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.

Objective To construct a predictive model for high-grade pathological components of early invasive lung adenocarcinoma(ILAC)based on radiomics.Methods Collecting information on total 495 patients who underwent radical operation and were pathologically diagnosed as stage Ⅰ in the cardiothoracic surgery of Zhoushan Hospital from January 2015 to December 2019,including gender,age,pathological findings,tumor markers and preoperative chest CT images.The micropapillary and solid components in postoperative pathology were defined as"high-grade pathological components",while those without high-grade pathological components were classified into the low-grade group and those with high-grade pathological components were classified into the high-grade group.And patients were randomly divided into the training set(343 cases)and the validation set(152 cases)with a ratio of 7∶3 using the simple randomization grouping method.The region of interest of nodules on CT images were delineated layer by layer by scientific research platform and 1950 radiomics features were extracted.And then those features were filtrated by F-test,Pearson correlation coefficient,and L1 based feature selection.A model was built by using Logistic regression machine learning classifier,named mod 2,and radscore was also obtained.Differences between general information and CT features were analyzed.Binary Logistic regression analysis was used to construct a model for statistically significant variables,named mod 1.At the same time,Radscore was added to build the mod and named comb mod.The area under the curve(AUC),sensitivity and specificity of the three models were calculated.A nomogram was also drawn.Results A total of 495 patients were divided into the training set(n=343)and the validation set(n=152).Gender,carcinoma embryonic antigen(CEA),nodule,and maximum diameter were screened out in clinical features and involved in constructing the mod 1.Twelve features were selected from the radiomics features to build mod 2.Comb mod performed best,training set AUC:0.887,validation set AUC:0.875,and had good clinical practicability.Conclusion The model composed of general feature,CT feature and radiomics features could accurately predict high-grade pathological components in early ILAC,and provide references for clinicians to choose surgical method for patients.

The aim of this study was to investigate the virulence determinants and genetic diversity of foodborne Yersinia enterocolitica from Wenzhou.A total of 71 strains of Yersinia enterocolitica were isolated from food and foodborne diarrhea ca-ses in Wenzhou,and their biotypes,serotypes,and drug resistance were analyzed.On the basis of whole genome sequencing,we assessed virulence gene profiles,and performed multilocus sequence typing(MLST)and core gene multilocus sequence typ-ing(cgMLST).A total of 94.4％(67/71)of isolates belonged to biotype 1A,and the highest proportion had serotype lA/O∶5(29.6％,21/71).The sensitivity rates of the isolates to 14 antibiotics exceeded 95.8％.A total of 16 categories and 126 viru-lence genes were identified,with two strains carrying the pYV plasmid and chromosome-related virulence genes.ST3(31.6％,12/38)was the most widespread MLST type,and cgMLST analysis revealed no dense clusters of genotypes except for strains sharing the same ST.In conclusion,pathogenic strains were identified from foodborne Yersinia enterocolitica in Wenzhou and were found to exhibit high genetic polymorphism.Enhanced regulatory supervision is essential to prevent the outbreak of food-borne diseases caused by Yersinia enterocolitica.

Objective:To assess the accuracy of two-dimensional (2D) photographs in measuring esthetic parameters of the maxillary anterior teeth by comparing them with measurements obtained from three-dimensional (3D) dental models.Methods:A total of one hundred volunteers (49 males, 51 females, aged 18-23 years) were recruited from School and Hospital of Stomatology, Wuhan University from January to February 2024. 3D digital models of their dentitions were obtained using an intraoral scanner, and standardized frontal 2D intraoral photographs were captured with a digital camera. The lengths, widths and width/length ratio of the bilateral incisors, lateral incisors and canines were measured on both the 3D digital models and the 2D intraoral photographs. The width ratios of adjacent maxillary anterior were also calculated on the 2D intraoral photographs and the frontal view of 3D digital models.Results:The widths of lateral incisors [(5.85±0.60) mm] and canines [(4.73±0.71) mm] and the lengths of canines [(8.72±0.96) mm] in the 2D intraoral photographs were significantly lower than those in 3D digital models [(6.65±0.59), (7.76±0.60), (8.90±0.86) mm] ( t=-18.24, P<0.001; t=-54.43, P<0.001; t=-4.40, P<0.001), while there were no significant differences in the lengths and widths of the other teeth ( P>0.05). The width/length ratios measured from the 2D intraoral photographs for the lateral incisors and canines (0.74±0.08, 0.55±0.08) were significantly lower than those measured in the 3D digital models (0.84±0.09, 0.88±0.09) ( t=-19.68, P<0.001; t=-50.21, P<0.001), and the width/length ratio of the central incisors showed no significant difference between the two groups ( P>0.05). The width ratios of canines/lateral incisors and lateral incisors/central incisors measured on the 2D intraoral photographs (0.72±0.06, 0.85±0.11) were significantly smaller than those measured in the frontal view of 3D digital models (0.75±0.06, 0.89±0.11) ( t=-9.31, P<0.001; t=-6.58, P<0.001). Conclusions:There is a difference between 2D and 3D measurement results of teeth in the esthetic area and the magnitude of the difference varies with their position in the dental arch. When analyzing the measurement of the anterior teeth, it is necessary to choose the appropriate method according to the target tooth position.

AIM To study the chemical constituents from the branches and leaves of Toona ciliata Roem.var.pubescens(Franch.)Hand-Mazz.and their antitumor activities.METHODS The compounds were isolated and purified by silica gel,RP-18 reverse phase silica gel and semi-preparative HPLC,the structures of compounds were identified by physicochemical properties and spectral data.The antitumor activities were determined by MTT method.RESULTS Fifteen compounds were isolated and identified as toonaolide D(1),toonaciliatin E(2),bourjotinolone A(3),(21R,23R)-epoxy-21α-ethoxy-24S,25-dihydroxyapotirucalla-7-en-3-one(4),(Z)-toonasterone C(5),(E)-toonasterone(6),3-epi-dyscusin C(7),(Z)-aglawone(8),(E)-volkendousin(9),8(14),15-isopimaradiene-2α,3α,19-triol(10),(-)-loliolide(11),cyclohexenone(12),pubinernoid A(13),quercetin-3-O-(4″-methoxy)-α-L-rahmnopyranosyl(14),5-hydroxymethyl-2-furancarboxaldehyde(15).The IC50 values of compounds 3 and 4 on K562 cells were 54.2 and 47.3 μmol/L,respectively,and the IC50 values on HEL cells were 47.3 and 61.1 μmol/L,respectively.CONCLUTION Compounds 4,7,10 and 11 are isolated from Toona genus for the first time,and compounds 2,15 are first isolated from this plant.Compounds 3 and 4 show weak antitumor activities.

Objective To study the bioequivalence and safety of two olmesartan medoxomil and hydrochlorothiazide tablets in Chinese healthy subjects.Methods A total of 24 healthy subjects underwent fasting and postprandial tests in a single-center,randomized,open-label,single-dose,two-formulation,two-sequence,two-period,self-cross-over controlled design.The subjects were administered a single oral dose of the test formulation and reference formulation(each containingolmesartan medoxomil 20 mg and hydrochlorothiazide 12.5 mg)in a random cross-over fashion.The plasma concentrations of olmesartan and hydrochlorothiazide were determined by LC-MS/MS.The non-compartmental model analysis of olmesartan and hydrochlorothiazide was conducted using WinNonlin 7.0 software to calculate pharmacokinetic parameters and assess bioequivalence.Results In the fasting test,the pharmacokinetic parameters of olmesartan of test and reference were as follows:Cmax were(798.35±206.78)and(664.52±168.25)ng·mL-1,AUC0-t were(4 430.71±1 294.87)and(3 976.67±1 083.54)h·ng·mL-1,AUC0-∞ were(4 551.67±1 303.06)and(4 090.37±1 103.97)h·ng·mL-1.The pharmacokinetic parameters of hydrochlorothiazide of test and reference were as follows:Cmax were(92.39±35.96)and(96.15±38.76)ng·mL-1,AUC0_t were(548.69±217.11)and(564.41±208.68)h·ng·mL-1,AUC0-∞ were(603.04±228.59)and(619.26±223.27)h·ng·mL-1.In the fed test,the pharmacokinetic parameters of olmesartan of T and R were as follows:Cmax were(583.15±149.48)and(550.57±104.76)ng·mL-1,AUC0-t were(3 585.18±952.72)and(3 292.19±904.58)h·ng·mL-1,AUC0-∞ were(3 696.05±996.55)and(3 396.30±923.41)h·ng·mL-1.The pharmacokinetic parameters of hydrochlorothiazide of test and reference were as follows:Cmax were(70.30±17.88)and(74.70±21.65)ng·mL-1,AUC0-t were(476.60±119.39)and(492.91±144.81)h·ng·mL-1,AUC0-∞ were(523.37±132.67)and(535.81±151.92)h·ng·mL-1.In fasting and fed condition,the 90％confidence interval(90％CI)of Cmax,AUC0-t and AUC0-∞ of olmesartan and hydrochlorothiazide were in 80.00％-125.00％.Conclusion The two olmesartan medoxomil and hydrochlorothiazide tablets were bioequivalent under fasting and fed conditions,and good security.

Objective To construct a prognostic model for liver hepatocellular carcinoma(LIHC)based on immune-related genes.Methods LIHC and normal tissue samples were downloaded from the UCSC Xena database and The Cancer Genome Atlas(TCGA)database.Differential analysis was performed on the gene data of LIHC samples and adjacent/normal samples.Enrichment analysis was conducted on differentially expressed genes.Kaplan-Meier survival analysis was performed on liver cancer samples from the TCGA cohort to obtain survival-and immune-related differentially expressed genes.LASSO Cox and multivariate Cox regression analysis were used to identify hub genes and construct a gene risk prognostic model.Data from a high-throughput gene expression(GEO)database was obtained for external validation.The sensitivity of hub genes to common anticancer drugs was investigated using the CellMiner database.Results Enrichment analysis result indicated that differentially expressed genes were mainly associated with metabolic pathways.Through differential analysis and Kaplan-Meier survival analysis,25 survival-and immune-related differentially expressed genes were obtained.Based on the result of LASSO Cox and multivariate Cox regression analysis,five hub genes(FYN,CSF3R,HLA-G,FOS,BIRC5)were identified and a nomogram was constructed.The concordance index(C-index)value for the training cohort and validation cohort were 0.739 and 0.625,respectively.Based on the sensitivity of hub genes to anticancer drugs,12 types of anticancer drugs were selected for subsequent experiments.Conclusion This model can effectively predict the prognosis of LIHC patients and provide a new insights for immune therapy in LIHC.

This study collected epidemic data of COVID-19 in Zhengzhou from January 1 to January 20 in 2022. The epidemiological characteristics of the local epidemic in Zhengzhou High-tech Zone caused by the SARS-CoV-2 Delta variant were analyzed through epidemiological survey and big data analysis, which could provide a scientific basis for the prevention and control of the Delta variant. In detail, a total of 276 close contacts and 599 secondary close contacts were found in this study. The attack rate of close contacts and secondary close contacts was 5.43% (15/276) and 0.17% (1/599), respectively. There were 10 confirmed cases associated with the chain of transmission. Among them, the attack rates in close contacts of the first, second, third, fourth and fifth generation cases were 20.00% (5/25), 17.86% (5/28), 0.72% (1/139) and 14.81% (4/27), 0 (0/57), respectively. The attack rates in close contacts after sharing rooms/beds, having meals, having neighbor contacts, sharing vehicles with the patients, having same space contacts, and having work contacts were 26.67%, 9.10%, 8.33%, 4.55%, 1.43%, and 0 respectively. Collectively, the local epidemic situation in Zhengzhou High-tech Zone has an obvious family cluster. Prevention and control work should focus on decreasing family clusters of cases and community transmission.
Humans ; SARS-CoV-2 ; COVID-19 ; Epidemics ; Incidence

Objective:To explore the current status of surgery for portal hypertension to grasp current status and future development of surgery in China.Methods:This study is jointly sponsored by China Hepatobiliary & Pancreatic Specialist Alliance & Portal Hypertension Alliance in China (CHESS).Comprehensive surveying is conducted for basic domestic situations of surgery for portal hypertension, including case load, surgical approaches, management of postoperative complications, primary effects, existing confusion and obstacles, liver transplantation(LT), laparoscopic procedures and transjugular intrahepatic portosystemic shunt(TIPS), etc.Results:A total of 8 512 cases of portal hypertension surgery are performed at 378 hospitals nationwide in 2021.Splenectomy plus devascularization predominated(53.0%)and laparoscopy accounted for 76.1%.Primary goal is preventing rebleeding(67.0%) and 72.8% of hospitals used preventive anticoagulants after conventional surgery.And 80.7% of teams believe that the formation of postoperative portal vein thrombosis is a surgical dilemma and 65.3% of hospitals practiced both laparoscopy and TIPS.The major reasons for patients with portal hypertension not receiving LT are due to a lack of qualifications for LT(69.3%)and economic factors(69.0%).Conclusions:Surgery is an integral part of management of portal hypertension in China.However, it is imperative to further standardize the grasp of surgical indications, the handling of surgical operation and the management of postoperative complications.Moreover, prospective, multi-center randomized controlled clinical studies should be performed.

Objective:To evaluate the hemostatic effects of our self-designed pelvic band with inflatable balloon in a swine model of hemodynamically unstable pelvic fracture.Methods:"Open-book like" fractures were created with the external iliac blood vessels exposed in 24 12-month-old female Bama miniature pigs which were randomly divided into 4 groups ( n=6). Group C (the control group) was subjected to no treatment other than exposure of the external iliac blood vessels, group D to no treatment following destruction of the external iliac blood vessels, group T1 to fixation with simple pelvic band after destruction of the external iliac blood vessels, and group T2 to fixation with our self-designed pelvic band with inflatable balloon after destruction of the external iliac blood vessels. The 4 groups were compared in terms of 40-min survival rate, bladder pressure, peak lactate value, total blood loss, bleeding rate, infusion rate, and angiographic images. Results:There was no significant difference in the baseline indexes among the 4 groups before experiment, showing comparability ( P>0.05). The 40-min survival rate in group T2 was 83.3% (5/6), significantly higher than that in groups D and T1 [0% (0/6) and 0% (0/6)] ( P<0.05). There were no significant differences among groups C, D, T1 and T2 in bladder pressure [(6.67±1.03) mmHg, (5.83±1.94) mmHg, (6.00±1.55) mmHg, and (6.00±1.10) mmHg] or in total blood loss among groups D, T1 and T2[(1,198.0±182.9) mL, (1,252.0±148.4) mL, and (1,150.0±125.7) mL] (all P>0.05). The peak lactate value in group T2 [(2.26±0.24) mmol/L] was significantly lower than that in group D [(5.00±0.60) mmol/L] and group T1 [(3.86±0.57) mmol/L], and the bleeding rate and infusion rate in group T2 [(25.83±5.49) mL/min and (26.00±4.69) mL/min] were also significantly lower than those in group D [(83.50±19.85) mL/min and (71.50±29.11) mL/min] and group T1 [(54.17±15.59) mL/min and (54.17±8.98) mL/min] (all P<0.05). Angiography showed contrast agent extravasation in group T2, especially from the artery, but the extravasation speed in group T2 was significantly slower than that in group D. Conclusion:In a swine model of hemodynamically unstable pelvic fracture, our self-designed pelvic band with inflatable balloon has a definite hemostatic effect on vascular injury which is better than that of a simple pelvic band.