Objective: To investigate and analyze the IgM/IgG antibody titer levels and population characteristics of local type O blood donors, and to provide data support for the establishment of a low-titer group O blood donor bank. Methods: Whole blood samples were collected from 527 type O blood donors. The agglutination of IgM and IgG anti-A/anti-B antibodies at titers 64 and 128 was assessed using an enzyme immunoassay reader. The distribution of antibody agglutination was displayed using GraphPad Prism 9.5. Statistical analysis was performed to compare antibody agglutination differences among donors of different genders, age groups, and donation frequencies. Results: At a titer of 64, the non-agglutination rate of IgM anti-A/anti-B was 71.35%, and that of IgG anti-A/anti-B was 54.46%. At a titer of 128, the non-agglutination rate of IgM anti-A/anti-B was 83.68%, and that of IgG anti-A/anti-B was 70.21%. At a titer of 64, the agglutination rate of IgM anti-B was significantly higher in female donors than in male donors (23.08% vs 13.71%, P<0.05). The agglutination rates of IgM anti-A/anti-B at a titer of 64 decreased with age in different age groups (anti-A: 26.22% vs 18.28% vs 8.49%; anti-B: 19.82% vs 11.83% vs 5.66%, P<0.05). The agglutination rates of IgM anti-A/anti-B at a titer of 64 were both higher in first-time donors than in repeat donors (anti-A: 24.00% vs 15.82%; anti-B: 18.00% vs 10.73%, P<0.05). The agglutination rate of IgG anti-A at a titer of 128 was higher in first-time donors than in repeat donors (26.57% vs 6.21%, P<0.05). Conclusion: The establishment of a low-titer type O whole blood donor bank should primarily target males, donors aged>30 years and repeat donors, with both IgM and IgG antibodies included in the antibody testing scope.

The elevated polyamines, amine-rich molecules with diverse functions in pathophysiology processes, are implicated in contributing to tumorigenesis and progression. Whether and how they affect the efficacy of chemotherapy is incompletely understood. Our screening assays reveal that the supplement with a low dose of spermidine (Spd), one of the polyamines, enhances ferroptosis in prostate cancer cells as evidenced by increased lipid peroxidation and intracellular Fe²⁺ levels in vitro. Combination treatment with Spd and a low dose of ferroptosis inducer erastin synergistically augments anti-tumor efficacy with undetectable toxicity in mice. Analysis of RNA-seq data indicates that heme oxygenase 1 (HMOX1), an enzyme that catalyzes the cleavage of heme to release Fe²⁺, is significantly upregulated in response to Spd and erastin cotreatment. Spd mediated the hypusine modification of the eukaryotic initiation factor 5A (EIF5A) promotes the translation of the nuclear factor erythroid 2-related factor 2 (NRF2), subsequently leading to elevation of HMOX1. Moreover, Spd and erastin significantly inhibit proteasome activity which results in a decrease in proteasomal degradation of NRF2, although many proteasome-related genes are induced either by Spd or Spd plus erastin. Thus, in addition to its pro-oncogenic activity, the supplement of Spd improves antitumor activity in combination with ferroptosis inducers and offers an optional approach to cancer treatment.

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.

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.

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 current status of occupational health literacy (OHL) among front-line workers in the metal products industry and to explore its influencing factors. Methods A total of 5 193 front-line workers from the metal products industry in 14 prefecture-level cities in Guangdong Province were selected as the research subjects by the stratified cluster random sampling method. The Occupational Health Literacy Questionnaire of National Key Populations was used to assess their OHL levels. To analyze the influencing factors of OHL, binary logistic regression analysis was conducted. Results The overall OHL level among the participants was 40.0% (2 079/5 193). The result of binary logistic regression analysis showed that workers with lower educational level, lower average monthly personal income, and smaller enterprise size had lower OHL levels (all P<0.01). In addition, workers in foreign-funded enterprises had higher OHL levels than those in private enterprises (P<0.01). Conclusion There remains considerable room for improvement in OHL among front-line workers in the metal products industry. Priority focus is to improve OHL among workers with lower education and income levels, as well as those employed in private and micro- or small-sized enterprises.

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.

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.