Search

Abstract Background Sleep disorders can be harmful to our health and treating them can also be expensive. Due to the widespread occurrence and impact of sleep disorders, it is valuable to investigate and study them from an epidemiological perspective. Therefore, this study aimed to determine the prevalence of sleep disorders among Iranian adults in 2022. Method This is a cross-sectional study that examines the prevalence of sleep disorders and problems in Iranian society. The participants were selected using a mixed sampling approach (utilizing virtual space and cluster sampling). A two-part package was used for evaluating participants sleep problems, which included a demographic profile form and the Holland Sleep Disorders Questionnaire. After collecting the data, appropriate statistical tests in SPSS version 25 were utilized for analysis. Results A total of 6013 questionnaires were fully filled out for this research, with participants answering the specific questions. The participants’ score on sleep disorders was 1.94, which means 44.1% of them suffer from sleep disorders. The results indicated that the prevalence of sleep disorders in this study was as follows: insomnia (35%), parasomnia (35.3%), circadian rhythm sleep disorder (38.4%), hypersomnia and excessive daytime sleepiness (39%), restless leg syndrome and leg movements during sleep (43%), and breathing disorders related to sleep (38.4%). The prevalence of sleep disorders among the study participants demonstrated a significant relationship with most of their demographic variables (P

Abstract Background Integration of artificial intelligence enhances precision, yielding dependable evaluations of left ventricular volumes and ejection fraction despite image quality variations. Commercial software like HeartModelAI provides fully automated 3DE quantification, simplifying the measurement of left chamber volumes and ejection fraction. In this manuscript, we present a cross-sectional study to assess and compare the diagnostic accuracy of automated 3D echocardiography (HeartModelAI) to the standard Cardiac Magnetic Resonance Imaging in patients with dilated cardiomyopathy. Methods In this cross-sectional study, 30 patients with dilated cardiomyopathy referring to the Tehran Heart Center with cardiac magnetic resonance imaging and comprehensive 3D transthoracic echocardiography within 24 h were included. All 3D volume analysis was performed with fully automated quantification software (HeartModelAI) using 3D images of 2,3, and 4-chamber views at the end of systole and diastole. Results Excellent Inter- and Intra-observer correlation coefficient was reported for HeartModelAI software for all indexes. HeartModelAI displayed a remarkable correlation with cardiac magnetic resonance for left ventricular end-systolic volume index (r = 0.918 and r = 0.911); nevertheless, it underestimated left ventricular end-systolic volume index and left ventricular end-diastolic volume index. Conversely, ejection fraction, stroke volume, and left ventricular mass were overestimated. It was found that manual contour correction can enhance the accuracy of automated model estimations, particularly concerning EF in participants needing correction. Conclusion HeartModelAI software emerges as a rapid and viable imaging approach for evaluating the left ventricle’s structure and function. In our study, LV volumes assessed by HeartModelAI demonstrated strong correlations with cardiac magnetic resonance imaging.

Abstract Background Crimean-Congo haemorrhagic fever (CCHF) is a lethal acute viral zoonosis with a case fatality rate of 5–50%. Due to the potential of human-to human transmission of the disease, healthcare workers (HCWs) are at risk of occupational exposure to CCHF virus. Little is known about CCHF virus route of transmission and risks in Iranian HCWs. Therefore this study was designed to identify the routes of exposure to the CCHF virus among Iranian HCWs. Methods From Oct 2000 to Feb 2023, 96 CCHF suspected healthcare workers referred to national reference laboratory were tested for CCHF virus infection by the use of RT-PCR and IgM Capture Enzyme-Linked Immunosorbent Assay (MAC-ELISA) and exposure history of cases were investigated to determine the CCHF virus routes of transmission in nosocomial settings. Results Twelve CCHF confirmed cases were identified including seven nurses and five physicians, with the median age of 32.5 years (range 23–53 years) and the median incubation period of 6.8 days (range from 1 to 22 days). None of the cases reported a history of tick bite or close contact with tissues or animal blood. The cases were from Razavi Khorasan (seven cases), Sistan and Baluchistan (two cases), Isfahan (one case), South Khorasan (one case) and Fars (one case). Percutaneous exposure (needle stick) (three cases), mucosal exposure (blood splash in to face) (three cases) and skin contact with blood (three cases) constituted the most prevalent routes of transmission. Since 2013, no CCHF cases have been identified among Iranian HCWs. Conclusions In healthcare settings, physicians and nurses are at risk of nosocomial CCHF virus infection. The routes of transmission mainly include direct exposures via needle-stick, mucosal or direct contact with the skin to infected blood. Continuous education and implementation of infection prevention and control measures are key factors to minimize the incidence of healthcare related CCHF.

Abstract Endocrine fibroblast growth factors (eFGFs) play essential roles in cellular signaling processes, including development and differentiation, and are implicated in various cancers. However, their precise involvement in colon neoplasia and colon adenocarcinoma (COAD) remains incompletely understood. Here, we conducted a comprehensive investigation utilizing multiple databases to explore the multifaceted characteristics of eFGFs. Through integrated analyses of diverse databases, including TIMER2.0, UALCAN, OncoDB, cBioPortal, LinkedOmics, STRING, htfTarget, mirTarBase, circBank, and DGIdb, we explored eFGFs’ gene expression, DNA methylation, prognostic significance, genetic alterations, gene regulatory networks, functional analysis, and drug interactions in COAD patients. Our findings revealed elevated expression levels of eFGFs in COAD, with aberrant gene expression potentially linked to promoter methylation. Importantly, hypermethylation of FGF21 and FGF23 and downregulation of FGF23 correlated with poor survival outcomes in COAD patients. Functional analyses highlighted the involvement of eFGF genes in Ras signaling, PI3K-Akt signaling, and cancer pathways. Furthermore, we validated our findings through a cross-sectional study by quantitative real-time polymerase chain reaction (qRT-PCR), confirming significant overexpression of FGF21 in colon polyps compared to normal mucosa. Additionally, we observed elevated RNA expression of FGF21 and FGF23 in adenomatous polyps compared to hyperplastic polyps. This study sheds new light on the critical roles of eFGFs in COAD tumorigenesis and underscores their potential as promising prognostic markers for COAD, as well as discriminative markers for distinguishing high-risk from low-risk polyps. These findings provide valuable insights into the complex molecular mechanisms underlying colorectal neoplasia and offer potential avenues for targeted therapeutic strategies.