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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) ; 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...
Chemometrics-assisted isotope ratio fingerprinting based on gas chromatography/combustion/isotope ratio mass spectrometry for saffron authentication
, Article Journal of Chromatography A ; Volume 1657 , 2021 ; 00219673 (ISSN) ; Parastar, H ; Sharif University of Technology
Elsevier B.V
2021
Abstract
In the present contribution, the capability of isotopic ratio mass spectrometry (IRMS) for saffron authentication and detection of four common plant-derived adulterants (marigold flower, safflower, rubia, and saffron style) was investigated. For this purpose, 62 authentic saffron samples were analyzed by elemental analyzer-IRMS (EA-IRMS) and gas chromatography-combustion-IRMS (GC-C-IRMS). In this regard, EA-IRMS and GC-C-IRMS isotope fingerprints of carbon-13 and nitrogen-15 isotopes of saffron components were provided and then analyzed by chemometric methods. Principal component analysis (PCA) showed two different behaviors regarding two main regions. Then, a representative saffron sample...
Comparison of near-infrared (NIR) and mid-infrared (MIR) spectroscopy based on chemometrics for saffron authentication and adulteration detection
, Article Food Chemistry ; Volume 344 , 2021 ; 03088146 (ISSN) ; Nikounezhad, N ; Amirahmadi, M ; Daraei, B ; Parastar, H ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
In this work, the potential of near-infrared (NIR) and mid-infrared (MIR) spectroscopy along with chemometrics was investigated for authentication and adulteration detection of Iranian saffron samples. First, authentication of one-hundred saffron samples was examined by principal component analysis (PCA). The results showed the NIR spectroscopy can better predict the origin of samples than the MIR. Next, partial least squares-discriminant analysis (PLS-DA) was developed to detect four common plant-derived adulterants (i.e., saffron style, calendula, safflower, and rubia). In all cases, PLS-DA classification figures of merit in terms of sensitivity, specificity, error rate and accuracy were...
Fuzzy C-means clustering for chromatographic fingerprints analysis: A gas chromatography-mass spectrometry case study
, Article Journal of Chromatography A ; Volume 1438 , 2016 , Pages 236-243 ; 00219673 (ISSN) ; Bazrafshan, A ; Sharif University of Technology
Elsevier
Abstract
Fuzzy C-means clustering (FCM) is proposed as a promising method for the clustering of chromatographic fingerprints of complex samples, such as essential oils. As an example, secondary metabolites of 14 citrus leaves samples are extracted and analyzed by gas chromatography-mass spectrometry (GC-MS). The obtained chromatographic fingerprints are divided to desired number of chromatographic regions. Owing to the fact that chromatographic problems, such as elution time shift and peak overlap can significantly affect the clustering results, therefore, each chromatographic region is analyzed using multivariate curve resolution-alternating least squares (MCR-ALS) to address these problems. Then,...
Joint approximate diagonalization of eigenmatrices as a high-throughput approach for analysis of hyphenated and comprehensive two-dimensional gas chromatographic data
, Article Journal of Chromatography A ; Volume 1524 , 2017 , Pages 188-201 ; 00219673 (ISSN) ; Parastar, H ; Sharif University of Technology
Abstract
The objective of the present work is development of joint approximate diagonalization of eigenmatrices (JADE) as a member of independent component analysis (ICA) family, for the analysis of gas chromatography-mass spectrometry (GC–MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC × GC–MS) data to address incomplete separation problem occurred during the analysis of complex sample matrices. In this regard, simulated GC–MS and GC × GC–MS data sets with different number of components, different degree of overlap and noise were evaluated. In the case of simultaneous analysis of multiple samples, column-wise augmentation for GC–MS and column-wise super-augmentation...
Gas chromatographic fingerprint analysis of secondary metabolites of Stachys lanata (Stachys byzantine C. Koch) combined with antioxidant activity modelling using multivariate chemometric methods
, Article Journal of Chromatography A ; Volume 1602 , 2019 , Pages 432-440 ; 00219673 (ISSN) ; Abtahi, M ; Parastar, H ; Sharif University of Technology
Elsevier B.V
2019
Abstract
S. lanata has been traditionally used as a medicinal plant due to its various biological activities such as antioxidant activity. Therefore, identification and quality control studies of this plant are of great importance. To this end, gas chromatography (GC) combined with chemometrics was proposed for fingerprint analysis of S. lanata samples. This study sought to classify GC fingerprints of twenty-eight S. lanata samples from eight different regions of Iran and more importantly, to correlate fingerprints to the antioxidant activity to select S. lanata volatile antioxidant markers. S. lanata samples were classified into five and three classes using partial least squares-discriminant...
Activated carbon/metal-organic framework nanocomposite: Preparation and photocatalytic dye degradation mathematical modeling from wastewater by least squares support vector machine
, Article Journal of Environmental Management ; Volume 233 , 2019 , Pages 660-672 ; 03014797 (ISSN) ; Abdi, J ; Taghizadeh, M ; Taghizadeh, A ; Hayati, B ; Shekarchi, A. A ; Vossoughi, M ; Sharif University of Technology
Academic Press
2019
Abstract
Herein, Kiwi peel activated carbon (AC), Materials Institute Lavoisier (MIL-88B (Fe), and AC/MIL-88B (Fe) composite were synthesized and used as catalysts to degrade Reactive Red 198. The material properties were analyzed by the FTIR, BET-BJH, XRD, FESEM, EDX, TGA, and UV–Vis/DRS. The BET surface area of AC, MIL-88B (Fe) and AC/MIL-88B (Fe) was 1113.3, 150.7, and 199.4 m2/g, respectively. The band gap values (Eg) estimated by Tauc plot method, were obtained 5.06, 4.19 and 3.79 eV for AC, MIL-88B (Fe) and AC/MIL-88B (Fe), respectively. The results indicated that the AC/MIL-88B (Fe) composite had higher photocatalytic activity (99%) than that of pure AC (79%) and MIL-88B (Fe) catalysts (87%)....
Combining multivariate image analysis with high-performance thin-layer chromatography for development of a reliable tool for saffron authentication and adulteration detection
, Article Journal of Chromatography A ; Volume 1628 , 2020 ; Rashidi, M ; Kamyar, M ; Amirahmadi, M ; Daraei, B ; Parastar, H ; Sharif University of Technology
Elsevier B.V
2020
Abstract
In this work, high-performance thin-layer chromatography (HPTLC) coupled with multivariate image analysis (MIA) is proposed as a fast and reliable tool for authentication and adulteration detection of Iranian saffron samples based on their HPTLC fingerprints. At first, the secondary metabolites of saffron were extracted using ultrasonic-assisted solvent extraction (UASE) which was optimized using central composite design (CCD). Next, the RGB coordinates of HPTLC images were used for estimation of saffron origin based on principal component analysis (PCA). The PCA scores plot showed that saffron samples were clustered into two clear-cut groups which was 92% matched with the geographical...
Detection of addition of barley to coffee using near infrared spectroscopy and chemometric techniques
, Article Talanta ; Volume 99 , 2012 , Pages 175-179 ; 00399140 (ISSN) ; Leardi, R ; Oliveri, P ; Chiara Casolino, M ; Jalali Heravi, M ; Lanteri, S ; Sharif University of Technology
Elsevier
2012
Abstract
The current study presents an application of near infrared spectroscopy for identification and quantification of the fraudulent addition of barley in roasted and ground coffee samples. Nine different types of coffee including pure Arabica, Robusta and mixtures of them at different roasting degrees were blended with four types of barley. The blending degrees were between 2 and 20 wt% of barley. D-optimal design was applied to select 100 and 30 experiments to be used as calibration and test set, respectively. Partial least squares regression (PLS) was employed to build the models aimed at predicting the amounts of barley in coffee samples. In order to obtain simplified models, taking into...
Introducing a comprehensive framework to measure spike-LFP coupling
, Article Frontiers in Computational Neuroscience ; Volume 12 , 2018 ; 16625188 (ISSN) ; Jahed, M ; Daliri, M. R ; Sharif University of Technology
Frontiers Media S.A
2018
Abstract
Measuring the coupling of single neuron's spiking activities to the local field potentials (LFPs) is a method to investigate neuronal synchronization. The most important synchronization measures are phase locking value (PLV), spike field coherence (SFC), pairwise phase consistency (PPC), and spike-triggered correlation matrix synchronization (SCMS). Synchronization is generally quantified using the PLV and SFC. PLV and SFC methods are either biased on the spike rates or the number of trials. To resolve these problems the PPC measure has been introduced. However, there are some shortcomings associated with the PPC measure which is unbiased only for very high spike rates. However evaluating...
Quantitative structure-activity relationship study of serotonin (5-HT7) receptor inhibitors using modified ant colony algorithm and adaptive neuro-fuzzy interference system (ANFIS)
, Article European Journal of Medicinal Chemistry ; Volume 44, Issue 4 , 2009 , Pages 1463-1470 ; 02235234 (ISSN) ; Asadollahi Baboli, M ; Sharif University of Technology
2009
Abstract
Quantitative structure-activity relationship (QSAR) approach was carried out for the prediction of inhibitory activity of some novel quinazolinone derivatives on serotonin (5-HT7) using modified ant colony (ACO) method and adaptive neuro-fuzzy interference system (ANFIS) combined with shuffling cross-validation technique. A modified ACO algorithm is utilized to select the most important variables in QSAR modeling and then these variables were used as inputs of ANFIS to predict 5-HT7 receptor binding activities of quinazolinone derivatives. The best descriptors describing the inhibition mechanism are Qmax, Se, Hy, PJI3 and DELS which are among electronic, constitutional, geometric and...
Application of genetic algorithm-kernel partial least square as a novel nonlinear feature selection method: Activity of carbonic anhydrase II inhibitors
, Article European Journal of Medicinal Chemistry ; Volume 42, Issue 5 , 2007 , Pages 649-659 ; 02235234 (ISSN) ; Kyani, A ; Sharif University of Technology
2007
Abstract
This paper introduces the genetic algorithm-kernel partial least square (GA-KPLS), as a novel nonlinear feature selection method. This technique combines genetic algorithms (GAs) as powerful optimization methods with KPLS as a robust nonlinear statistical method for variable selection. This feature selection method is combined with artificial neural network to develop a nonlinear QSAR model for predicting activities of a series of substituted aromatic sulfonamides as carbonic anhydrase II (CA II) inhibitors. Eight simple one- and two-dimensional descriptors were selected by GA-KPLS and considered as inputs for developing artificial neural networks (ANNs). These parameters represent the role...
Early detection of immunization: A study based on an animal model using 1H nuclear magnetic resonance spectroscopy
, Article Pakistan Journal of Biological Sciences ; Volume 14, Issue 3 , 2011 , Pages 195-203 ; 10288880 (ISSN) ; Arjmand, M ; Tafazzoli, M ; Ghohzadeh, A ; Pourfallah, F ; Sadeghi, S ; Mirzazadeh, R ; Mirkham, F ; Tahen, S ; Iravam, A ; Bayat, P ; Vahabi, F ; Sharif University of Technology
2011
Abstract
Vaccines require a period of at least three months for clinical trials, hence a method that can identify elicitation of immune response a few days after the first dose is a necessity. Evolutionary variable selections are modeling approaches for proper manipulation of available data which were used to set up an animal model for classification of time dependent 'HNMR metabolomic profiles and pattern recognition of fluctuations of metabolites in two groups of male rabbits. One group of rabbits was immunized with human red blood cells and the other used as control. Blood was obtained every 48 h from each rabbit for a period of six weeks and the serum monitored for antibodies and metabolites by...
An intelligent approach for improved predictive control of spray drying process
, Article INES 2010 - 14th International Conference on Intelligent Engineering Systems, Proceedings, 5 May 2010 through 7 May 2010, Las Palmas of Gran Canaria ; 2010 , Pages 127-136 ; 9781424476527 (ISBN) ; Neshat, N ; Saberi, M ; Sharif University of Technology
2010
Abstract
A flexible meta modelling approach is presented to predictive control of a drying process using Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Network (ANN) and Partial Least Squares (PLS) analysis. In the proposed approach, the PLS analysis is used to pre-process actual data and to provide the necessary background to apply ANN and ANFIS approaches. A reasonable section of this study is assigned to the modelling with aim at predicting the granule particle size and executing by ANFIS and ANN. ANN hold the promise of being capable of producing non-linear models, being able to work under noise conditions and being fault tolerant to the loss of neurons or connections. Also, the...
Thermal conductivity ratio prediction of Al2O3/water nanofluid by applying connectionist methods
, Article Colloids and Surfaces A: Physicochemical and Engineering Aspects ; Volume 541 , 2018 , Pages 154-164 ; 09277757 (ISSN) ; Alhuyi Nazari, M ; Ghasempour, R ; Madah, H ; Shafii, M. B ; Ahmadi, M. A ; Sharif University of Technology
Elsevier B.V
2018
Abstract
Various parameters affect thermal conductivity of nanofluid; however, some of them are more influential such as temperature, size and type of nano particles and volumetric concentration. In this study, artificial neural network as well as least square support vector machine (LSSVM) are applied in order to predict thermal conductivity ratio of alumina/water nanofluid as a function of particle size, temperature and volumetric concentration. LSSVM, Self-Organizing Map and Levenberg-Marquardt Back Propagation algorithms are applied to predict thermal conductivity ratio. Obtained results indicated that these algorithms are appropriate tool for thermal conductivity ratio prediction. The...
A novel distributed model of the heart under normal and congestive heart failure conditions
, Article Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine ; Volume 227, Issue 4 , 2013 , Pages 362-372 ; 09544119 (ISSN) ; Jahed, M ; Sharif University of Technology
2013
Abstract
Conventional models of cardiovascular system frequently lack required detail and focus primarily on the overall relationship between pressure, flow and volume. This study proposes a localized and regional model of the cardiovascular system. It utilizes noninvasive blood flow and pressure seed data and temporal cardiac muscle regional activity to predict the operation of the heart under normal and congestive heart failure conditions. The analysis considers specific regions of the heart, namely, base, mid and apex of left ventricle. The proposed method of parameter estimation for hydraulic electric analogy model is recursive least squares algorithm. Based on simulation results and comparison...
Elimination of chromatographic and mass spectrometric problems in GC-MS analysis of Lavender essential oil by multivariate curve resolution techniques: Improving the peak purity assessment by variable size moving window-evolving factor analysis
, Article Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences ; Volume 983-984 , 2015 , Pages 83-89 ; 15700232 (ISSN) ; Moazeni Pourasil, R. S ; Sereshti, H ; Sharif University of Technology
Abstract
In analysis of complex natural matrices by gas chromatography-mass spectrometry (GC-MS), many disturbing factors such as baseline drift, spectral background, homoscedastic and heteroscedastic noise, peak shape deformation (non-Gaussian peaks), low S/N ratio and co-elution (overlapped and/or embedded peaks) lead the researchers to handle them to serve time, money and experimental efforts. This study aimed to improve the GC-MS analysis of complex natural matrices utilizing multivariate curve resolution (MCR) methods. In addition, to assess the peak purity of the two-dimensional data, a method called variable size moving window-evolving factor analysis (VSMW-EFA) is introduced and examined. The...
Chemometrics comparison of gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry Daphnia magna metabolic profiles exposed to salinity
, Article Journal of Separation Science ; Volume 41, Issue 11 , 2018 , Pages 2368-2379 ; 16159306 (ISSN) ; Garreta Lara, E ; Campos, B ; Barata, C ; Lacorte, S ; Tauler, R ; Sharif University of Technology
Wiley-VCH Verlag
2018
Abstract
The performances of gas chromatography with mass spectrometry and of comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry are examined through the comparison of Daphnia magna metabolic profiles. Gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with mass spectrometry were used to compare the concentration changes of metabolites under saline conditions. In this regard, a chemometric strategy based on wavelet compression and multivariate curve resolution–alternating least squares is used to compare the performances of gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with...