Objective To integrate and analyze the disease burden of esophageal cancer caused by alcohol consumption in China from 1990 to 2019, along with the differences between genders, and predict the trends in disease burden changes from 2020 to 2029 to improve prevention and treatment strategies. Methods The disease burden of esophageal cancer caused by alcohol consumption in China from 1990 to 2019 was extracted and integrated from the 2019 Global Burden of Disease (GBD) database, and the corresponding trend was analyzed using the Joinpoint regression model with Joinpoint 4.9.1.0 software. The gray prediction model [GM (1, 1) ] was used to forecast the disease burden of alcohol-related esophageal cancer in China from 2020 to 2029. Results In 2019, the leading causes of esophageal cancer in China were tobacco, alcohol, high body mass index, and insufficient fruit and vegetable intake, accounting for the first to fifth positions in esophageal cancer deaths. From a gender perspective, in 2019, the death number and standardized mortality rate for males were 18.97 times and 20.00 times higher than for females, respectively. The disability-adjusted life years (DALYs) and standardized DALYs rate for males were 33.08 times and 24.78 times higher than those for females, respectively, indicating a heavier disease burden of alcohol-related esophageal cancer among Chinese males. From 1990 to 2019, the average annual percentage change (AAPC) in deaths and DALYs due to alcohol-related esophageal cancer in China was 2.08% and 1.63%, respectively, showing a continuous upward trend with statistical significance (P<0.05). The AAPC values for standardized mortality rate and standardized DALYs rate from 1990 to 2019 were –0.92% and –1.23%, respectively, showing a continuous downward trend with statistical significance (P<0.05). The population aged ≥55 years was the main group bearing the disease burden among all age groups from 1990 to 2019. The gray prediction model predicted that by 2029, the overall standardized mortality rate and standardized DALYs rate would decrease to 2.94/100 000and 67.94/100 000, with a greater decline in females than in males. Conclusion Over the past 30 years, the disease burden of alcohol-related esophageal cancer in China has slightly decreased. However, the reduction in disease burden is still lower compared to the overall decline in esophageal cancer burden, and the disease burden for males is significantly higher than for females. Focusing on prevention and treatment for males and the elderly population remains a major issue in addressing alcohol-related esophageal cancer in China.

Prostate cancer is the most prevalent malignant tumor among men, ranking first in incidence and second in mortality globally. Novel hormone therapies (NHT) targeting the androgen receptor (AR) pathway have become the standard of care for metastatic prostate cancer. This review offers a comprehensive overview of NHT, including abiraterone, enzalutamide, apalutamide, darolutamide, and rezvilutamide, which have demonstrated efficacy in delaying disease progression and improving patient survival and quality of life. Nevertheless, resistance to NHT remains a critical challenge. The mechanisms underlying resistance are complex, involving AR gene amplification, mutations, splice variants, increased intratumoral androgens, and AR-independent pathways such as the glucocorticoid receptor, neuroendocrine differentiation, DNA repair defects, autophagy, immune evasion, and activation of alternative signaling pathways. This review discusses these resistance mechanisms and examines strategies to counteract them, including sequential treatment with novel AR-targeted drugs, chemotherapy, poly ADP-ribose polymerase inhibitors, radionuclide therapy, bipolar androgen therapy, and approaches targeting specific resistance pathways. Future research should prioritize elucidating the molecular basis of NHT resistance, optimizing existing therapeutic strategies, and developing more effective combination regimens. Additionally, advanced sequencing technologies and resistance research models should be leveraged to identify novel therapeutic targets and improve drug delivery efficiencies. These advancements hold the potential to overcome NHT resistance and significantly enhance the management and prognosis of patients with advanced prostate cancer.

Background Occupational stress has emerged as a critical public health concern affecting the physical and mental well-being of workers in the manufacturing sector. However, researchers typically evaluate its core driver—cumulative fatigue—using a crude binary “present/absent” variable, thereby overlooking the high-dimensional complexity and heterogeneity inherent in fatigue characteristics. This oversimplification constrains both the precision and predictive performance of occupational stress risk assessment model. Objective Leveraging a data-driven approach, to survey data on cumulative fatigue among manufacturing employees, and then use this new classification to develop and validate an occupational stress prediction model, with an ultimate aim of enhancing the accuracy and effectiveness of occupational stress assessment. Methods A set of cross-sectional survey data on 3871 manufacturing employees in 2021 were derived from the “Long working hours exposure and its adverse health effect risk assessment” program of the National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention. Occupational stress was assessed using the Core Occupational Stress Measurement Scale, while cumulative fatigue was evaluated via the Worker’s Self-Diagnostic Questionnaire for Fatigue Accumulation. Boruta method was applied to screen core variables from 20 occupational stress influencing factors. Dimensionality reduction of cumulative fatigue features was performed using a Bayesian sparse autoencoder (BASE), followed by comparison and application of clustering methods to achieve multi-class classification of the reduced features. Six machine learning classification models were then selected including logistic regression, support vector machine, decision tree, random forest, adaptive boosting, and lightweight gradient boosting machine (LightGBM) to construct and compare two occupational stress prediction models involving cumulative fatigue combined with ten other core variables: one utilizing the original binary cumulative fatigue label as a core variable, and another employing the novel fatigue classification proposed herein as a core variable. Results The positive rate of occupational stress among the manufacturing employees was 38.9%. The Boruta method identified 11 core variables of occupational stress: depressive symptoms, cumulative fatigue, age, length of service, tenure in current position, average weekly working hours, average daily overtime hours, average monthly income, low levels of exercise, life satisfaction, and sleep quality. The BSAE reduced the original cumulative fatigue factors to 12 dimensions, while the K-means clustering grouped the reduced fatigue features into three categories: no fatigue, moderate fatigue, and sever fatigue. Six occupational stress prediction models were constructed using the three-category labels of cumulative fatigue and ten additional factors. The results indicated that the LightGBM model performed best, achieving an area under the curve (AUC) of 0.78, an accuracy of 0.77, and an F1 score of 0.72. Compared with the model incorporating the traditional binary labels for cumulative fatigue, the best prediction AUC (0.72), accuracy (0.66), and F1 score (0.65) improved by 6%, 11%, and 7%, respectively. Conclusion Cumulative fatigue is a significant predictor of occupational stress among manufacturing employees. Applying data dimensionality reduction combined with three-class cluster analysis to characterize cumulative fatigue improves the performance of occupational stress prediction models. From a data-driven perspective, machine learning methods demonstrate strengths in processing complex datasets, capturing nonlinear relationships, and generating predictions based on key variables. This study therefore confirms that refined processing of core factors substantially enhances the predictive capability of machine learning models in assessing occupational stress risk in the manufacturing workforce.

Objectives:To analyze the disease burden and changing trends of non-rheumatic valvular heart disease(NRVHD)from 1990 to 2019 in China. Methods:Based on the Global Burden of Disease 2019 database,we collected data related to NRVHD in China from 1990 to 2019,analyzed the crude incidence rate,crude prevalence rate,crude disability-adjusted life year(DALY),and age-scaled rate of NRVHD during this period,and analyzed the corresponding trends.The grey prediction model GM(1,1)was used to predict the disease burden of NRVHD in China from 2020 to 2029. Results:The crude incidence,crude prevalence,and crude DALY rates of NRVHD increased in China from 7.87/100 000,123.21/100 000,and 9.83/100 000 in 1990 to 22.85/100 000,374.16/100 000,and 11.95/100 000 in 2019;the age-standardized incidence rate and the age-standardized prevalence rate increased from 9.22/100 000 and 169.04/100 000 in 1990 to 15.30/100000 and 262.85/100 000 in 2019 respectively,with females being higher than males;the age-standardized DALY rate declined from 13.43/100 000 in 1990 to 9.07/100 000 in 2019,with females being higher than males.Joinpoint regression model analysis showed an increasing trend in the age-standardized incidence rate and age-standardized prevalence rate,and a decreasing trend in the age-standardized DALY rate(annual average percentage change[AAPC]values of 1.86%,1.72%and-1.66%,respectively),trend of change was statistically significant(all P<0.05).The burden of disease for all age groups from 1990 to 2019 showed an overall increasing trend,and the crude incidence rate,crude prevalence rate and crude DALY rate all increased with age,and the elderly group over 60 years old was the main group of disease burden.The results of the grey prediction model showed that by 2029,the age-standardized incidence rate and age-standardized prevalence rate would increase to 18.51/100 000 and 303.26/100 000,respectively,and the age-standardized DALY rate would decrease to 7.42/100 000. Conclusions:From 1990 to 2019,the age-standardized incidence rate and age-standardized prevalence rate of NRVHD in China showed an increasing trend,and the age-standardized DALY rate all showed a decreasing trend.The disease burden of NRVHD in China remains high.Women and the senior population are the main target groups needing special attention in China,and more targeted prevention and treatment strategies are needed for high-risk population.

Objective:To investigate the association between serum uric acid,pulmonary function and airflow obstruction in Chinese Taiwan healthy subjects.Methods:All the cross-sectional analysis was performed in the population over 40 years old using the physical examination data of Chinese Taiwan MJ Health Resource Center between 1996 and 2016 stratification by gender.The correlation analyses between serum uric acid were done and multivariate Logistic regression analysis was used to explore the effect of serum uric acid on airflow obstruction.Results:A total of 35 465 people were included in the study,in-cluding 16 411 men and 19 054 women.Among them,the serum uric acid concentration of men was higher than that of women,and the serum uric acid concentration of the people with airflow obstruction was higher than that of the people without airflow obstruction.There was a negative correlation between serum uric acid level and the forced expiratory volume in one second(FEV1)and the force vital capacity(FVC)in women(P＜0.05),but in men the correlation didn't exist(P＞0.05).After adjusting for age,education,smoking status,drinking status,work strength,body mass index,history of cough,his-tory of hypertension,history of diabetes,history of dyslipidemia,white blood cells and blood albumin,the airflow obstruction in women was more likely to exist with the serum uric acid elevated(OR=1.12,95％CI:1.02-1.22,P＜0.05).The results showed that women with hyperuricemia were more likely to have airflow obstruction than those without hyperuricemia(OR=1.36,95％CI:1.06-1.75,P＜0.05).There was no correlation between serum uric acid concentration and airflow obstruction in men(OR=1.04,95％CI:0.96-1.13,P＞0.05),also the hyperuricemia and airflow obstruction(OR=1.12,95％CI:0.89-1.39,P＞0.05).Conclusion:There is a negative correlation between serum uric acid and FEV1 and FVC in relatively healthy women,and there is an association between elevated serum uric acid and airflow obstruction in women,but not in men.Further prospective studies are needed to explore whether high serum uric acid level can increase the risk of airflow obstruction.

Ferroptosis is a newly discovered form of programmed cell death,which is mainly character-ized by the accumulation of iron-dependent lipid peroxidation in cells.Studies have found that ferroptosis may play a key role in the occurrence and development of Parkinson's disease.This article reviews the molecular regulation mechanism of ferroptosis and its research progress in Parkinson's disease,in order to provide the theoretical basis and new ideas for targeted ferroptosis in the treatment of Parkinson's disease.

Objective To evaluate the collateral circulation in patients with acute ischemic stroke(AIS)by using score and grade of prominent cortical vein(PCV)-susceptibility weighted imaging(SWI),and to analyze the relationship between these two imaging features and hemorrhagic transformation(HT).Methods A total of 68 AIS patients admitted in our hospital between Janu-ary 2018 and December 2022 were enrolled in this study.All of them received multimodal brain MRI scanning to observe and analyze the collateral circulation.Then PCV-SWI assessment was performed to obtain PCV score and grade of the collateral circulation.Within 2 weeks,brain MRI scanning was carried out again to evaluate HT,and then the patients were divided into HT group(n=39)and non-HT group(n=29).The relationship between collateral circulation and HT was analyzed.Results The HT group had significantly larger proportion of PVC grade 3 than the non-HT group(P＜0.01).Among the 68 AIS patients,32 had PCV sign with a PCV-SWI score of 0-7,and 36 were identified non-PCV sign with a score of 8-10.There were 27 patients with PCV sign experiencing HT and only 12 with non-PCV sign having HT,with the PCV patients having a higher incidence of HT than the non-PCV patients(P＜0.01).The PCV patients represented a more extensive PCV,and the incidence of HT accounted for 69.23％in them and 30.77％in the non-PCV patients.Of the 68 AIS patients,61 had a diffusion weighted imaging(DWI)-Alberta Stroke Program Early CT Score(ASPECTS)of ≤7 and 7 had a score of＞7,and the incidence of HT was higher in the patients with a DWI-ASPECTS score of ≤7 than those of a score of＞7(97.44％vs 79.31％,P＜0.05).Binary logistic regression analysis showed that PCV grade and NIHSS score at 10-14 d after admission were independent risk factors for HT(OR=2.128,95％CI:1.200-3.774,P=0.010;OR=1.308,95％CI:1.057-1.620,P=0.014),and DWI-ASPECTS score was a protective factor for HT(OR=0.646,95％CI:0.442-0.945,P=0.024).Conclusion DWI-ASPECTS score,PCV grade,and NIHSS score at 10-14 d after admission are independent predictive risk factors for the occurrence of HT in AIS patients in high-altitude areas.Further clin-ical evaluation of PCV signs and infarct size on images is helpful to predict the early occurrence of HT.

Objective To clarify the anti-inflammatory quality markers(Q-markers)of Salvia plebeia and determine their contents,so as to provide a reference for the quality control of Salvia plebeia.Methods The main components of Salvia plebeia were characterized by high-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry(UPLC-Q-TOF-MS/MS).According to the fragmentation information of the secondary mass spectrometry and the literature data,the analysis and identification were carried out.Further,the active components with high oral bioavailability(OB)and in line with the five principles of drug-like(DL)were screened from the identified chemical components through the SwissADME platform.The SwissTargetPrediction database was used to find and predict the component targets of Salvia plebeia.Disease targets were screened through online Mendelian Inheritance in Man(OMIM),GeneCards database,etc.String11.5 database and Cytoscape3.7.2 software were used to construct the PPI network and screen core targets.Gene Ontology(GO)annotation and KEGG pathway enrichment analysis were performed using DAVID6.8,and the enriched pathways were verified by experiments to clarify their mechanism of action.Reverse traceability was used to analyze the potential pharmacodynamic material basis of key pathways,experimental verification was carried out,and high-performance liquid chromatography(HPLC)content determination method was established.Results 36 main components were identified,including flavonoids and terpenoids.Further screening of 190 active ingredients and disease intersection targets;through network topology screening,18 core targets were obtained;enrichment analysis showed that the primary pathways involved in the anti-inflammatory effect of Salvia plebeia include:NF-κB signaling pathway,PI3K-Akt signaling pathway and TNF signaling pathway.Four related components including homoplantaginin,hispidulin,luteolin and isorhamnetin were obtained by reverse traceability of the NF-κB signaling pathway.Molecular docking demonstrated excellent docking activities of the 4 components to PTGS2 with the binding energies of-9.5,-9.7,-9.4,and-9.4 kcal·mol-1,respectively.According to the measurability of quality markers,it was determined that homoplantaginin and hispidulin could be used as anti-inflammatory quality markers of Salvia plebeia.Western Blot results showed that homoplantaginin and hispidulin could significantly reduce the expression of COX-2 and NF-κB p-p65(P<0.05,P<0.01).Conclusion The anti-inflammatory quality markers of Salvia plebeia are homoplantaginin and hispidulin,which can exert anti-inflammatory effects through the NF-κB pathway.

Objective To investigate the clinical features of of patients with Staphylococcus aureus blood-stream infection and risk factors for septic shock.Methods A total of 51 patients diagnosed with Staphylococ-cus aureus bloodstream infection in the hospital from January 2018 to March 2023 were enrolled in the study.According to whether the patients developed septic shock,they were divided into septic shock group and non-septic shock group.The clinical data of the patients were collected,and the clinical laboratory indicators were detected on the day of blood culture samples were collected.Bacteria isolated from blood culture specimens of patients were identified and tested for drug sensitivity.The clinical data and clinical laboratory test indicators of the two groups were compared.Multivariate Logistic regression was used to analyze the independent risk factors of septic shock in patients with Staphylococcus aureus bloodstream infection.The receiver operating characteristic(ROC)curve was used to analyze the predictive value of clinical laboratory test indicators for septic shock in patients with Staphylococcus aureus bloodstream infection.Results Septic shock occurred in 12 of 51 patients,with an incidence of 23.5％.The proportion of patients with diabetes,gouty arthritis,the proportion of patients with long-term glucocorticoid use,the proportion of patients with respiratory tract in-fection,the proportion of patients who died,and the hospitalization cost in the septic shock group were higher than those in the non-septic shock group,and the differences were statistically significant(P＜0.05).Long-term glucocorticoid use was an independent risk factor for septic shock in Staphylococcus aureus bloodstream infection(P＜0.05).The combination of C-reactive protein(CRP),albumin(Alb),neutrophil/lymphocyte ratio(NLR)and procalcitonin(PCT)had high value in predicting septic shock in patients with Staphylococ-cus aureus bloodstream infection,and the area under the ROC curve was 0.983.Conclusion Long-term use of glucocorticoids can lead to an increased risk of septic shock in patients with Staphylococcus aureus blood-stream infection.The combined detection of CRP,Alb,NLR and PCT has a higher predictive value than single detection for septic shock in patients with Staphylococcus aureus bloodstream infection.

Objective:To comprehensively evaluate the performance of the iterative cone beam CT (iCBCT) imaging mode of Varian linear accelerators and to explore its specific advantages in clinical application.Methods:The kV cone beam CT (CBCT) imaging systems of Halcyon 2.0, Edge, and VitalBeam linear accelerators from Tianjin Medical University Cancer Institute & Hospital were selected, among which Halcyon 2.0 and Edge were equipped with the iCBCT imaging mode. The Penta-Guide phantom was used to evaluate the registration accuracy of iCBCT imaging modes. The accuracy of treatment couch position was measured by a ruler. The image quality of the iCBCT and conventional CBCT modes of various imaging devices were analyzed using the CatPhan604 phantom. The imaging beam-on time and reconstruction time were measured to assess image acquisition efficiency. The uniformity, spatial resolution, contrast, contrast-to-noise ratio (CNR), image acquisition time and reconstruction time between two imaging modes were statistically analyzed by t-test. Results:The maximum deviations of image registration measurement results of the iCBCT mode for Halcyon 2.0 and Edge accelerators compared to the standard values were 0.7 mm and 0.6 mm, respectively. The treatment couch position error of all devices was less than 1 mm. The iCBCT images under head scanning protocol primarily improved the uniformity and CNR. Compared to conventional CBCT images, Halcyon iCBCT increased the uniformity and CNR by 2.50% ( P<0.001) and 78.85% ( P<0.001), respectively, while Edge increased them by 2.18% ( P<0.001) and 86.42% ( P<0.001), both superior to VitalBeam CBCT images. Under pelvis scanning protocols, iCBCT images primarily improved the CNR compared to conventional CBCT images. Halcyon and Edge iCBCT increased the CNR by 113.57% ( P<0.001) and 133.87% ( P<0.001), respectively, both superior to VitalBeam CBCT images. In terms of image acquisition efficiency, the average reconstruction times for Halcyon and Edge iCBCT images increased by 7.28 s and 15.53 s, respectively, and the total image acquisition time of Halcyon accelerator was the shortest. Conclusions:While ensuring the registration accuracy, iCBCT imaging mode can significantly improve the CNR of images and improve the uniformity of images under head scanning protocol. The Halcyon imaging system can enhance image acquisition efficiency.