Background Depressive symptoms have become a significant factor affecting the physical and mental health of the occupational population, and workers in petroleum refining enterprises face multiple stressors in their work environment. Objective To explore the impact of occupational noise exposure on depressive symptoms among workers in a petroleum refining enterprise. Methods This cross-sectional study was conducted in July 2024 using a questionnaire survey among workers of a petroleum refining enterprise in Hainan Province. Basic information of the subjects was collected. The Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms, the Chinese version of the Pittsburgh Sleep Quality Index (PSQI) scale was used to assess sleep quality, and the Chinese version of the Effort-Reward Imbalance (ERI) scale was used to evaluate occupational stress. Chi-square test was employed to compare the differences in reporting depressive symptoms among populations with different characteristics. Binary logistic regression models were used to analyze the impact of occupational noise exposure and other factors on depressive symptoms. Results The overall positive rate of depressive symptoms in the study population was 42.7%. The results of the multifactor analysis indicated that compared with the control group, employees in both the low-exposure and high-exposure groups had elevated odds of depressive symptoms, with OR (95%CI) of 2.244 (1.131, 4.454) and 1.970 (1.009, 3.850), respectively. This association remained robust after adjusting for potential confounders, including gender, age, work tenure, and other occupational exposures. Additionally, female [OR (95%CI)=1.483 (1.039, 2.118)], exposure to benzene, toluene, or xylene [OR (95%CI)=1.621 (1.208, 2.174)], sleep disturbance [OR (95%CI)=3.772 (2.942, 4.838)], and occupational stress [OR (95%CI)=2.018 (1.575, 2.585)] were also significantly associated with higher odds of depressive symptoms. Conclusion The positive rate of depressive symptoms is relatively high among employees in this petrochemical enterprise, and occupational noise exposure may be a risk factor for depressive symptoms.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveTo investigate the role of DEAD-box helicase 3 X-linked （DDX3X） in immune-mediated liver injury （ILI）， and to clarify its mechanism by regulating endoplasmic reticulum stress （ERS）-dependent apoptotic pathway and its association with the clinical progression of hepatitis B. MethodsMice were given injection of concanavalin A （ConA） via the caudal vein to establish a model of ILI， PBS （control group） and different concentrations of ConA were injected into the tail vein of hepatocyte-specific DDX3X-knockout mice （DDX3X^ΔHep and DDX3X-flox mice （DDX3X^fl/fl）， respectively.. The log-rank survival analysis， measurement of the serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT）， and HE staining of liver tissue were performed to assess liver injury， and qRT-PCR and Western Blot were used to measure the mRNA and protein expression levels of glucose-regulated protein 78 （GRP78）， CCAAT/enhancer-binding protein homologous protein （CHOP）， and DDX3X in liver tissue. Intraperitoneal injection of 4-phenylbutyric acid （4-PBA， 100 mg/kg） was performed to inhibit ERS. Serum samples （n=30） and liver tissue samples （n=6） were collected from healthy controls， chronic hepatitis B （CHB） patients， and hepatitis B virus-associated liver failure （HBV-LF） patients； ELISA was used to measure the serum level of DDX3X， and qRT-PCR/Western Blot was used to analyze the expression of targets in liver tissue. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups. ResultsCompared with the control group of mice， the expression of DDX3X in the liver of mice induced by ConA was significantly increased after liver injury （P<0.05）， and hepatocyte-specific DDX3X knockout increased the 72-hour survival rate of mice by 55% （compared with 20% in the DDX3X^fl/fl group）， with significant reductions in the serum levels of ALT and AST （P<0.000 1） and the expression levels of the ERS markers GRP78 and CHOP （P<0.05）. After ERS was inhibited by 4-PBA， there was alleviation of liver injury （with reductions in ALT and AST， P <0.001） and a reduction in DDX3X expression （P<0.01）. The analysis of clinical samples showed that the mRNA and protein expression levels of liver DDX3X in CHB patients and HBV-LF patients were significantly higher than those in healthy controls （all P<0.01）， and there was a significant increase in the serum level of DDX3X in HBV-LF patients （P<0.000 1）. ConclusionDDX3X exacerbates ILI by regulating the ERS-dependent apoptotic pathway （GRP78/CHOP）， and its expression is associated with the progression of hepatitis B. Therefore， it can be used as a potential therapeutic target.

Background: Adrenocortical hormones, particularly 11-oxygenated androgens, are pivotal in female reproductive health and fertility. Standardized detection kits and population-specific reference intervals are lacking in China, hindering related clinical applications. Methods: A HPLC-tandem mass spectrometry (HPLC-MS/MS) pipeline was developed, rigorously validated, and applied to simultaneously quantify corticosterone, cortisone, cortisol, 18-OH cortisol, androstenedione (A4), 11β-hydroxyandrostenedione (11-OH A4), dehydroepiandrosterone, and dehydroepiandrosterone sulfate in serum samples from 455 reproductive-aged women (18–45 yrs) in Guangxi, China. Age-dependent concentration trends were analyzed, and reference intervals stratified by age (2.5th to 97.5th percentiles) were established. Correlations with body-composition metrics, ethnicity, and the menstrual cycle were investigated. Results: The HPLC-MS/MS method demonstrated high precision (intra- and inter-assay CVs < 15%), accuracy, and sensitivity. All eight hormones exhibited significant age-related declines (P < 0.001 for seven hormones; P = 0.001 for 11-OH A4). Notably, 11-OH A4 levels were significantly lower in the 35–45-yr (3.05 nmol/L) and 25–34-yr (3.09 nmol/L) age groups than in the 18–24-yr (3.57 nmol/L) age group, whereas no significant difference was observed between the 35–45-yr and 25–34-yr age groups. Weak negative correlations were observed between the body mass index and corticosterone and cortisone levels, whereas ethnicity and the menstrual cycle showed no significant associations with hormone levels. Conclusions We developed an HPLC-MS/MS-based method for simultaneously quantifying eight adrenocortical hormones, including 11-OH A4, and defined age-specific reference intervals for reproductive-aged Chinese women. These findings advance the clinical utility of adrenocortical hormones in diagnosing and managing reproductive disorders.

Objective To systematically evaluate the factors affecting taste alteration in patients undergoing cancer chemotherapy.Methods PubMed,Cochrane Library,Web of Science,CINAHL,Embase,CBM,CNKI,WanFang Data and VIP were searched from the establishment until August 1,2024.The retrieved literature was independently screened,evaluated and the data were extracted by 2 researchers,and statistical analysis was performed using Stata 17.0 software.Results A total of 18 studies were included,involving 4 686 patients.The incidence of taste changes is 73.46％.Totally 9 influencing factors were extracted through quantitative analysis,including oral mucositis(OR=1.98),dry mouth(OR=1.82),nausea(OR=3.05),loss of appetite(OR=2.41),use of triple antiemetic drugs(OR=2.45),gynecological cancers(OR=0.67),lung cancer(OR=0.57),paclitaxel types of chemotherapy d rugs(OR=2.86),and smoking(β=9.38).Conclusion The alteration of taste in cancer chemotherapy patients is in-fluenced by multiple factors.Nurses should regularly and dynamically assess changes in taste and implement individualized and refined nursing interventions in clinical practice to prevent or delay the development of taste alterations,thereby improving patients' quality of life and treatment adherence.

Objective To observe the value of machine learning model based on MR T2WI and diffusion weighted imaging(DWI)radiomics for predicting perineural invasion(PNI)of rectal cancer.Methods Totally 343 patients with rectal cancer were retrospectively collected and divided into training set(n=275,92 PNI[+]and 183 PNI[-])and test set(n=68,23 PNI[+]and 45 PNI[-])at the ratio of 8∶2.Univariate and multivariate logistic regression(LR)were used to analyze clinical data and screen the independent predictors of PNI in rectal cancer,so as to construct a clinical model.The best radiomics features were extracted and screened based on preoperative T2WI and DWI.Then extremely randomized trees,multilayer perceptron,light gradient boosting machine,extreme gradient boosting,support vector machine(SVM),LR,K-nearest neighbor and random forest algorithms were used to construct ML models,respectively,and the optimal ML model was selected to establish a clinical-radiomics ML model combined with clinical relevant independent predictors.The predictive efficacy and clinical value of each model were evaluated.Results Patients' age was the independent predictor of PNI of rectal cancer(OR=0.988,P＜0.001),and the area under the curve(AUC)of the clinical model constructed based on it was 0.435 and 0.458 in training and test sets,respectively.SVM model was the best one among 8 ML models,with AUC in training and test set of 0.887 and 0.854,respectively.The AUC of clinical-radiomics ML model in training and test sets was 0.887 and 0.860,respectively,not different with AUC of SVM model(both P＞0.05).Decision curve analysis showed that when the threshold value was 0.20-0.45,clinical net benefit of SVM model was higher than that of other models.Conclusion SVM model based on T2WI and DWI radiomics could effectively predict PNI of rectal cancer.

Objective:To construct a failure mode and effects analysis(FMEA)evaluation model for medical devices to manage devices,so as to enhance management efficiency for medical devices.Methods:The FMEA was adopted to construct FMEA evaluation model for medical devices,so as to conduct comprehensive lifecycle management for medical devices.The process of management for equipment was optimized,and the operational risk of medical devices was reduced through failure mode(FM)analysis and the construction of management system for equipment.A total of 47 medical devices in clinical use of The First People's Hospital of Neijiang from January to December 2023 were included.In them,23 devices received conventional management mode during January and June 2023,and 24 devices received FMEA evaluation model(model management mode)during July and December 2023.For each group,2,000 patients'medical records were selected.The control effectiveness of infectious indicators,effect of cleaning and disinfection,and quality scores of infectious control for medical devices were compared between different management modes.A self-designed questionnaire was adopted to investigate the recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for two kinds of management modes.Results:In 2,000 patients'medical records,who adopted model management mode,the infection rate of patients,and infection rate of aseptic surgical incision were respectively 0.15%and 0.05%,both were significantly lower than those in the conventional management mode(x2=5.420,8.358,P<0.05).The cleaning rate,and disinfection qualification rate of 24 medical devices,which adopted model management mode,were respectively 83.33%and 87.50%,all of which were significantly higher than these of conventional management mode(x2=8.080,6.741,P<0.05).The scores of standardized operation,rational use,disinfection and cleaning,and emergency intervention for medical devices in adopting model management mode were significantly higher than those in adopting conventional management mode(t=14.435,16.014,13.049,12.537,P<0.05).The recognition scores of engineers who used and managed devices,operators,physicians,and department administrators for adopting model management mode were significantly higher than those for adopting conventional management mode,and the differences were significant(t=12.219,12.147,17.437,13.420,P<0.05).Conclusion:The FMEA evaluation model for medical devices can real-time monitor the entire management process for medical devices,and reduce clinical infections,and ensure normal operation of devices,and improve clinically operational quality of them,and increase satisfaction of staffs in clinical departments.

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.

The data of 44 scalp acupuncture schools are collected to analyze their commonalities in theoretical foundations, needling sites, techniques, and indications. The integration of these characteristics into an optimized, unified scalp acupuncture protocol has become an inevitable trend. The paper discusses the potential for a unified scalp acupuncture protocol from aspects such as theoretical unification, the relationships between point areas, lines, and sites, and needle numbers. It also explores the primary issues and solutions involved in unifying scalp acupuncture protocols, providing a reference for standardization and unification in scalp acupuncture protocol.
Scalp ; Humans ; Acupuncture Therapy/methods* ; Acupuncture Points

This article analyzes the current status of the researches on acupuncture-moxibustion for idiopathic facial palsy (Bell's palsy). Acupuncture-moxibustion is widely applied in treatment of Bell's palsy and the relevant researches are enriched. But the hierarchical discussion on the effectiveness is reported inadequately. Consequently, the necessity and advantages of acupuncture-moxibustion are hardly prominent. Besides, the safety of acupuncture-moxibustion in treatment is not fully explored. The common shortcomings are presented in professional study and statistical designs, and the quality of the evidences is not high. The recommendation strength of acupuncture-moxibustion is weak in international guidelines. The crucial questions are not deeply discussed, and there are lack of the recognized optimal protocol in clinical practical guidelines. It is suggested that the researches should improve the evaluation of the disease itself that may affect the prognosis of Bell's palsy, such as location, conditions and duration of illness, basic diseases and syndrome/pattern differentiation. The effect of acupuncture-moxibustion should be verified hierarchically, the questions on safety should be emphasized, the quality of study should be improved, the staging of treatment should be specified and the effect of acupuncture-moxibustion should be evaluated in multi-dimensions, and the elements of acupuncture-moxibustion should be optimized systematically in the aspects of timing, acupoint selection, needle devices, manipulation, intervention measures and regimen composition. So as to promote the research of acupuncture-moxibustion for Bell's palsy to a new process.
Humans ; Acupuncture Therapy ; Moxibustion ; Bell Palsy/therapy*