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    Nuclear magnetic resonance -based metabolomics analysis of patients exposed to sulfur mustard in different stages using random forest method

    , Article Koomesh ; Volume 17, Issue 3 , 2016 , Pages 701-706 ; 16087046 (ISSN) Nobakht M. Gh., B. F ; Aliannejad, R ; Oskouie, A. A ; Fathi, F ; Sahakhah, H. A ; Rezaei Tavirani, M ; Sharif University of Technology
    Semnan University of Medical Sciences 
    Abstract
    Metabolomics is a powerful technique for determination of biomarkers. Here, we aimed to determine discriminatory metabolomic profiles in different stages of sulfur mustard-exposed patients (SMEPs). Materials and methods: Nuclear magnetic resonance spectroscopy was used to analyze serum samples from 17 SMEPs (normal group patients) and 17 SMEPs (severe group patients). Multivariate statistical analysis using random forest (RF) was performed on a ‘training set’ (70% of the total sample) in order to produce a discriminatory model classifying two groups of patients, and the model tested in the remaining subjects. Results: A classification model was derived using data from the training set with... 

    NMR spectroscopy-based metabolomic study of serum in sulfur mustard exposed patients with lung disease

    , Article Biomarkers ; 2016 , Pages 1-7 ; 1354750X (ISSN) Nobakht M. Gh., B. F ; Arefi Oskouie, A ; Rezaei Tavirani, M ; Aliannejad, R ; Taheri, S ; Fathi, F ; Naseri, M. T ; Sharif University of Technology
    Taylor and Francis Ltd  2016
    Abstract
    Sulfur mustard (SM) is a vesication chemical warfare agent for which there is currently no antidote. Despite years of research, there is no common consensus about the pathophysiological basis of chronic pulmonary disease caused by this chemical warfare agent. In this study, we combined chemometric techniques with nuclear magnetic resonance (NMR) spectroscopy to explore the metabolic profile of sera from SM-exposed patients. A total of 29 serum samples obtained from 17 SM-injured patients, and 12 healthy controls were analyzed by Random Forest. Increased concentrations of seven amino acids, glycerol, dimethylamine, ketone bodies, lactate, acetate, citrulline and creatine together with the... 

    Fourier transform infrared spectroscopy: A potential technique for noninvasive detection of spermatogenesis

    , Article Avicenna Journal of Medical Biotechnology ; Vol. 6, Issue. 1 , 2014 , pp. 47-52 ; ISSN: 2008-4625 Gilany, K ; Moazeni Pouracil, R. S ; Reza Sadeghi, M ; Sharif University of Technology
    Abstract
    Background: The seminal plasma is an excellent source for noninvasive detection of spermatogenesis. The seminal plasma of normospermic and azoospermic men has been analyzed for detection of spermatogenesis. Methods: Optical spectroscopy (Attenuated Total Reflectance-Infrared spectroscopy (ATR-IR) and Fourier Transform infrared spectroscopy (FT-IR) has been used to analyze the seminal plasma and the metabolome of seminal plasma for detection of spermatogenesis. Results The seminal plasma of normospermic and azoospermic men has been analyzed by ATR-IR. The results show that there is a pattern variation in the azoospermic men compared to normospermic men. However, the seminal plasma is too... 

    Metabolomics fingerprinting of the human seminal plasma of asthenozoospermic patients

    , Article Molecular Reproduction and Development ; Vol. 81, Issue. 1 , 2014 , pp. 84-86 ; ISSN: 1098-2795 Gilany, K ; Moazeni-Pourasil, R. S ; Jafarzadeh, N ; Savadi-Shiraz, E ; Sharif University of Technology
    Abstract
    It is estimated that 20% of couples are infertile, and half of these infertility cases are linked to men. One of conditions that can affect male fertility is asthenozoospermia. We applied Raman spectroscopy to the analysis of the metabolome of the human seminal plasma, and used chemometrics on the patterns of Raman spectra obtained. Significant changes were observed in the metabolome of the human seminal plasma of asthenozoospermic patients  

    A metabonomics investigation of multiple sclerosis by nuclear magnetic resonance

    , Article Magnetic Resonance in Chemistry ; Volume 51, Issue 2 , DEC , 2013 , Pages 102-109 ; 07491581 (ISSN) Mehrpour, M ; Kyani, A ; Tafazzoli, M ; Fathi, F ; Joghataie, M. T ; Sharif University of Technology
    2013
    Abstract
    Multiple sclerosis (MS) is a nervous system disease that affects the fatty myelin sheaths around the axons of the brain and spinal cord, leading to demyelination and a broad range of signs and symptoms. MS can be difficult to diagnose because its signs and symptoms may be similar to other medical problems. To find out which metabolites in serum are effective for the diagnosis of MS, we utilized metabolic profiling using proton nuclear magnetic resonance spectroscopy (1H-NMR). Random forest (RF) was used to classify the MS patients and healthy subjects. Atomic absorption spectroscopy was used to measure the serum levels of selenium. The results showed that the levels of selenium were lower in... 

    RMet: An automated R based software for analyzing GC-MS and GC×GC-MS untargeted metabolomic data

    , Article Chemometrics and Intelligent Laboratory Systems ; Volume 194 , 2019 ; 01697439 (ISSN) Moayedpour, S ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2019
    Abstract
    Gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) are powerful techniques for measurement of all metabolites in complex metabolic samples. However, analyzing GC-MS and especially GC×GC-MS metabolomic data is a major challenge to the researchers in the field of metabolomics mainly due to the complexity and large data size. In this regard, an automated R based software entitled RMet has been developed to overcome the challenges in the metabolomic analysis workflow of GC-MS and GC×GC-MS data sets. Additionally, it is able to facilitate the complex process of extracting reliable and useful biological information from... 

    Recent trends in application of chemometric methods for GC-MS and GC×GC-MS-based metabolomic studies

    , Article TrAC - Trends in Analytical Chemistry ; Volume 138 , 2021 ; 01659936 (ISSN) Feizi, N ; Hashemi Nasab, F. S ; Golpelichi, F ; Sabouruh, N ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Metabolomics is the science of studying small molecules (metabolites) in biological systems with the aim of getting insight into cells, biofluids and organisms. Chemometric methods are powerful tools to address data problems generated in metabolomic studies and to extract valuable information. This review focuses mainly on a range of chemometric methods used for processing of metabolomics data generated from gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC-MS). Herein, essential skills used for preprocessing of raw data, multivariate resolution, pattern recognition, variable selection and identification of... 

    The Pattern Recognition Methods in Combination with Nuclear Magnetic Resonance (NMR)Spectroscopy in Order to Develop a Metabolomic Approach to Breast Cancer Prognosis

    , M.Sc. Thesis Sharif University of Technology Esmaeili, Pedram (Author) ; Parastar Shahri, Hadi (Supervisor)
    Abstract
    The emerging field of “metabolomics” focuses on investigating into the changes of low-molecular-weight – less than 1500 Daltons – molecules, or metabolites, and it has significantly developed in the field of detecting diseases, particularly cancer in recent years. Regarding the importance of breast cancer (BC), especially among women, developing simple, trusted metabolic approaches are crucial. In the present work, utilizing multivariate class-modelling techniques combined to nuclear magnetic resonance (NMR) in order to predict breast cancer based on analyzing the blood serum of healthy and BC patients is presented. To do so, using 42 blood samples, 18 BC patients and 24 healthy individuals,... 

    Metabolic load comparison between the quarters of a game in elite male basketball players using sport metabolomics

    , Article European Journal of Sport Science ; 2020 Khoramipour, K ; Gaeini, A. A ; Shirzad, E ; Gilany, K ; Chashniam, S ; Sandbakk, Ø ; Sharif University of Technology
    Taylor and Francis Ltd  2020
    Abstract
    Purpose: A basketball match is characterized by intermittent high-intensity activities, thereby relying extensively on both aerobic and anaerobic metabolic pathways. Here, we aimed to compare the metabolic fluctuations between the four 10-min quarters of high-level basketball games using metabolomics analyses. Methods: 70 male basketball players with at least 3 years of experience in the Iran national top-league participated. Before and after each quarter, saliva samples were taken for subsequent untargeted metabolomics analyses, where Principal component analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA) were employed for statistical analysis. Results: Quarters 1 and 3... 

    NMR- and GC/MS-based metabolomics of sulfur mustard exposed individuals: a pilot study

    , Article Biomarkers ; Volume 21, Issue 6 , 2016 , Pages 479-489 ; 1354750X (ISSN) Nobakht, B. F ; Aliannejad, R ; Rezaei Tavirani, M ; Arefi Oskouie, A ; Naseri, M. T ; Parastar, H ; Aliakbarzadeh, G ; Fathi, F ; Taheri, S ; Sharif University of Technology
    Taylor and Francis Ltd 
    Abstract
    Sulfur Mustard (SM) is a potent alkylating agent and its effects on cells and tissues are varied and complex. Due to limitations in the diagnostics of sulfur mustard exposed individuals (SMEIs) by noninvasive approaches, there is a great necessity to develop novel techniques and biomarkers for this condition. We present here the first nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC/MS) metabolic profiling of serum from and healthy controls to identify novel biomarkers in blood serum for better diagnostics. Of note, SMEIs were exposed to SM 30 years ago and that differences between two groups could still be found. Pathways in which differences between SMEIs and... 

    Metabolic profiling of seminal plasma from teratozoospermia patients

    , Article Journal of Pharmaceutical and Biomedical Analysis ; Volume 178 , January , 2020 Mehrparvar, B ; Chashmniam, S ; Nobakht, F ; Amini, M ; Javidi, A ; Minai Tehrani, A ; Arjmand, B ; Gilany, K ; Sharif University of Technology
    Elsevier B. V  2020
    Abstract
    Teratozoospermia is one of conditions that can cause male infertility. The mechanism of teratozoospermia remains unclear. The knowledge of the metabolites in human seminal plasma (HSP) is meaningful for the pathological study of teratozoospermia. Analysis of changed metabolites in HSP can help understand the cellular mechanism, find the novel biomarkers and subsequently design a diagnosis test. In this study, the analysis of samples performed by proton nuclear magnetic resonance spectroscopy (1H NMR spectroscopy) to identify the various metabolites, with the aim of finding metabolic profiles and biomarkers related to male infertility. Eighteen de-regulated metabolites were identified in... 

    Metabolic load comparison between the quarters of a game in elite male basketball players using sport metabolomics

    , Article European Journal of Sport Science ; Volume 21, Issue 7 , 2021 , Pages 1022-1034 ; 17461391 (ISSN) Khoramipour, K ; Gaeini, A. A ; Shirzad, E ; Gilany, K ; Chashniam, S ; Sandbakk, Ø ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    Purpose: A basketball match is characterized by intermittent high-intensity activities, thereby relying extensively on both aerobic and anaerobic metabolic pathways. Here, we aimed to compare the metabolic fluctuations between the four 10-min quarters of high-level basketball games using metabolomics analyses. Methods: 70 male basketball players with at least 3 years of experience in the Iran national top-league participated. Before and after each quarter, saliva samples were taken for subsequent untargeted metabolomics analyses, where Principal component analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA) were employed for statistical analysis. Results: Quarters 1 and 3... 

    Untargeted metabolomics based on nuclear magnetic resonance spectroscopy and multivariate classification techniques for identifying metabolites associated with breast cancer patients

    , Article Chemometrics and Intelligent Laboratory Systems ; Volume 223 , 2022 ; 01697439 (ISSN) Esmaeili, P ; Khalilvand, M ; Tavakolizadeh, H ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2022
    Abstract
    In this study, multivariate classification techniques combined with proton nuclear magnetic resonance (1HNMR) spectroscopy is proposed to identify breast cancer biomarkers that can precisely distinguish between healthy control and breast cancer (BC) patients. In this regard, first optimizing the metabolite extraction procedure was performed using Box-Behnken design (BBD). Then, data-driven soft independent modeling of class analogy (DD-SIMCA) model and partial least squares-discriminant analysis (PLS-DA) were successfully utilized for separating healthy from BC patient's classes. On this matter, both DD-SIMCA and PLS-DA models could successfully distinguish the healthy class from the BC... 

    Metabolomics analysis of the saliva in patients with chronic hepatitis b using nuclear magnetic resonance: A pilot study

    , Article Iranian Journal of Basic Medical Sciences ; Volume 22, Issue 9 , 2019 , Pages 1044-1049 ; 20083866 (ISSN) Gilany, K ; Mohamadkhani, A ; Chashmniam, S ; Shahnazari, P ; Amini, M ; Arjmand, B ; Malekzadeh, R ; Nobakht Motlagh Ghoochani, B. F ; Sharif University of Technology
    Mashhad University of Medical Sciences  2019
    Abstract
    Objective(s): Hepatitis B virus infection causes chronic disease such as cirrhosis and hepatocellular carcinoma. The metabolomics investigations have been demonstrated to be related to pathophysiologic mechanisms in many disorders such as hepatitis B infection. The aim of this study was to investigate the saliva metabolic profile of patients with chronic hepatitis B infection and to identify underlying mechanisms as well as potential biomarkers associated with the disease. Materials and Methods: Saliva from 16 healthy subjects and 20 patients with chronic hepatitis B virus were analyzed by nuclear magnetic resonance (NMR). Then, multivariate statistical analysis was performed to identify... 

    Chemometric techniques coupled with NMR for matabolic profiling of lettuce exposed to polycyclic aromatic hydrocarbones

    , Article Analytical Biochemistry ; Volume 611 , 2020 Feizi, N ; Seraj, M ; Tajali, R ; Shavandi, S. R ; Parastar, H ; Sharif University of Technology
    Academic Press Inc  2020
    Abstract
    Treated waste water (TWW) quality varies due to the occurrence of polycyclic aromatic hydrocarbons (PAHs) up to low μg L−1. In this study, a non-targeted metabolomic analysis was performed on lettuce (Lactuca sativa L) exposed to 4 PAHs by irrigation. The plants were watered with different concentrations of contaminants (0–100 μg L−1) for 39 days under controlled conditions and then harvested, extracted and analyzed by nuclear magnetic resonance (NMR). Different chemometric tools based on principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are proposed for the analysis of the complex data sets generated in the different exposure experiments.... 

    Metabolomic biomarkers in the diagnosis of non-alcoholic fatty liver disease

    , Article Hepatitis Monthly ; Volume 19, Issue 9 , 2019 ; 1735143X (ISSN) Chashmniam, S ; Ghafourpour, M ; Rezaei Farimani, A ; Gholami, A ; Nobakht Motlagh Ghoochani, B. F ; Sharif University of Technology
    Kowsar Medical Publishing Company  2019
    Abstract
    Background: Nonalcoholic fatty liver disease (NAFLD) is the most abundant chronic liver disorder, because racial and ethnic differences may influence prevalence and severity of NAFLD. Objectives: This metabolomic study was conducted to identify the metabolic biomarkers and determine the mechanism of progress of NAFLD in Iranian patients. Methods: Serum samples were collected from 75 participants (37 healthy controls and 38 patients with NAFLD) after an overnight fast. The metabolome of all samples were determined by nuclear magnetic resonance (NMR) and were compared by multivariate statistical analysis. Results: Totally, 19 metabolomic biomarkers were identified by NMR. Compared to healthy... 

    A noninvasive urine metabolome panel as potential biomarkers for diagnosis of t cell-mediated renal transplant rejection

    , Article OMICS A Journal of Integrative Biology ; Volume 24, Issue 3 , March , 2020 , Pages 140-147 Kalantari, S ; Chashmniam, S ; Nafar, M ; Samavat, S ; Rezaie, D ; Dalili, N ; Sharif University of Technology
    Mary Ann Liebert Inc  2020
    Abstract
    Acute T cell-mediated rejection (TCMR)is a major complication after renal transplantation. TCMR diagnosis is very challenging and currently depends on invasive renal biopsy and nonspecific markers such as serum creatinine. A noninvasive metabolomics panel could allow early diagnosis and improved accuracy and specificity. We report, in this study, on urine metabolome changes in renal transplant recipients diagnosed with TCMR, with a view to future metabolomics-based diagnostics in transplant medicine. We performed urine metabolomic analyses in three study groups: (1) 7 kidney transplant recipients with acute TCMR, (2) 15 kidney transplant recipients without rejection but with impaired kidney... 

    NMR based metabonomics study on celiac disease in the blood serum

    , Article Gastroenterology and Hepatology from Bed to Bench ; Volume 6, Issue 4 , 2013 , Pages 190-194 ; 20082258 (ISSN) Fathi, F ; Ektefa, F ; Arefi Oskouie, A ; Rostami, K ; Rezaei Tavirani, M ; Mohammad Alizadeh, A. H ; Tafazzoli, M ; Rostami Nejad, M ; Sharif University of Technology
    2013
    Abstract
    Aim: The aim of this study is to look for the proper methods that would be a major step towards untreated CD diagnosis and seek the metabolic biomarkers causes of CD and compare them to control group. Background: Celiac disease (CD) is a common autoimmune disorder that is not easily diagnosed using the clinical tests. Patients and methods: Thirty cases and 30 controls were entered into this study. Metabolic profiling was obtained using proton nuclear magnetic resonance spectroscopy (1HNMR) to seek metabolites that are helpful for the detection of CD. Classification of CD and healthy subject was done using random forest (RF). Results: The obtained classification model showed an 89% correct... 

    Advantage of applying OSC to 1H NMR-based metabonomic data of celiac disease

    , Article International Journal of Endocrinology and Metabolism ; Volume 10, Issue 3 , 2012 , Pages 548-552 ; 1726913X (ISSN) Rezaei Tavirani, M ; Fathi, F ; Darvizeh, F ; Zali, M. R ; Nejad, M. R ; Rostami, K ; Tafazzoli, M ; oskouie, A. A ; Mortazavi Tabatabaei, S. A ; Sharif University of Technology
    2012
    Abstract
    Background: Celiac disease (CD) is a disorder associated with body reaction to gluten. After the gluten intake, an immune reaction against the protein occurs and damages villi of small intestine in celiac patients gradually. Objectives: The OSC, a filtering method for minimization of inter- and intra-spectrom-eter variations that influence on data acquisition, was applied to biofluid NMR data of CD patients. Patients and Methods: In this study, metabolites of total 56 serum samples from 12 CD patients, 15 CD patients taking gluten-free diet (GFD), and 29 healthy cases were analyzed using nuclear magnetic resonance (NMR) and associated theoretical analysis. Employ-ing ProMetab (version... 

    Urine and serum NMR-based metabolomics in pre-procedural prediction of contrast-induced nephropathy

    , Article Internal and Emergency Medicine ; Volume 15, Issue 1 , 2020 , Pages 95-103 Dalili, N ; Chashmniam, S ; Khoormizi, S. M. H ; Salehi, L ; Jamalian, S. A ; Nafar, M ; Kalantari, S ; Sharif University of Technology
    Springer  2020
    Abstract
    Contrast induced nephropathy (CIN) has been reported to be the third foremost cause of acute renal failure. Metabolomics is a robust technique that has been used to identify potential biomarkers for the prediction of renal damage. We aim to analyze the serum and urine metabolites changes, before and after using contrast for coronary angiography, to determine if metabolomics can predict early development of CIN. 66 patients undergoing elective coronary angiography were eligible for enrollment. Urine and serum samples were collected prior to administration of CM and 72 h post procedure and analyzed by nuclear magnetic resonance. The significant differential metabolites between patients who...