Objective To analyze the factors influencing occupational health literacy (OHL), work-related musculoskeletal disorders (WMSDs), and occupational stress in medical staff, and to investigate the potential associations between OHL and WMSDs as well as occupational stress. Methods A total of 880 medical staff members from 18 medical institutions were selected as the study subjects using a probability proportional method. Data on OHL, WMSDs, and occupational stress were investigated using the National Key Populations Occupational Health Literacy Surveillance Individual Questionnaire (including the Musculoskeletal Disorders Questionnaire and the Core Occupational Stress Scale), and the influencing factors and potential relationships were analyzed. Results The OHL level was 63.1%, the prevalence of WMSDs was 88.1%, and the detection rate of occupational stress was 24.0% in the study subjects. Multivariable logistic regression analysis showed that female medical staff had lower OHL levels than males (P<0.05). Medical staff with higher education levels and those working in higher-level medical institutions had higher OHL levels (all P<0.05). Medical staff working >40-<49 hours per week and those working ≥49 hours per week had higher OHL levels than those working ≤40 hours per week (all P<0.01). Medical staff with higher education levels or longer working hours had a higher risk of WMSDs (all P<0.05). Medical staff with lower monthly personal income, longer weekly working hours, and lower OHL levels had a higher risk of occupational stress (all P<0.05), and those working night shifts had a higher risk of occupational stress than those who did not (P<0.01). Conclusion The study participants had a relatively high level of OHL, a high prevalence of WMSDs, and a low detection rate of occupational stress. It is recommended that medical institutions effectively implement occupational health promotion and support measures to improve the OHL level of medical staff, to reduce the risk of WMSDs and occupational stress.

Objective: To investigate the influencing factors of overactive bladder (OAB) in college freshmen and the impacts of OAB on their mental health, quality of life and social interaction. Methods: An epidemiological questionnaire survey was conducted in an anonymous manner on the prevalence of OAB among 5300 freshmen aged 17 to 22 years enrolled in the 2023—2024 academic year in Xinxiang Medical University and Sanquan College of Xinxiang Medical University.The questionnaire included questions on basic information, history of urinary tract infection, constipation, smoking, history of alcohol consumption, history of coffee/strong tea drinking, history of carbonated beverage drinking, redundant prepuce, phimosis, holding urine, chronic insomnia, self-rating anxiety scale (SAS), quality of life score (QoL), and social avoidance and distress scale (SADS).The influencing factors of OAB were analyzed with multivariate logistic regression analysis.The subjects were grouped according to whether they had OAB, and the differences in SAS, QoL and SADS between the OAB group and non-OAB group were compared.The impacts of OAB on the anxiety level, quality of life, and social interaction were analyzed with multiple linear regression analysis. Results: The overall prevalence rate of OAB was 4.9% (244/5018).Multivariate logistic regression analysis showed that the history of urinary tract infection (OR=0.177), constipation (OR=0.636), smoking (OR=0.582), alcohol consumption (OR=0.685), coffee/strong tea drinking (OR=0.387), carbonated beverage drinking (OR=0.631), redundant prepuce (OR=0.673), phimosis (OR=0.311), urine holding (OR=0.593), and chronic insomnia (OR=0.256) were influencing factors for the occurrence of OAB (P＜0.05).The OAB group had higher SAS score [(41.18±6.54) vs. (38.61±6.36)], QoL score [(3.65±1.20) vs. (2.79±0.95)], social avoidance score [(6.25±1.86) vs. (5.86±1.51)], social distress score [(6.27±1.59) vs. (5.97±1.32)], and total SADS score [(12.51±2.35) vs. (11.84±2.01)] than the non-OAB group (P＜0.05).The results of multiple linear regression analysis showed that OAB could independently affect the scores of QoL, SAS, and SADS.The OAB group had higher scores of QoL, SAS, and SADS compared with the non-OAB group (P＜0.001). Conclusion: History of urinary tract infection, constipation, smoking, alcohol consumption, coffee/strong tea drinking, carbonated beverage drinking, redundant prepuce, phimosis, urine holding, and chronic insomnia are influencing factors for the occurrence of OAB in male college students.Moreover, OAB has negative impacts on their mental health, quality of life, and social interaction.

BACKGROUND: Disease-modifying therapies have been approved for the treatment of relapsing multiple sclerosis (RMS). The present study aims to examine the safety of teriflunomide in Chinese patients with RMS. METHODS: This non-randomized, multi-center, 24-week, prospective study enrolled RMS patients with variant (c.421C>A) or wild type ABCG2 who received once-daily oral teriflunomide 14 mg. The primary endpoint was the relationship between ABCG2 polymorphisms and teriflunomide exposure over 24 weeks. Safety was assessed over the 24-week treatment with teriflunomide. RESULTS: Eighty-two patients were assigned to variant ( n  = 42) and wild type groups ( n  = 40), respectively. Geometric mean and geometric standard deviation (SD) of pre-dose concentration (variant, 54.9 [38.0] μg/mL; wild type, 49.1 [32.0] μg/mL) and area under plasma concentration-time curve over a dosing interval (AUC tau ) (variant, 1731.3 [769.0] μg∙h/mL; wild type, 1564.5 [1053.0] μg∙h/mL) values at steady state were approximately similar between the two groups. Safety profile was similar and well tolerated across variant and wild type groups in terms of rates of treatment emergent adverse events (TEAE), treatment-related TEAE, grade ≥3 TEAE, and serious adverse events (AEs). No new specific safety concerns or deaths were reported in the study. CONCLUSION: ABCG2 polymorphisms did not affect the steady-state exposure of teriflunomide, suggesting a similar efficacy and safety profile between variant and wild type RMS patients. REGISTRATION NCT04410965, https://clinicaltrials.gov .
Humans ; Crotonates/adverse effects* ; Toluidines/adverse effects* ; Nitriles ; Hydroxybutyrates ; Female ; Male ; Adult ; ATP Binding Cassette Transporter, Subfamily G, Member 2/genetics* ; Middle Aged ; Multiple Sclerosis, Relapsing-Remitting/genetics* ; Prospective Studies ; Young Adult ; Neoplasm Proteins/genetics* ; East Asian People

OBJECTIVE To analyze the comprehensive intervention measures to raise the etiological submission rate for hospitalized patients before antimicrobial treatment and evaluate the effect.METHODS The hospitalized pa-tients who were treated with therapeutic antibiotics in the Affiliated Hospital of Inner Mongolia Medical University from Jan.2023 to Jun.2023 were assigned as the exploratory analysis phase,the hospitalized patients who were treated with therapeutic antibiotics from Jul.2023 to Dec.2023 were assigned as the first post-intervention phase,and the hospitalized patients who were treated with therapeutic antibiotics from Jan.2024 to Mar.2024 were as-signed as the second post-intervention phase.The related indexes for etiological submission rate before the antimi-crobial treatment were compared before and after the intervention.RESULTS After the comprehensive interven-tion,the etiological submission rate of the entire hospital before the antimicrobial treatment was increased from 28.30％to 42.22％in the first post-intervention phase and 55.86％in the second post-intervention phase.The etio-logical submission rate with respect to diagnosis of hospital-associated infection was increased from 68.34％before the intervention to 85.85％in the first post-intervention phase and 94.58％in the second post-intervention phase.The incidence of hospital-associated infection showed a slight downward trend,dropping from 1.51％to 1.27％in the first post-intervention phase and 1.11％in the second post-intervention phase.The proportion of submission of sterile samples showed a slight upward trend,which was 26.13％before the intervention,29.57％in the first post-intervention phase,28.96％in the second post-intervention phase.There were significant differences in the a-bove indexes(P＜0.05).The etiological submission rate before the combined use of key drugs was increased from 84.71％to 85.95％in the first post-intervention phase and 88.33％in the second post-intervention phase,and there was no significant difference.CONCLUSIONS The etiological submission rate of the hospitalized patients be-fore the antimicrobial treatment is remarkably raised by taking the comprehensive intervention measures,but the etiological submission rate before the combined use of key drugs does not meet the standard,the proportion of submission of the sterile samples is not remarkably raised.It is necessary to continuously complete the intervention measures in the next phase.

Objective:To investigate the influence of continuous infusion with long time on infusion precision of infusion pump,and establish a predictive model for flow velocity to predict the change of flow velocity of infusion pump after infusion with long time,so as to provide reference for the use of infusion pump in clinical treatment.Methods:Six infusion sets of different models,numbered A to F,were selected.A 24-hour continuous infusion experiment was conducted using an infusion pump with the above six infusion sets.The flow rate of the infusion pump was set to 100 mL/h,and real-time data of the infusion speed was recorded to evaluate the performance changes of the infusion pump under long-term continuous infusion.A flow rate prediction model for the infusion pump was established based on the research data,and the accuracy of the model was verified.Results:After 24 hours of continuous infusion,the infusion accuracy of infusion sets A to F showed varying degrees of decline over time.The final infusion accuracies were 96.47%,97.95%,92.56%,88.41%,89.26%,93.93%,respectively,with corresponding flow rate errors of 3.53%,2.05%,7.44%,11.59%,10.74%,6.07%.The prediction model established in this study was used to predict the flow rate of the infusion pump during 24-36 hours of continuous infusion.Compared with the actual flow rate under the same conditions,the difference was not statistically significant(P>0.05).Conclusion:Long-term continuous infusion affects the infusion accuracy of the infusion pump,resulting in a decrease in infusion speed.The established flow rate prediction model can accurately predict the flow rate of the infusion pump after long-term continuous infusion,providing a useful reference for the clinical application of infusion pumps.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To explore the association between long working hours, anxiety symptoms, and insomnia symptoms among footwear industry workers, and to examine the mediating effect of anxiety symptoms between long working hours and insomnia symptoms. Methods A total of 710 workers from 15 footwear manufacturing enterprises in Guangdong Province were selected as study subjects using a stratified random sampling method. Long working hours, anxiety symptoms, and insomnia symptoms among the workers were assessed using the National Key Population Occupational Health Literacy Monitoring Questionnaire, the Chinese version of the Generalized Anxiety Disorder Self-Rating Scale, and the Self-Rating Sleep Questionnaire. Binary logistic regression was applied to analyze the associations of long working hours and anxiety symptoms with insomnia symptoms, and a mediation effect model was used to examine the mediating role of anxiety symptoms. Results The workers with long working hours accounted for 69.6% of participants. The detection rates of anxiety symptoms and insomnia symptoms were 17.0% and 20.7% in these workers, respectively. Binary logistic regression analysis showed that both long working hours and anxiety symptoms were influencing factors for insomnia symptoms (both P<0.01). Mediation analysis indicated that long working hours had a direct effect on insomnia symptoms, accounting for 67.9% of the total effect. Anxietysymptoms played a partial mediating role between long working hours and insomnia symptoms, with an effect value of 0.18 (95% confidence interval 0.07-0.30, P<0.01), accounting for 32.1% of the total effect. Conclusion Both long working hours and anxiety symptoms are influencing factors for insomnia symptoms among the footwear industry workers, and anxiety symptoms partially mediate the impact of long working hours on insomnia symptoms.

Objective To provide theoretical basis for the clinical application of the rational compatibility of C. odorata by studying the related domestic and international literature and explore the properties of C. odorata according to the theory of Traditional Chinese Medicine. Methods The medical literature related to C. odorata was retrieved and screened from CNKI, VIP, Wanfang Data, China Biomedical Literature Database and foreign literature databases such as PubMed, Web of Science, Scopus, Embase, and SciFinder. A total of 397 English articles and 50 Chinese articles were included in the study, which were systematically classified according to clinical application, chemical composition, pharmacological effect, toxic and side effects, and were analyzed according to the theory of Traditional Chinese Medicine. Results C. odorata features spicy, astringent tastes, a cool nature, entering heart and liver meridians, and a slightly toxic.Its functions included astringing to stop bleeding, detoxifying and promoting tissue regeneration, as well as intercepting malaria and killing parasites. It was used for conditions such as hematemesis, haemoptysis, traumatic bleeding, sores and abscesses, malaria, and leech bites. Conclusion The exploration of the properties and efficacy of C. odorata could provide reference for its clinical research and application in Traditional Chinese Medicine.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.