16687 research outputs found
Sort by
بررسی عوامل موثر بر مصرف میوه و سبزی در بیماران دیابتی شهرستان سیرجان بر اساس مدل ارتقای سلامت پندر در سال ۱۳۹۹
Get PDFفرمولاسیون و بررسی خصوصیات فیزیکوشیمیایی دهانشویه نانوامولسیون عصاره شنبلیله (Trigonella foenum-gaecum L) و بره موم (Propolis) جهت فلورایدتراپی
Get PDFبررسی شیوع عوارض پوستی متعاقب شیمی درمانی در بیماران مراجعه کننده به کلینیک جواد الائمه و بیمارستان باهنر کرمان
Get PDFEffectiveness of Wet Cupping on Patients with Facial Acne Vulgaris: a 12-week, Randomized, Single-blind, Intervention-sham-controlled Trial
Get PDF
بررسی میزان رعایت و ضرورت بهکارگیری تکنیکهای اعتبار دادهها در قسمت پذیرش سیستمهای اطلاعات بیمارستانی در بیمارستان های آموزشی شهر کرمان
Get PDFRepurposing novel therapeutic candidate drugs for coronavirus disease-19 based on protein-protein interaction network analysis
No full textBackground: The coronavirus disease-19 (COVID-19) emerged in Wuhan, China and rapidly spread worldwide. Researchers are trying to find a way to treat this disease as soon as possible. The present study aimed to identify the genes involved in COVID-19 and find a new drug target therapy. Currently, there are no effective drugs targeting SARS-CoV-2, and meanwhile, drug discovery approaches are time-consuming and costly. To address this challenge, this study utilized a network-based drug repurposing strategy to rapidly identify potential drugs targeting SARS-CoV-2. To this end, seven potential drugs were proposed for COVID-19 treatment using protein-protein interaction (PPI) network analysis. First, 524 proteins in humans that have interaction with the SARS-CoV-2 virus were collected, and then the PPI network was reconstructed for these collected proteins. Next, the target miRNAs of the mentioned module genes were separately obtained from the miRWalk 2.0 database because of the important role of miRNAs in biological processes and were reported as an important clue for future analysis. Finally, the list of the drugs targeting module genes was obtained from the DGIDb database, and the drug-gene network was separately reconstructed for the obtained protein modules. Results: Based on the network analysis of the PPI network, seven clusters of proteins were specified as the complexes of proteins which are more associated with the SARS-CoV-2 virus. Moreover, seven therapeutic candidate drugs were identified to control gene regulation in COVID-19. PACLITAXEL, as the most potent therapeutic candidate drug and previously mentioned as a therapy for COVID-19, had four gene targets in two different modules. The other six candidate drugs, namely, BORTEZOMIB, CARBOPLATIN, CRIZOTINIB, CYTARABINE, DAUNORUBICIN, and VORINOSTAT, some of which were previously discovered to be efficient against COVID-19, had three gene targets in different modules. Eventually, CARBOPLATIN, CRIZOTINIB, and CYTARABINE drugs were found as novel potential drugs to be investigated as a therapy for COVID-19. Conclusions: Our computational strategy for predicting repurposable candidate drugs against COVID-19 provides efficacious and rapid results for therapeutic purposes. However, further experimental analysis and testing such as clinical applicability, toxicity, and experimental validations are required to reach a more accurate and improved treatment. Our proposed complexes of proteins and associated miRNAs, along with discovered candidate drugs might be a starting point for further analysis by other researchers in this urgency of the COVID-19 pandemic. © 2021, The Author(s)
Is the sharp increasing trend of multiple sclerosis incidence real in Iran?
No full textBackground: Some epidemiologic studies have reported a sharp increase in multiple sclerosis (MS) incidence in different provinces in Iran. This report aimed to investigate more closely the increasing trend of MS incidence in the past 10 years in Iran. Methods: In this longitudinal study, the data for all MS patients meeting the McDonald criteria were obtained from a national registry, coordinated by the Ministry of Health (MOH). Joinpoint (JP) regression was used for time trend analysis of MS incidence and determine the optimal number of significant joinpoints. Finally, an annual percentage change (APC) in MS incidence for each segment of the trend line was estimated with 95 confidence interval. Results: The mean age of the patients and the mean annual incidence rate of MS were 30.9 ± 1.1 and 5.3 ± 1.9 per 100,000 population, respectively. The overall incidence rate of MS had increased significantly from 2.14 in 2006 to its peak (7.5) in 2014, per 100,000 population (APC = 12, P < 0.001). The first JP was observed in 2011 in both male and female groups. The overall APC in the first segment was 22.6 (17.2�28.2, p < 0.01). Besides, the corresponding APC values for males and females were 22.1 (14.7�30, p < 0.01) and 22.5 (17.5�27.8, p < 0.01), respectively. After 2011, the MS incidence underwent a more or less decreasing trend in both genders. Conclusion: Contrary to previous studies, the MS incidence trend in Iran was rising just before 2011, and in the recent decade, Iran has a stable rate of MS cases. © 2021, The Author(s)