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Abstract Background Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts as a major contributor to cardiovascular diseases. Advancements in lipidomics and metabolomics have unveiled the complex role of fatty acid metabolism (FAM) in both healthy and pathological states. However, the specific roles of fatty acid metabolism-related genes (FAMGs) in shaping therapeutic approaches, especially in AS, remain largely unexplored and are a subject of ongoing research. Methods This study employed advanced bioinformatics techniques to identify and validate FAMGs associated with AS. We conducted differential expression analysis on a select list of 49 candidate FAMGs. GSEA and GSVA were utilized to elucidate the potential biological roles and pathways of these FAMGs. Subsequently, Lasso regression and SVM-RFE were applied to identify key hub genes and assess the diagnostic efficacy of seven FAMGs in distinguishing AS. The study also explored the correlation between these hub FAMGs and clinical features of AS. Validation of the expression levels of the seven FAMGs was performed using datasets GSE43292 and GSE9820. Results The study pinpointed seven FAMGs with a close association to AS: ACSBG2, ELOVL4, ACSL3, CPT2, ALDH2, HSD17B10, and CPT1B. Analysis of their biological functions underscored their significant involvement in critical processes such as fatty acid metabolism, small molecule catabolism, and nucleoside bisphosphate metabolism. The diagnostic potential of these seven FAMGs in AS differentiation showed promising results. Conclusions This research has successfully identified seven key FAMGs implicated in AS, offering novel insights into the pathophysiology of the disease. These findings not only contribute to our understanding of AS but also present potential biomarkers for the disease, opening avenues for more effective monitoring and progression tracking of AS.

Abstract Background Asthma, a prevalent chronic inflammatory disorder, is shaped by a multifaceted interplay between genetic susceptibilities and environmental exposures. Despite strides in deciphering its pathophysiological landscape, the intricate molecular underpinnings of asthma remain elusive. The focus has increasingly shifted toward the metabolic aberrations accompanying asthma, particularly within the domain of pyrimidine metabolism (PyM)—a critical pathway in nucleotide synthesis and degradation. While the therapeutic relevance of PyM has been recognized across various diseases, its specific contributions to asthma pathology are yet underexplored. This study employs sophisticated bioinformatics approaches to delineate and confirm the involvement of PyM genes (PyMGs) in asthma, aiming to bridge this significant gap in knowledge. Methods Employing cutting-edge bioinformatics techniques, this research aimed to elucidate the role of PyMGs in asthma. We conducted a detailed examination of 31 PyMGs to assess their differential expression. Through Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA), we explored the biological functions and pathways linked to these genes. We utilized Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) to pinpoint critical hub genes and to ascertain the diagnostic accuracy of eight PyMGs in distinguishing asthma, complemented by an extensive correlation study with the clinical features of the disease. Validation of the gene expressions was performed using datasets GSE76262 and GSE147878. Results Our analyses revealed that eleven PyMGs—DHODH, UMPS, NME7, NME1, POLR2B, POLR3B, POLR1C, POLE, ENPP3, RRM2B, TK2—are significantly associated with asthma. These genes play crucial roles in essential biological processes such as RNA splicing, anatomical structure maintenance, and metabolic processes involving purine compounds. Conclusions This investigation identifies eleven PyMGs at the core of asthma's pathogenesis, establishing them as potential biomarkers for this disease. Our findings enhance the understanding of asthma’s molecular mechanisms and open new avenues for improving diagnostics, monitoring, and progression evaluation. By providing new insights into non-cancerous pathologies, our work introduces a novel perspective and sets the stage for further studies in this field.

Abstract Background Effective interprofessional teamwork is essential for the efficiency, safety and quality of healthcare system services and requires interprofessional education for medical students. Physical education is a simple and easy way to teach teamwork, which translates into team performance in the work environment. This study was conducted to examine the effectiveness of the physical education competition model, instead of the exams model, for improving teamwork skills among medical students. Methods A quasiexperimental intervention design was used to measure the effect of a 16-week cheerleading programme on subjects' teamwork skills by completing a teamwork scale comprising four subdimensions, namely, personal characteristics, teamwork, leadership, and conflict management, before the start and at the end of the programme, and by comparing nonwinning to winning students to measure the effect of teamwork skills on team performance. Results A total of 179 students completed the valid baseline and posttest (effective rate = 95.21%). The teamwork scale scores (B M = 4.81, R M = 5.05, p < 0.001) and 4 subdimension scores (personal characteristics p = 0.002, teamwork p = 0.028, leadership p < 0.001, conflict management p < 0.001) were statistically significant. Twenty-two of the 44 items in the scale improved significantly. The differences between students who won the competition and those who did not (N M=4.86, W M=5.14, p

Abstract Background This study delves into the intricate landscape of atherosclerosis (AS), a chronic inflammatory disorder with significant implications for cardiovascular health. AS poses a considerable burden on global healthcare systems, elevating both mortality and morbidity rates. The pathological underpinnings of AS involve a marked metabolic disequilibrium, particularly within pyrimidine metabolism (PyM), a crucial enzymatic network central to nucleotide synthesis and degradation. While the therapeutic relevance of pyrimidine metabolism in diverse diseases is acknowledged, the explicit role of pyrimidine metabolism genes (PyMGs) in the context of AS remains elusive. Utilizing bioinformatics methodologies, this investigation aims to reveal and substantiate PyMGs intricately linked with AS. Methods A set of 41 candidate PyMGs was scrutinized through differential expression analysis. GSEA and GSVA were employed to illuminate potential biological pathways and functions associated with the identified PyMGs. Simultaneously, Lasso regression and SVM-RFE were utilized to distill core genes and assess the diagnostic potential of four quintessential PyMGs (CMPK1, CMPK2, NT5C2, RRM1) in discriminating AS. The relationship between key PyMGs and clinical presentations was also explored. Validation of the expression levels of the four PyMGs was performed using the GSE43292 and GSE9820 datasets. Results This investigation identified four PyMGs, with NT5C2 and RRM1 emerging as key players, intricately linked to AS pathogenesis. Functional analysis underscored their critical involvement in metabolic processes, including pyrimidine-containing compound metabolism and nucleotide biosynthesis. Diagnostic evaluation of these PyMGs in distinguishing AS showcased promising results. Conclusion In conclusion, this exploration has illuminated a constellation of four PyMGs with a potential nexus to AS pathogenesis. These findings unveil emerging biomarkers, paving the way for novel approaches to disease monitoring and progression, and providing new avenues for therapeutic intervention in the realm of atherosclerosis.

Abstract Background Acute postoperative pain remains a major clinical problem that affects patient recovery. Distal acupoint and peri-incisional stimulation are both used for relieving acute postoperative pain in hospital. Our objective was to assess and compare the effects of distal and peri-incisional stimulation on postoperative pain in open abdominal surgery. Methods MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Chinese databases CNKI and Wanfangdata were searched to identify eligible randomized controlled trials. Intensity of postoperative pain, opioid consumption and related data were extracted and analyzed using a random effects model. Risk of bias was assessed. Subgroup analyses were conducted when data were enough. Results Thirty-five trials were included, in which 17 trials studied distal stimulation, another 17 trials studied peri-incisional stimulation and one studied the combination of the two approaches. No studies that directly compared the two approaches were identified. Subgroup analysis showed that both distal and peri-incisional stimulation significantly alleviated postoperative resting and movement pain from 4 h to 48 h after surgery by 6 to 25 mm on a 100 mm visual analogue scale. Peri-incisional stimulation showed a better reduction in postoperative opioid consumption. No studies compared the effects of the combined peri-incisional and distal stimulation with either mode alone. Overall the quality of evidence was moderate due to a lack of blinding in some studies, and unclear risk of allocation concealment. Conclusion Both distal and peri-incisional modes of stimulation were effective in reducing postoperative pain. Whether a combined peri-incisional stimulation and distal acupuncture has superior results requires further studies.