Shahid Beheshti University of Medical Sciences and Health Services

About: Shahid Beheshti University of Medical Sciences and Health Services is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Population & Medicine. The organization has 19456 authors who have published 33659 publications receiving 365676 citations.

Noninvasive Fuhrman grading of clear cell renal cell carcinoma using computed tomography radiomic features and machine learning

Abstract: To identify optimal classification methods for computed tomography (CT) radiomics-based preoperative prediction of clear cell renal cell carcinoma (ccRCC) grade. Seventy-one ccRCC patients (31 low grade and 40 high grade) were included in this study. Tumors were manually segmented on CT images followed by the application of three image preprocessing techniques (Laplacian of Gaussian, wavelet filter, and discretization of the intensity values) on delineated tumor volumes. Overall, 2530 radiomics features (tumor shape and size, intensity statistics, and texture) were extracted from each segmented tumor volume. Univariate analysis was performed to assess the association between each feature and the histological condition. Multivariate analysis involved the use of machine learning (ML) algorithms and the following three feature selection algorithms: the least absolute shrinkage and selection operator, Student’s t test, and minimum Redundancy Maximum Relevance. These selected features were then used to construct three classification models (SVM, random forest, and logistic regression) to discriminate high from low-grade ccRCC at nephrectomy. Lastly, multivariate model performance was evaluated on the bootstrapped validation cohort using the area under the receiver operating characteristic curve (AUC) metric. The univariate analysis demonstrated that among the different image sets, 128 bin-discretized images have statistically significant different texture parameters with a mean AUC of 0.74 ± 3 (q value < 0.05). The three ML-based classifiers showed proficient discrimination between high and low-grade ccRCC. The AUC was 0.78 for logistic regression, 0.62 for random forest, and 0.83 for the SVM model, respectively. CT radiomic features can be considered as a useful and promising noninvasive methodology for preoperative evaluation of ccRCC Fuhrman grades.

Curcumin (a constituent of turmeric): New treatment option against COVID-19

Abstract: In late December 2019, the outbreak of respiratory illness emerged in Wuhan, China, and spreads worldwide. World Health Organization (WHO) named this disease severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused by a new member of beta coronaviruses. Several medications are prescribed to patients, and some clinical trials are underway. Scientists are trying to find a specific drug against this virus. In this review, we summarize the pathogenesis, clinical features, and current treatments of coronavirus disease 2019 (COVID-19). Then, we describe the possible therapeutic effects of curcumin and its molecular mechanism against coronavirus-19. Curcumin, as an active constituent of Curcuma longa (turmeric), has been studied in several experimental and clinical trial studies. Curcumin has some useful clinical effects such as antiviral, antinociceptive, anti-inflammatory, antipyretic, and antifatigue effects that could be effective to manage the symptoms of the infected patient with COVID-19. It has several molecular mechanisms including antioxidant, antiapoptotic, and antifibrotic properties with inhibitory effects on Toll-like receptors, NF-κB, inflammatory cytokines and chemokines, and bradykinin. Scientific evidence suggests that curcumin could have a potential role to treat COVID-19. Thus, the use of curcumin in the clinical trial, as a new treatment option, should be considered.

Mental health in the Islamic Republic of Iran: achievements and areas of need.

Abstract: The development of mental health in the Islamic Republic of Iran is described with particular reference to the integration mental health into the primary health care system. The achievements made so far are outlined and the areas of need discussed.

A case of possible atypical demyelinating event of the central nervous system following COVID-19.

Abstract: After the novel coronavirus disease outbreak first began in Wuhan, China, in December 2019, the viral epidemic has quickly spread across the world, and it is now a major public health concern Here we present a 21-year-old male with encephalomyelitis following intermittent vomiting and malaise for 4 days He reported upper respiratory signs and symptoms 2 weeks before this presentation Two cerebrospinal fluid (CSF) analyses were notable for mononuclear pleocytosis, elevated protein (more than 100 mg/dl), and hypoglycorrhachia Brain Magnetic Resonance Imaging (MRI) showed bilateral posterior internal capsule lesions extending to the ventral portion of the pons and a marbled splenium hyperintensity pattern Cervical and thoracic MRI showed longitudinally extensive transverse myelitis (LETM), none of which were enhanced with gadolinium Both the AQP4 and MOG antibodies were negative Spiral chest computed tomography (CT) scan confirmed to COVID-19 as did the high IgG level against coronavirus, but the oropharyngeal swabs were negative Neurological manifestations of COVID-19 have not been adequately studied Some COVID-19 patients, especially those suffering from a severe disease, are highly likely to have central nervous system (CNS) manifestations Our case is a post-COVID-19 demyelinating event in the CNS