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    Evaluation of the effect of organic pollutants exposure on the antioxidant activity, total phenolic and total flavonoid content of lettuce (Lactuca sativa L.) using UV–Vis spectrophotometry and chemometrics

    , Article Microchemical Journal ; Volume 170 , 2021 ; 0026265X (ISSN) Nikzad, N ; Parastar, H ; Sharif University of Technology
    Elsevier Inc  2021
    In the present contribution, the effects of different contaminants of emerging concerns (CECs), including parabens, drugs, and polycyclic aromatic hydrocarbons (PAHs) on antioxidant activity of Lactuca sativa L. in different concentration levels (10–500 µg L−1) were evaluated using ultraviolet–visible (UV–Vis) spectrophotometry combined with chemometric techniques. The extracts of lettuce samples were investigated for the antioxidant activity (AA), total phenolic content (TPC), and total flavonoid content (TFC) after 39 days of planting and 14 days of exposure. Then, the spectroscopic data were arranged in two different data matrices, including (i) the control lettuce samples and PAHs... 

    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
    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... 

    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
    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....