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Total 128 records

    A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI

    , Article Medical Physics ; Volume 47, Issue 10 , 2020 , Pages 5158-5171 Bahrami, A ; Karimian, A ; Fatemizadeh, E ; Arabi, H ; Zaidi, H ; Sharif University of Technology
    John Wiley and Sons Ltd  2020
    Abstract
    Purpose: Despite the proven utility of multiparametric magnetic resonance imaging (MRI) in radiation therapy, MRI-guided radiation treatment planning is limited by the fact that MRI does not directly provide the electron density map required for absorbed dose calculation. In this work, a new deep convolutional neural network model with efficient learning capability, suitable for applications where the number of training subjects is limited, is proposed to generate accurate synthetic computed tomography (sCT) images from MRI. Methods: This efficient convolutional neural network (eCNN) is built upon a combination of the SegNet architecture (a 13-layer encoder-decoder structure similar to the... 

    Fabrication and characterization of an injectable reinforced composite scaffold for cartilage tissue engineering: An in vitro study

    , Article Biomedical Materials (Bristol) ; Volume 16, Issue 4 , 2021 ; 17486041 (ISSN) Khozaei Ravari, M ; Mashayekhan, S ; Zarei, F ; Sayyahpour, F. A ; Taghiyar, L ; Eslaminejad, M. B ; Sharif University of Technology
    IOP Publishing Ltd  2021
    Abstract
    There are limitations in current medications of articular cartilage injuries. Although injectable bioactive hydrogels are promising options, they have decreased biomechanical performance. Researchers should consider many factors when providing solutions to overcome these challenges. In this study, we created an injectable composite hydrogel from chitosan and human acellular cartilage extracellular matrix (ECM) particles. In order to enhance its mechanical properties, we reinforced this hydrogel with microporous microspheres composed of the same materials as the structural building blocks of the scaffold. Articular cartilage from human donors was decellularized by a combination of physical,... 

    A novel metabolic disorder in the degradation pathway of endogenous methanol due to a mutation in the gene of alcohol dehydrogenase

    , Article Clinical Biochemistry ; Volume 90 , 2021 , Pages 66-72 ; 00099120 (ISSN) Razzaghy Azar, M ; Nourbakhsh, M ; Vafadar, M ; Nourbakhsh, M ; Talebi, S ; Sharifi Zarchi, A ; Salehi Siavashani, E ; Garshasbi, M ; Sharif University of Technology
    Elsevier Inc  2021
    Abstract
    Background: A small amount of methanol is produced endogenously in the human body but it is efficiently metabolized by alcohol dehydrogenase (ADH) and other enzymes, and the products eliminated without harm. In this study, we present a new entity of inborn error of methanol metabolism due to a mutation in the ADH1C gene coding for the γ subunit that is part of several ADH isoenzymes. Results: This disorder was discovered in an 11.58-year-old boy. During one 9-month hospital admission, he had periods of 1–4 days during which he was comatose, and between these periods he was sometimes verbose and euphoric, and had ataxia, dysarthria. Following hemodialysis treatments, he became conscious and... 

    Subcutaneous insulin administration by deep reinforcement learning for blood glucose level control of type-2 diabetic patients

    , Article Computers in Biology and Medicine ; Volume 148 , 2022 ; 00104825 (ISSN) Raheb, M. A ; Niazmand, V. R ; Eqra, N ; Vatankhah, R ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    Background: Type-2 diabetes mellitus is characterized by insulin resistance and impaired insulin secretion in the human body. Many endeavors have been made in terms of controlling and reducing blood glucose via the medium of automated controlling tools to increase precision and efficiency and reduce human error. Recently, reinforcement learning algorithms are proved to be powerful in the field of intelligent control, which was the motivation for the current study. Methods: For the first time, a reinforcement algorithm called normalized advantage function (NAF) algorithm has been applied as a model-free reinforcement learning method to regulate the blood glucose level of type-2 diabetic... 

    Modeling and optimization of respiratory-gated partial breast irradiation with proton beams - A Monte Carlo study

    , Article Computers in Biology and Medicine ; Volume 147 , 2022 ; 00104825 (ISSN) Piruzan, E ; Vosoughi, N ; Mahani, H ; Sharif University of Technology
    Elsevier Ltd  2022
    Abstract
    The selection of a suitable duty factor (DF) remains a major challenge in respiratory-gated treatments. Therefore, this study aims at presenting a new methodology for fast optimizing the gating window width (duty factor (DF)) in respiratory-gated proton partial breast irradiation (PBI). To do so, GATE Monte Carlo simulations were performed for various target sizes and locations in supine and prone positions. Three different duty factors of 20, 25, and 33% were considered. Sparing factors (SF) for four organs-at-risk (OARs) were then assessed. The weighted-sum method was employed to search for an optimal DF. The results indicate that an SF higher than unity was obtained for all plans. The SF... 

    Asthma induces psychiatric impairments in association with default mode and salience networks alteration: A resting-state EEG study

    , Article Respiratory Physiology and Neurobiology ; Volume 300 , 2022 ; 15699048 (ISSN) Gholami Mahtaj, L ; Salimi, M ; Nazari, M ; Tabasi, F ; Bamdad, S ; Dehdar, K ; Mikaili, M ; Mahdaviani, S. A ; Salari, F ; Lookzadeh, S ; Jamaati, H ; Salimi, A ; Raoufy, M. R ; Sharif University of Technology
    Elsevier B.V  2022
    Abstract
    Asthma is a chronic inflammatory disease associated with a high prevalence of psychiatric disorders. There are specific brain networks responsible for emotional processes, including two important networks associated with psychiatric problems: the default mode network (DMN), which is more active in the resting state, and the salience network (SN), which is structurally connected to DMN. Although previous studies suggested that neuro-phenotypes of asthma may be recognizable by the neural activity of brain circuits, an association between the brain's functional alterations and psychiatric impairments induced by asthma remains unknown. We aimed to assess DMN and SN activity and its association... 

    Genetic risk variants for class switching recombination defects in ataxia-telangiectasia patients

    , Article Journal of Clinical Immunology ; Volume 42, Issue 1 , 2022 , Pages 72-84 ; 02719142 (ISSN) Amirifar, P ; Mehrmohamadi, M ; Ranjouri, M. R ; Akrami, S. M ; Rezaei, N ; Saberi, A ; Yazdani, R ; Abolhassani, H ; Aghamohammadi, A ; Sharif University of Technology
    Springer  2022
    Abstract
    Background: Ataxia-telangiectasia (A-T) is a rare autosomal recessive disorder caused by mutations in the ataxia telangiectasia mutated (ATM) gene. A-T patients manifest considerable variability in clinical and immunological features, suggesting the presence of genetic modifying factors. A striking heterogeneity has been observed in class switching recombination (CSR) in A-T patients which cannot be explained by the severity of ATM mutations. Methods: To investigate the cause of variable CSR in A-T patients, we applied whole-exome sequencing (WES) in 20 A-T patients consisting of 10 cases with CSR defect (CSR-D) and 10 controls with normal CSR (CSR-N). Comparative analyses on modifier... 

    Perylene diimide-POSS network for semi selective solid-phase microextraction of lung cancer biomarkers in exhaled breath

    , Article Analytica Chimica Acta ; Volume 1198 , 2022 ; 00032670 (ISSN) Soufi, G ; Bagheri, H ; Yeganeh Rad, L ; Minaeian, S ; Sharif University of Technology
    Elsevier B.V  2022
    Abstract
    Lung cancer (LC) is the leading cause of cancer mortality so, the analysis of exhaled human breath has great significance for early non-invasive diagnosis. Poor selectivity and strong humidity are two bottlenecks for the application of gas sensors to exhaled breath analysis. The development of novel extractive phases for the analysis of exhaled breath by chromatography is therefore a lucrative object. Polyhedral oligomeric silsesquioxanes (POSS) are among the 3D porous materials whose unique properties make them promising coatings for solid-phase microextraction (SPME). Selective enrichment of polar or nonpolar targets depends on the pore size and functional groups on the POSSs. Herein, we...