Background Work-related musculoskeletal disorders (WMSDs) are a major occupational health concern, particularly among workers exposed to adverse ergonomic conditions. Manganese production involves heavy physical demands, yet research on WMSDs among manganese workers remains limited. Objective To investigate the prevalence and influencing factors of WMSDs among manganese workers in a manganese enterprise in Guangxi. Methods A cross-sectional survey was conducted from May to June 2024 on workers at a manganese factory in Guangxi. The Chinese Musculoskeletal Disorders Questionnaire was used to collect information on demographic characteristics, distribution of musculoskeletal symptoms, and work-related exposures. χ² test was applied to compare differences in positive WMSDs rates across groups, and logistic regression analysis was performed to identify associated factors. Results A total of 1476 workers were enrolled in the study after pre-determined inclusion and exclusion criteria. The overall prevalence of WMSDs was 34.15%. The most commonly affected body regions were the lower back (17.28%), neck (16.67%), and shoulders (13.82%). The results of logistic regression analysis indicated that female, older age, and education level of college or above were associated with a higher risk of WMSDs (P<0.05). Awkward working postures were significantly associated with WMSDs in corresponding body regions; in particular, awkward postures of the neck, upper limbs, trunk, and lower limbs were related to an increased risk of WMSDs in multiple body sites (P<0.05). In addition, poor lighting conditions, high workplace temperature, frequent or sustained arm support during work, and high job demands were associated with an increased risk of overall or site-specific WMSDs (P<0.05). Conclusion The high prevalence of WMSDs among manganese workers is closely associated with demographic characteristics, working postures, and work environment and organizational factors. Targeted ergonomic interventions focusing on high-risk body regions and key ergonomic exposures are warranted to reduce the risk of WMSDs among manganese workers.

ObjectiveThis study aims to compare the modeling effects of submaxillary gland antigen and salivary gland antigen in the establishment of Sjögren syndrome (SS) mouse models, and to characterize the phenotypic and immunological features of these models in comparison with spontaneous SS-prone non-obese diabetic (NOD)/LtJ mice. MethodsAdult C57BL/6J mice (equal numbers of males and females) were immunized with submaxillary gland antigen or salivary gland antigen, respectively, combined with Freund's adjuvant to induce SS models. Mice immunized with phosphate-buffered saline (PBS) combined with Freund's adjuvant served as the control group. Immunization was induced via multiple subcutaneous injections in the back with antigen combined with Freund's complete adjuvant (FCA) on Days 1 and 7. A booster immunization was administered via multiple subcutaneous injections in the back with antigen combined with Freund's incomplete adjuvant (FIA) on Day 14. Female NOD/LtJ mice were used as the spontaneous SS model group, with ICR mice as the corresponding control strain for comparative analysis. Body weight, water intake, and salivary flow rate of mice were dynamically monitored for 4 weeks. At the end of the experiment, tissue and serum samples were collected, the weights of submaxillary glands, thymus, and spleen were measured, and organ indices (organ-to-body weight ratios) were calculated. Pathological morphological analysis of the submaxillary gland and spleen was performed with hematoxylin and eosin (HE) staining. Serum interleukin-17 (IL-17) level was detected using enzyme-linked immunosorbent assay (ELISA). Real-time quantitative polymerase chain reaction was used to detect the mRNA expression levels of SS type A (SSA) and SS type B (SSB) in submaxillary gland tissues. ResultsFemale mice in the submaxillary gland antigen group exhibited significantly increased water intake (P<0.05) and reduced salivary flow rate (P<0.05) compared with the female control group. No statistically significant differences were observed in the submaxillary gland index, thymus index and spleen index (P>0.05). Focal lymphocytic infiltration was observed in the submaxillary glands, and the splenic marginal zone was enlarged. Serum IL-17 levels were significantly increased (P<0.05). There was no significant difference in submaxillary gland SSA/SSB expression levels (P>0.05). Compared with the female control group, female mice in the salivary gland antigen group showed no statistically significant differences in water intake, salivary flow rate, submaxillary gland index, and spleen index (P>0.05), whereas the thymus index was significantly reduced (P<0.01). Mild inflammatory cell infiltration and glandular atrophy were observed in the submaxillary glands, and the splenic white pulp and marginal zone were slightly enlarged. Serum IL-17 levels and submaxillary gland SSB mRNA expression levels were significantly increased (P<0.01), whereas no significant change was observed in submaxillary gland SSA expression levels (P>0.05). Compared with the male control group, mild submaxillary gland atrophy was observed in male mice in the submaxillary gland antigen group, whereas no obvious changes were found in other modeling-related indicators (P>0.05). Compared with the ICR control group, NOD/LtJ model mice exhibited elevated water intake (P<0.05), significantly reduced salivary flow rate (P<0.01), no significant differences in the submaxillary gland index or spleen index (P>0.05), but a significantly increased thymus index (P<0.05). Marked focal infiltration was observed in the submaxillary glands, the splenic marginal zone was obviously enlarged, and serum IL-17 concentrations as well as submaxillary gland SSA/SSB expression levels were significantly increased (P<0.05). ConclusionSubmaxillary gland antigen and salivary gland antigen can induce SS-related features in female C57BL/6J mice. The SS-related phenotype is more pronounced in the submaxillary gland antigen group than in the salivary gland antigen group, but weaker than that in spontaneously SS-prone female NOD/LtJ mice. Immunization of male C57BL/6J mice with submaxillary or salivary gland antigens fails to induce an obvious SS phenotype.

ObjectiveTo analyze the long-term trend of incidence and mortality of type 2 diabetic kidney disease （DKD） in China from 1990 to 2021. MethodsThe Joinpoint regression model was used to analyze the average annual percentage change （AAPC） of standardized incidence rate and standardized mortality rate， and the age-period-cohort （APC） model was constructed to analyze the longitudinal age change， period and cohort effect risk ratio （RR）. ResultsFrom 1990 to 2021， the standardized incidence rate of type 2 DKD in males and females showed an overall upward trend， with AAPC of 0.08% and 0.36%， respectively. The age-standardized mortality rate of the total population and female showed a downward trend， with AAPC of -0.61% and -1.03%， respectively. However， there was no significant difference in males. APC model showed that the age effect existed： the peak age was 75-79 years old， the mortality rate of females increased， and the mortality rate of males decreased after 80-84 years old. For the effect of time period， the risk of type 2 DKD incidence in females in 2017—2021 was 1.05 times that in 2002—2006， and the risk of death in males and females in 2017—2021 was 0.84 and 0.71 times that in 2002—2006， respectively. For cohort effects， the highest risk of disease was seen in men and women born in 1967—1971， and the highest risk of death was seen in men born in 1952—1956 and women born in 1912—1916. ConclusionFrom 1990 to 2021， the standardized incidence rate of type 2 DKD in China shows an upward trend， and the standardized mortality rate shows a downward trend. It is necessary to strengthen the health behavior publicity and education of type 2 DKD， and actively carry out early screening to reduce the disease burden.

ObjectiveTo analyze the drug resistance and the molecular typing characteristics through pulsed field gel electrophoresis (PFGE) of Campylobacter spp. isolated from patients with infectious diarrhea in Baoshan District of Shanghai, and to provide a basis for Campylobacter spp. prevention and control and clinical medication. MethodsCampylobacter spp. was isolated, cultured and identified from stool samples of diarrheal patients collected from medical institutions at two monitoring sites in Baoshan District from 2019 to 2022. Antimicrobial susceptibility testing for 12 antibiotics was conducted on the isolated Campylobacter jejuni (C. jejuni) and Campylobacter. Coli (C. coli), and molecular typing was performed using PFGE. ResultsA total of 179 strains of Campylobacter spp. were isolated from 1 786 samples of diarrheal patients, with a positive rate of 10.02%. The highest resistance rate of C. jejuni was to ciprofloxacin (98.63%), followed by tetracycline (97.26%) and nalidixic acid (89.73%). C. coli was completely resistant to ciprofloxacin and nalidixic acid (100.00%), followed by tetracycline (90.91%). The multidrug resistance rates of C. jejuni and C. coli were 89.73% and 100.00%, respectively. 142 strains of C. jejuni produced 122 PFGE bands, while 33 strains of C. coli produced 33 PFGE bands, and the distribution of the bands was relatively dispersed. ConclusionFrom 2019 to 2022, the detection rate of Campylobacter in diarrheal patients was relatively high in Baoshan District of Shanghai, the multidrug resistance rate of Campylobacter isolates from diarrheal patients was relatively serious, in addition, the drug resistance pattern was complex, and the PFGE band pattern displayed a polymorphic distribution.

OBJECTIVES: To study the epidemiological characteristics of respiratory syncytial virus (RSV) infection in hospitalized children with community-acquired pneumonia (CAP) in Hebei Province. METHODS: Hospitalized children with CAP who tested positive for RSV and were admitted to Hebei Children's Hospital from various cities and counties across Hebei Province between January 2019 and December 2023 were included in the study. Clinical data were collected and analyzed to assess epidemiological characteristics. RESULTS: The clinical data of 43 978 children with CAP were collected, with an overall RSV detection rate of 25.98%. The detection rate was higher during the implementation of non-pharmaceutical interventions (NPIs) (30.60%) than in the non-NPIs period. Winter and spring were the primary epidemic seasons for RSV each year except in 2022. The detection rate in males (26.62%) was higher than in females (25.06%) (P<0.001). The highest detection rate (59.18%) was found in infants aged 29 days to <1 year. Single RSV infection was more common, with rhinovirus being the most frequent co-infection. CONCLUSIONS The overall RSV detection rate in Hebei Province is influenced by NPIs, being higher during their implementation. RSV predominantly circulates in winter and spring. The detection rate of RSV is higher in males and infants. RSV infection is primarily single, most often co-occurring with rhinovirus.
Humans ; Respiratory Syncytial Virus Infections/epidemiology* ; Female ; Male ; Infant ; Child, Preschool ; Seasons ; China/epidemiology* ; Infant, Newborn ; Community-Acquired Infections/epidemiology* ; Child

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

OBJECTIVE: To investigate the association of various polycyclic aromatic hydrocarbon (PAH) metabolites with diverse subtypes of cardiovascular disease (CVD) risk. METHODS: A novel predicting risk of cardiovascular disease EVENTs PREVENT equation was used to estimate the 10-year diverse subtypes of CVD risk, and their associations with PAH metabolites were analyzed using multiple logistic regression models, the weighted quantile sum (WQS) model, the quantile g-computation (qgcomp) model, and a stratified analysis of subgroups. RESULTS: For this study, six thousand seven hundred and forty-five participants were selected, and significant positive associations were observed between PAHs, naphthalene (NAP), and fluorene (FLU), and the risks of total CVD, atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). NAP and FLU were the primary contributors to the effects of PAH mixtures, and their associations with total CVD, ASCVD, and HF risk were significant in younger participants (30 ≤ age < 50 years); however, the associations of phenanthrene (PHEN) with ASCVD, HF, coronary heart disease (CHD), and stroke were dominant in aging participants (age ≥ 50 years). Notably, pyrene (PYR) was negatively associated with the risk of ASCVD, HF, CHD, and stroke. Similarly, negative associations of PYR with the four CVD subtypes were noticeable in aging participants. CONCLUSION Different PAHs metabolites had different impacts on each CVD subtype among different age groups. Notably, the protective effects of PYR on ASCVD, HF, CHD, and stroke were noticeable in aging individuals.
Humans ; Cardiovascular Diseases/chemically induced* ; Middle Aged ; Polycyclic Aromatic Hydrocarbons/metabolism* ; Male ; Female ; Adult ; Aged ; Risk Factors ; China/epidemiology*

Objective To observe the value of T1WI deep learning models for evaluating brain injury of neonatal hyperbilirubinemia(NHB).Methods Totally 106 NHB(defined as newborns with neonatal behavioral neurological assessment≤37,NHB group)and 119 non-NHB newborns(control group)in center A,as well as 34 NHB and 18 non-NHB newborns in center B were collected.ROI was delineated based on bilateral globus pallidus on T1WI.A total of 690 slices were obtained by preprocessing data of center A and then were divided into training set(n=552)and test set(n=138)at a ratio of 8∶2.ResNet18,DenseNet121 and EfficientNetB0 models was established,respectively.External validation was performed based on data of center B.Receiver operating characteristic curves were drawn,area under the curves(AUC)were calculated to evaluate the performance of models for assessing NHB brain injuries compared with traditional visual analysis.Results The AUC of ResNet18 model for evaluating NHB brain injury was 0.910-0.990,significantly higher than that of DenseNet121 model(0.710-0.820)and EfficientNetB0 model(0.640-0.740)(all P＜0.001).The accuracy,sensitivity and precision of ResNet18 model for evaluating NHB brain injury were all higher than those of visual analysis(all P＜0.05),while no significant difference of specificity was found between the above two(P＞0.05).Conclusion T1WI ResNet18 model showed excellent performance and generalization ability for evaluating NHB brain injury.

Objective To compare the differences in the average transaction costs per-referral patients under different models of Integrated Delivery Systems(IDS).Methods Using a typical case sampling method,it selected referred patients from three IDS models:the county medical alliance in D City(Qinghai Province),the urban medical consortium in J District(Zhengzhou City,Henan Province),and the health management coalition in N County(Shandong Province).Structured questionnaires collected demographics,average transaction costs per-referral and cost perceptions.t-tests and ANOVA assessed cost differences;generalized linear regression identified influencing factors.Results Among 915 patients,the average transaction costs per-referral were 1 035.05 yuan(county alliance),195.31 yuan(urban consortium),and 700.97 yuan(health management coalition),with statistically significant differences(P＜0.05).The urban consortium exhibited lower time costs and specialized input costs.Key influencing factors included older age(county alliance),education level,employment status,and referral travel time(urban consortium),as well as urban-rural disparities(health management coalition).Patients'cost perceptions significantly differed across models(P＜0.05).Conclusion The urban medical consortium demonstrated the lowest patient the average transaction costs,highlighting its institutional advantage in minimizing financial burdens.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.