （SCAT-MH）. Then the sleep profiles were identified through latent profile analysis， and the robust mixture regression model was employed to determine the influencing factors of sleep profiles. ResultsA 3-profile solution showed the best fit： 732 cases （68.67%） of good sleep quality group， 87 cases （8.16%） of low sleep efficiency group， and 247 cases （23.17%） of daytime dysfunction group. In comparison with subjects in good sleep quality group， first-trimester pregnant women in low sleep efficiency group were at a younger age （OR=0.951， 95% CI： 0.922~0.980）， held a Bachelor's degree or above （OR=1.869， 95% CI： 1.260~2.773） and exhibited lower levels of social capital （OR=0.962， 95% CI： 0.951~0.973）， while those in daytime dysfunction group were at an older age （OR=1.072， 95% CI： 1.027~1.120） and had higher levels of depression （OR=1.166， 95% CI： 1.115~1.218）. Pregnant women who were workers （OR=0.507， 95% CI： 0.293~0.876） were less likely to report daytime dysfunction. ConclusionThree latent profiles with significant heterogeneity are derived from the sleep quality of first-trimester pregnant women， and levels of depression and social capital are the main influencing factors of sleep quality. ［Funded by Industry-University-Research Innovation Fund for Chinese Universities （number， 2023HT018）］

ObjectiveTo explore the effects of different dosage forms of Kaixinsan （KXS） on the morphology and function of mitochondria in rat models of Alzheimer's disease （AD） and potential mechanisms of action. MethodsMale SD rats were randomly assigned to a sham group， model group， treatment groups receiving KXS decoction， powders， and granules （3.08 g·kg^-1）， as well as donepezil group （0.51×10^-3 g·kg^-1）， with 10 rats in each group. AD model was created using intracerebroventricular injection of streptozocin （STZ）. After 30 days of administration， behavioral assessments were conducted， and mitochondrial morphology was observed using transmission electron microscopy. Mitochondrial respiratory chain complex content was measured via enzyme-linked immunosorbent assay （ELISA）. Changes in mitochondrial membrane potential were measured via JC-1 staining， and superoxide dismutase （SOD） activity and reactive oxygen species （ROS） levels were measured via biochemical assays. The mRNA expression of adenosine 5'-monophosphate-activated protein kinase （AMPK）， peroxisome proliferator-activated receptor gamma coactivator-1α （PGC-1α）， and silent information regulator 3 （SIRT3） was detected by real-time fluorescent quantitative polymerase chain reaction （Real-time PCR）， and Western blot was used to examine the protein expression levels of optic atrophy protein1 （OPA1）， mitochondrial fission protein 1 （FIS1）， AMPK， p-AMPK， PGC-1α， and SIRT3. ResultsCompared with the sham group， rats in the model group had significantly lower recognition index， spontaneous alternation rate， escape latency， number of platform crossings， time spent in the target quadrant， and percentage of distance traveled in the target quadrant distance （P<0.05， P<0.01）. Significant mitochondrial damage was observed in the hippocampal tissue， with a marked decrease in mitochondrial respiratory chain complex content （P<0.01） and reduced mitochondrial membrane potential （P<0.05）. Additionally， the SOD activity was reduced， while ROS levels were elevated （P<0.01）. The mRNA expression of PGC-1α and SIRT3 was significantly downregulated （P<0.01）， along with decreased protein expression levels of OPA1， p-AMPK/AMPK， PGC-1α， and SIRT3， whereas FIS1 protein expression was significantly upregulated （P<0.05， P<0.01）. Compared with the model group， rats in KXS-treated groups （various dosage forms） showed significant improvement in behavioral indexes （P<0.05， P<0.01）， reduced hippocampal mitochondrial damage， and more organized mitochondrial cristae. Mitochondrial respiratory chain complex content was significantly increased （P<0.05， P<0.01）， and mitochondrial membrane potentials were elevated （P<0.05）. SOD activity was elevated， and ROS levels were significantly reduced （P<0.05， P<0.01）. Furthermore， the mRNA expression of PGC-1α and SIRT3 was upregulated， with increased protein levels of OPA1， p-AMPK/AMPK， PGC-1α， and SIRT3， while FIS1 protein expression levels were significantly reduced （P<0.05， P<0.01）. Across the KXS-treated groups， the granule group showed a higher spontaneous alternation rate than the decoction and powder groups （P<0.05）. ConclusionKXS decoction， powders， and granules can improve the learning and memory ability of rats， with granules being the most effective. The mechanism of action may involve activation of the AMPK/PGC-1α/SIRT3 signaling pathway， improvement of the mitochondrial function， and subsequent amelioration of the brain energy metabolism disorders.

ObjectiveTo explore the mechanism by which Ruyan Neixiao cream （RUC） induces ferroptosis in breast precancerous lesion （BPL） cells， and to enrich the theoretical foundation for its use in the treatment of BPL. MethodsThe inhibition of cell proliferation by 1%， 2%， and 4% concentrations of Ruyanneixiao Cream transdermal solution （RUT） was assessed using cell counting kit-8 （CCK-8） and a colony formation assay. Reactive oxygen species （ROS） were measured using the DCFH-DA probe， and the levels of ferrous ions （Fe²⁺）， glutathione （GSH）， and malondialdehyde （MDA） were determined using appropriate kits. Lipid peroxidation was detected with the C11-BODIPY^581/591 fluorescent probe. The expression of nuclear factor E₂-related factor 2 （Nrf2）， solute carrier family 7 member 11 （SLC7A11）， and glutathione peroxidase 4 （GPX4） proteins was analyzed by Western blot. The BPL rat model was constructed using 2，2′-bis（hydroxymethyl）butyric acid （DMBA） combined with estrogen and progesterone， and the rats were treated with RUC for external application. After the 12^th cycle， the rats were euthanized， and histopathological changes in breast tissue were observed by hematoxylin-eosin （HE） staining. Fe²⁺ and MDA levels in breast tissue were measured using corresponding kits. The expression of Nrf2， SLC7A11， and GPX4 proteins in BPL rat breast tissue was detected by immunohistochemistry （IHC） and Western blot. ResultsCompared with the matrix group， the cell viability of MCF-10AT cells in the 1%， 2%， and 4% RUT groups was significantly reduced （P<0.05） in a concentration-dependent manner， with the 24-hour half inhibitory concentration （IC₅₀） being 2.23%. Compared with the 4% RUT group， cell viability in the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the colony formation rates of MCF-10AT cells in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the cell colony formation rate of the RUT + Fer-1 group was significantly increased （P<0.05）. Compared with the matrix group， the levels of ROS and Fe²⁺ in the 1%， 2%， and 4% RUT groups were significantly increased （P<0.05）， while GSH levels were significantly decreased （P<0.05）， and MDA and lipid peroxidation levels were significantly increased （P<0.05）. Compared with the 4% RUT group， ROS and Fe²⁺ levels in the RUT + Fer-1 group were significantly reduced （P<0.05）， while GSH levels were significantly increased （P<0.05）， and MDA and lipid peroxidation levels were significantly reduced （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the 1%， 2%， and 4% RUT groups were significantly decreased （P<0.05）. Compared with the 4% RUT group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the RUT + Fer-1 group were significantly increased （P<0.05）. In the in vivo experiment， compared with the matrix group， the breast tissue histopathological status of the BPL rats in the RUC group was effectively improved， with less dilatation of the mammary ducts and more orderly duct arrangement. No pathological morphology indicative of invasive cancer was observed. Compared with the matrix group， Fe²⁺ and MDA levels in the mammary tissue of the RUC group were significantly increased （P<0.05）. Compared with the matrix group， the protein expression levels of Nrf2， SLC7A11， and GPX4 in the mammary tissue of the RUC group were significantly reduced （P<0.05）. ConclusionRUC may induce ferroptosis in BPL cells by inhibiting the Nrf2/SLC7A11/GPX4 signaling pathway， increasing Fe²⁺ accumulation， and promoting lipid peroxidation.

The incidence and mortality of hepatocellular carcinoma (HCC) in China are among the highest in the world, imposing a heavy social burden. Liver resection and liver transplantation are the primary radical treatments for HCC, although most patients are no longer able to meet the surgical requirements at initial diagnosis. Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT) has the advantages of shrinking tumors, enlarging residual liver, regressing portal vein tumor thrombus and improving the quality of life, which can be used for conversion, downstaging and bridging therapy for HCC before surgical treatment, enabling patients regain the chance of radical treatment and reducing the postoperative recurrence rate. This review focuses on the clinical application and progress of ⁹⁰Y-SIRT in this field.

Primary liver cancer is a common malignant tumor in China. The current main treatment methods include surgical resection, liver transplantation, interventional therapy, radiofrequency ablation, chemotherapy, targeted therapy, and immunotherapy. Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT) represents a critical treatment option for converting unresectable intermediate to advanced hepatocellular carcinoma. This report details a case of a patient with a giant hepatocellular carcinoma in the right lobe treated with ⁹⁰Y resin microsphere at the Third Affiliated Hospital of Sun Yat-sen University. Post-treatment, the tumor showed significant necrosis and reduction in size, with a marked decrease in alpha fetoprotein (AFP) levels and notable improvement in clinical symptoms. The case highlights the substantial efficacy of ⁹⁰Y-SIRT in controlling tumor progression and enhancing patient quality of life.

ObjectiveTo investigate the value of different noninvasive diagnostic models in the diagnosis of esophageal and gastric varices since there is a high risk of esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and to provide a basis for the early diagnosis of esophageal and gastric varices. MethodsA total of 108 patients with significant portal hypertension due to compensated hepatitis B cirrhosis who attended Guangdong Provincial Hospital of Traditional Chinese Medicine from November 2017 to November 2023 were enrolled， and according to the presence or absence of esophageal and gastric varices under gastroscopy， they were divided into esophageal and gastric varices group （GOV group） and non-esophageal and gastric varices group （NGOV group）. Related data were collected， including age， sex， imaging findings， and laboratory markers. The chi-square test was used for comparison of categorical data between groups； the least significant difference t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. The receiver operating characteristic （ROC） curve was plotted to evaluate the diagnostic value of five scoring models， i.e.， fibrosis-4 （FIB-4）， LOK index， LPRI， aspartate aminotransferase-to-platelet ratio index （APRI）， and aspartate aminotransferase/alanine aminotransferase ratio （AAR）. The binary logistic regression method was used to establish a combined model， and the area under the ROC curve （AUC） was compared between the combined model and each scoring model used alone. The Delong test was used to compare the AUC value between any two noninvasive diagnostic models. ResultsThere were 55 patients in the GOV group and 53 patients in the NGOV group. Compared with the NGOV group， the GOV group had a significantly higher age （52.64±1.44 years vs 47.96±1.68 years， t=0.453， P<0.05） and significantly lower levels of alanine aminotransferase ［42.00 （24.00 — 17.00） U/L vs 82.00 （46.00 — 271.00） U/L， Z=-3.065， P<0.05］， aspartate aminotransferase ［44.00 （32.00 — 96.00） U/L vs 62.00 （42.50 — 154.50） U/L，Z=-2.351， P<0.05］， and platelet count ［100.00 （69.00 — 120.00）×10⁹/L vs 119.00 （108.50 — 140.50）×10⁹/L， Z=-3.667， P<0.05］. The ROC curve analysis showed that FIB-4， LOK index， LPRI， and AAR used alone had an accuracy of 0.667， 0.681， 0.730， and 0.639， respectively， in the diagnosis of esophageal and gastric varices （all P<0.05）， and the positive diagnostic rates of GOV were 69.97%， 65.28%， 67.33%， and 58.86%， respectively， with no significant differences in AUC values （all P>0.05）， while APRI used alone had no diagnostic value （P>0.05）. A combined model （LAF） was established based on the binary logistic regression analysis and had an AUC of 0.805 and a positive diagnostic rate of GOV of 75.80%， with a significantly higher AUC than FIB-4， LOK index， LPRI， and AAR used alone （Z=-2.773，-2.479，-2.206， and-2.672， all P<0.05）. ConclusionFIB-4， LOK index， LPRI， and AAR have a similar diagnostic value for esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and APRI alone has no diagnostic value. The combined model LAF had the best diagnostic efficacy， which provides a certain reference for clinical promotion and application.

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 Construction workers represent a high risk group for occupational injuries. Currently, domestic and international studies examining the factors affecting occupational injuries among construction workers focus on demographic and behavioural characteristics. However, there is limited attention to psychosocial, use of digital technology, and health status of workers. Objective To analyze the occurrence of occupational injuries among workers in the construction industry, explore impacts of psychosocial risk, use of digital technology, health status, and preventive measures at the workplace on occupational injuries, and provide a basis for the development of preventive measures. Methods Publicly available data from the European Union Occupational Safety and Health Administration were retrieved, comprising a sample of 2167 construction workers. The outcome indicator was the presence of occupational injuries among workers. A total of 25 variables in the dimensions of psychosocial risk, use of digital technology, health status, and preventive measures at the workplace were extracted after Chi-square test, and then a combination of Boruta's algorithm and logistic regression was applied to identify the key factors affecting occupational injuries. Results Among the 2167 construction workers surveyed, 182 (8.6%) reported experiencing occupational injuries. The Boruta algorithm identified eight characteristics which in descending order of importance were musculoskeletal disorders, job type, depression and anxiety, level of completed education, use of electronic smart products, timely solution of safety problems, overall fatigue, and age. The logistic regression results indicated that six variables had statistically significant effects on occupational injuries: age, job type, level of completed education, musculoskeletal disorders, overall fatigue, and timely solution of safety problems (P<0.05). Conclusion Occupational injuries in construction workers are influenced by a variety of factors, including age, job type, level of completed education, musculoskeletal disorders, overall fatigue, and timely solution of safety problems. Companies and workers should take targeted measures to reduce the incidence of occupational injuries.

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.