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    A pH-sensitive carrier based-on modified hollow mesoporous carbon nanospheres with calcium-latched gate for drug delivery

    , Article Materials Science and Engineering C ; Volume 109 , 2020 Asgari, S ; Pourjavadi, A ; Hosseini, S. H ; Kadkhodazadeh, S ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    A novel nanocarrier based-on hollow mesoporous carbon nanospheres (HMCNs) with primary amines on its surface, a large cavity, and good hydrophilicity was synthesized by a hydrothermal reaction. The primary amine functionalities on the mesoporous carbon were used as the initiation sites for growing poly (epichlorohydrin) (PCH) chains. The chlorine groups in the side chain of PCH were replaced with imidazole as the pendant groups. Calcium chloride (CaCl2) was applied as a capping agent. The coordination bonding was formed between pendant imidazole groups and calcium ions. Doxorubicin (DOX) was selected as a model of hydrophilic anticancer drug and was loaded onto the nanocarrier and released... 

    A hybrid deep model for automatic arrhythmia classification based on LSTM recurrent networks

    , Article 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020, 1 June 2020 through 3 June 2020 ; 2020 Bitarafan, A ; Amini, A ; Baghshah, M. S ; Khodajou Chokami, H ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    Electrocardiogram (ECG) recording of electrical heart activities has a vital diagnostic role in heart diseases. We propose to tackle the problem of arrhythmia detection from ECG signals totally by a deep model that does not need any hand-designed feature or heuristic segmentation (e.g., ad-hoc R-peak detection). In this work, we first segment ECG signals by detecting R-peaks automatically via a convolutional network, including dilated convolutions and residual connections. Next, all beats are aligned around their R-peaks as the most informative section of the heartbeat in detecting arrhythmia. After that, a deep learning model, including both dilated convolution layers and a Long-Short Term... 

    Decoding olfactory stimuli in EEG data using nonlinear features: A pilot study

    , Article Journal of Neuroscience Methods ; Volume 341 , 2020 Ezzatdoost, K ; Hojjati, H ; Aghajan, H ; Sharif University of Technology
    Elsevier B.V  2020
    Abstract
    Background: While decoding visual and auditory stimuli using recorded EEG signals has enjoyed significant attention in the past decades, decoding olfactory sensory input from EEG data remains a novelty. Recent interest in the brain's mechanisms of processing olfactory stimuli partly stems from the association of the olfactory system and its deficit with neurodegenerative diseases. New Methods: An olfactory stimulus decoder using features that represent nonlinear behavior content in the recorded EEG data has been introduced for classifying 4 olfactory stimuli in 5 healthy male subjects. Results: We show that by using nonlinear and chaotic features, a subject-specific classifier can be... 

    Prevention of gestational diabetes mellitus (GDM) and probiotics: Mechanism of action: A review

    , Article Current Diabetes Reviews ; Volume 16, Issue 6 , 2020 , Pages 538-545 Homayouni, A ; Bagheri, N ; Mohammad Alizadeh Charandabi, S ; Kashani, N ; Mobaraki Asl, N ; Mirghafurvand, M ; Asgharian, H ; Ansari, F ; Pourjafar, H ; Sharif University of Technology
    Bentham Science Publishers  2020
    Abstract
    Background: Gestational Diabetes Mellitus (GDM) is a health problem that is increasing around the world. Introduction: Prevention of GDM, rather than treatment, could have several benefits in terms of both health and economic cost. Even a slight reduction in maternal glucose in non-diabetic women, particularly in women at high risk for GDM, may have significant benefits for pregnancy results and the future health of off-springs. Probiotics are a relatively new intervention, which are assessed by mothers’ metabolism, and can reduce blood sugar levels, prevent gestational diabetes and reduce the maternal and fetal complications resulting from it. The aim of this study was to review the studies... 

    Identification of catecholamine neurotransmitters using a fluorescent electronic tongue

    , Article ACS Chemical Neuroscience ; Volume 11, Issue 1 , November , 2020 , Pages 25-33 Jafarinejad, S ; Bigdeli, A ; Ghazi Khansari, M ; Sasanpour, P ; Hormozinezhad, M. R ; Sharif University of Technology
    American Chemical Society  2020
    Abstract
    Catecholamine neurotransmitters, specifically, dopamine (DA), epinephrine (EP), and norepinephrine (NE), are known as substantial indicators of various neurological diseases. Developing rapid detection methods capable of simultaneously screening their concentrations is highly desired for early clinical diagnosis of such diseases. To this aim, we have designed an optical sensor array using three fluorescent dyes with distinct emission bands and have monitored variations in their emission profiles upon the addition of DA, EP, and NE in the presence of gold ions. Because of the different reducing power of catecholamines, differently sized gold nanoparticles (GNPs) with different levels of... 

    Development of a nano biosensor for anti-gliadin detection for Celiac disease based on suspension microarrays

    , Article Biomedical Physics and Engineering Express ; Volume 6, Issue 5 , August , 2020 Kharati, M ; Rabiee, M ; Rostami Nejad, M ; Aghamohammadi, E ; Asadzadeh Aghdaei, H ; Zali, M. R ; Rabiee, N ; Fatahi, Y ; Bagherzadeh, M ; Webster, T. J ; Sharif University of Technology
    IOP Publishing Ltd  2020
    Abstract
    Celiac disease is an autoimmune disorder represented by the ingestion of the gluten protein usually found in wheat, barley and rye. To date, ELISA has been the most accurate method for determining the presence of anti-gliadin, which is cumbersome, expensive (compared to a suspension microarray technique), and requires extensive sample preparation. In this study, in order to establish a more accurate assay to identify gliadin at lower concentrations, optical nano biosensors using an indirect immunoassay method for gliadin detection was designed and fabricated. For this, polycaprolactone (PCL) nano- to micro-beads were fabricated as a platform for the gliadin antigen which were optimized and... 

    Comparison of acidity and metal ion affinity of D-Glucosamine and N-acetyl-D-glucosamine, a DFT study

    , Article Journal of Molecular Graphics and Modelling ; Volume 98 , April , 2020 Mosapour Kotena, Z ; Fattahi, A ; Sharif University of Technology
    Elsevier Inc  2020
    Abstract
    The derivatives of glucose such as glucosamine (β-D-GlcN) and N-acetyl-D-β-glucosamine (GlcNAc) are significant in several biological systems. D-GlcN has been used widely to treat osteoarthritis in humans and animal models as well as GlcNAc has been proposed as a treatment for autoimmune diseases. The DFT/B3LYP/6–311++G (d,p) method as well as QTAIM and NBO analyses were used to the acidity values of D-GlcN and GlcNAc sugars and their complexes with alkali ions in the gas phase. The Li+, Na+ and K+ prefer bi-dentate chelate in these complexes. The computed results indicate that metal ion affinity (MIA) in GlcNAc is higher than that in D-GlcN. There are direct correlations between the MIA... 

    Bioengineering approaches for corneal regenerative medicine

    , Article Tissue Engineering and Regenerative Medicine ; Volume 17, Issue 5 , July , 2020 , Pages 567-593 Mahdavi, S. S ; Abdekhodaie, M. J ; Mashayekhan, S ; Baradaran Rafii, A ; Djalilian, A. R ; Sharif University of Technology
    Korean Tissue Engineering and Regenerative Medicine Society  2020
    Abstract
    Background:: Since the cornea is responsible for transmitting and focusing light into the eye, injury or pathology affecting any layer of the cornea can cause a detrimental effect on visual acuity. Aging is also a reason for corneal degeneration. Depending on the level of the injury, conservative therapies and donor tissue transplantation are the most common treatments for corneal diseases. Not only is there a lack of donor tissue and risk of infection/rejection, but the inherent ability of corneal cells and layers to regenerate has led to research in regenerative approaches and treatments. Methods:: In this review, we first discussed the anatomy of the cornea and the required properties for... 

    The immunomodulatory effects of probiotics on respiratory viral infections: A hint for COVID-19 treatment?

    , Article Microbial Pathogenesis ; Volume 148 , November , 2020 Mahooti, M ; Miri, S. M ; Abdolalipour, E ; Ghaemi, A ; Sharif University of Technology
    Academic Press  2020
    Abstract
    Respiratory virus infections are among the most prevalent diseases in humans and contribute to morbidity and mortality in all age groups. Moreover, since they can evolve fast and cross the species barrier, some of these viruses, such as influenza A and coronaviruses, have sometimes caused epidemics or pandemics and were associated with more serious clinical diseases and even mortality. The recently identified Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a Public Health Emergency of International concern and has been associated with rapidly progressive pneumonia. To ensure protection against emerging respiratory tract... 

    Effective brain connectivity estimation between active brain regions in autism using the dual Kalman-based method

    , Article Biomedizinische Technik ; Volume 65, Issue 1 , 2020 , Pages 23-32 Rajabioun, M ; Motie Nasrabadi, A ; Shamsollahi, M. B ; Coben, R ; Sharif University of Technology
    De Gruyter  2020
    Abstract
    Brain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities... 

    Diagnosis of schizophrenia from R-fMRI data using Ripplet transform and OLPP

    , Article Multimedia Tools and Applications ; Volume 79, Issue 31-32 , 2020 , Pages 23401-23423 Sartipi, S ; Kalbkhani, H ; Shayesteh, M. G ; Sharif University of Technology
    Springer  2020
    Abstract
    Schizophrenia is a severe brain disease that influences the behaviour and thought of person. These effects may fail in achieving the expected levels of interpersonal, academic, or occupational functioning. Although the underlying mechanism is not yet clear, the early detection of schizophrenia is an attractive and challenging research area. There are differences in brain connections of patients and healthy people. This study presents a new computer-aided diagnosis (CAD) method to diagnose schizophrenia (SZ) patients from normal control (NC) people by using the rest-state functional magnetic resonance imaging (R-fMRI) data. fMRI data has a huge dimension, and extracting efficient features is... 

    Stockwell transform of time-series of fMRI data for diagnoses of attention deficit hyperactive disorder

    , Article Applied Soft Computing Journal ; Volume 86 , 2020 Sartipi, S ; Kalbkhani, H ; Ghasemzadeh, P ; Shayesteh, M. G ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    Attention deficit hyperactivity disorder (ADHD) is a common brain disorder among children. It presents various symptoms, hence, utilizing the information obtained from functional magnetic resonance imaging (fMRI) time-series data can be useful. Finding functional connections in typically developed control (TDC) and ADHD patients can be helpful in classification. The aim of this paper is to present a multifold method for the study of fMRI data to diagnose ADHD patients. In the proposed method, first, by applying the Stockwell transform (ST), we obtain detailed information about the time-series of the region of interests (ROIs) in the time and frequency domains. ST provides information about... 

    A Close look at the imitation performance of children with autism and typically developing children using a robotic system

    , Article International Journal of Social Robotics ; 2020 Taheri, A ; Meghdari, A ; Mahoor, M. H ; Sharif University of Technology
    Springer Science and Business Media B.V  2020
    Abstract
    Deficit in imitation skills is one of the core symptoms of children with Autism Spectrum Disorder (ASD). In this study, we have tried to look closer at the body gesture imitation performance of 20 participants with autism, i.e. ASD group, and 20 typically developing subjects, i.e. TD group, in a set of robot-child and human-child gross imitation tasks. The results of manual scoring by two specialists indicated that while the TD group showed a significantly better imitation performance than the ASD group during the tasks, both ASD and TD groups performed better in the human-child mode than the robot-child mode in our experimental setup. Next, to introduce an automated imitation assessment... 

    Preoperative paraspinal neck muscle characteristics predict early onset adjacent segment degeneration in anterior cervical fusion patients: A machine-learning modeling analysis

    , Article Journal of Orthopaedic Research ; 2020 Wong, A. Y. L ; Harada, G ; Lee, R ; Gandhi, S. D ; Dziedzic, A ; Espinoza Orias, A ; Parnianpour, M ; Louie, P. K. H ; Basques, B ; An, H. S ; Samartzis, D ; Sharif University of Technology
    John Wiley and Sons Inc  2020
    Abstract
    Early onset adjacent segment degeneration (ASD) can be found within six months after anterior cervical discectomy and fusion (ACDF). Deficits in deep paraspinal neck muscles may be related to early onset ASD. This study aimed to determine whether the morphometry of preoperative deep neck muscles (multifidus and semispinalis cervicis) predicted early onset ASD in patients with ACDF. Thirty-two cases of early onset ASD after a two-level ACDF and 30 matched non-ASD cases were identified from a large-scale cohort. The preoperative total cross-sectional area (CSA) of bilateral deep neck muscles and the lean muscle CSAs from C3 to C7 levels were measured manually on T2-weighted magnetic resonance... 

    Classification of vascular function in upper limb using bilateral photoplethysmographic signals

    , Article Physiological Measurement ; Volume 29, Issue 3 , 2008 , Pages 365-374 ; 09673334 (ISSN) Hesam Shariati, N ; Zahedi, E ; Jajai, H. M ; Sharif University of Technology
    2008
    Abstract
    Bilateral PPG signals have been used for comparative study of two groups of healthy (free from any cardiovascular risk factors) and diabetic (as cardiovascular disease risk group) subjects in the age-matched range 40-50 years. The peripheral blood pulsations were recorded simultaneously from right and left index fingers for 90 s. Pulses have been modeled with the ARX440 model in the interval of 300 sample points with 100 sample points overlap between segments. Model parameters of three segments based on the highest fitness (higher than 80%) of modeled segments were retained for each subject. Subsequently, principal component analysis (PCA) was applied to the parameters of retained segments... 

    Development of Alzheimer's disease recognition using semiautomatic analysis of statistical parameters based on frequency characteristics of medical images

    , Article 2007 IEEE International Conference on Signal Processing and Communications, ICSPC 2007, Dubai, 14 November 2007 through 27 November 2007 ; 2007 , Pages 868-871 ; 9781424412365 (ISBN) Torabi, M ; Moradzadeh, H ; Vaziri, R ; Razavian, S. M. J ; Dehestani Ardekani, R ; Rahmandoust, M ; Taalimi, A ; Fatemizadeh, E ; Sharif University of Technology
    2007
    Abstract
    The paper presents an effective algorithm to analyze MR-images in order to recognize Alzheimer's Disease (AD) which appeared in patient's brain. The features of interest are categorized in Features of the Spatial Domain (FSD's) and Features of the Frequency Domain (FFD's) which are based on the first four statistic moments of the wavelet transform. Extracted features have been classified by a multi-layer perceptron Artificial Neural Network (ANN). Before ANN, the number of features is reduced from 44 to 12 to optimize and eliminate any correlation between them. The contribution of this paper is to demonstrate that by using the wavelet transform number of features needed for AD diagnosis has... 

    Translation and validation study of the Iranian versions of the neck disability index and the neck pain and disability scale

    , Article Spine ; Volume 32, Issue 26 , 2007 , Pages E825-E831 ; 03622436 (ISSN) Mousavi, J ; Parnianpour, M ; Montazeri, A ; Mehdian, H ; Karimi, A ; Abedi, M ; Askary Ashtiani, A ; Mobini, B ; Hadian, M. R ; Sharif University of Technology
    2007
    Abstract
    STUDY DESIGN. Cultural translation and psychometric testing. OBJECTIVE. To translate and validate the Iranian versions of the Neck Disability Index (NDI-IR) and the Neck Pain and Disability Scale (NPDS-IR). SUMMARY OF BACKGROUND DATA. The widely used the NDI and the NPDS scales have not been translated and validated for Persian-speaking patients with neck pain. This was to provide a validated instrument to measure functional status in patients with neck pain in Iran. METHODS. The translation and cultural adaptation of the original questionnaires were carried out in accordance with the published guidelines. One hundred and eighty-five patients with neck pain were participated in the study.... 

    Computational simulation of non-Newtonian blood flow in carotid bifurcation for investigation the various rheological blood models

    , Article ASME 2007 International Mechanical Engineering Congress and Exposition, IMECE 2007, 11 November 2007 through 15 November 2007 ; Volume 2 , 2007 , Pages 263-270 ; 0791842967 (ISBN) Jahanyfard, E ; Firoozabadi, B ; Goodarzvand Chegini, A ; ASME ; Sharif University of Technology
    American Society of Mechanical Engineers (ASME)  2007
    Abstract
    One of the leading causes for death after heart diseases and cancer in all over the world is still stroke. Most strokes happen because an artery carrying blood from the heart to the brain is clogged. Most of the time, as with heart attacks, the problem is atherosclerosis, hardening of the arteries, calcified build up of fatty deposits on the vessel wall. The primary troublemaker is the carotid artery, one on each side of the neck, the main thoroughfare for blood to the brain. In this study, the fluid dynamic simulations were done in the carotid bifurcation artery for studying the formation of atherosclerosis, and shear thinning behavior of blood as well as Newtonian comportment was studied.... 

    Conifer: clonal tree inference for tumor heterogeneity with single-cell and bulk sequencing data

    , Article BMC Bioinformatics ; Volume 22, Issue 1 , 2021 ; 14712105 (ISSN) Baghaarabani, L ; Goliaei, S ; Foroughmand Araabi, M. H ; Shariatpanahi, P ; Goliaei, B ; Sharif University of Technology
    BioMed Central Ltd  2021
    Abstract
    Background: Genetic heterogeneity of a cancer tumor that develops during clonal evolution is one of the reasons for cancer treatment failure, by increasing the chance of drug resistance. Clones are cell populations with different genotypes, resulting from differences in somatic mutations that occur and accumulate during cancer development. An appropriate approach for identifying clones is determining the variant allele frequency of mutations that occurred in the tumor. Although bulk sequencing data can be used to provide that information, the frequencies are not informative enough for identifying different clones with the same prevalence and their evolutionary relationships. On the other... 

    GKD: Semi-supervised graph knowledge distillation for graph-independent inference

    , Article 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, 27 September 2021 through 1 October 2021 ; Volume 12905 LNCS , 2021 , Pages 709-718 ; 03029743 (ISSN) ; 9783030872397 (ISBN) Ghorbani, M ; Bahrami, M ; Kazi, A ; Soleymani Baghshah, M ; Rabiee, H. R ; Navab, N ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    The increased amount of multi-modal medical data has opened the opportunities to simultaneously process various modalities such as imaging and non-imaging data to gain a comprehensive insight into the disease prediction domain. Recent studies using Graph Convolutional Networks (GCNs) provide novel semi-supervised approaches for integrating heterogeneous modalities while investigating the patients’ associations for disease prediction. However, when the meta-data used for graph construction is not available at inference time (e.g., coming from a distinct population), the conventional methods exhibit poor performance. To address this issue, we propose a novel semi-supervised approach named GKD...