PubMed İndeksli Yayınlar / PubMed Indexed Publications

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Browsing PubMed İndeksli Yayınlar / PubMed Indexed Publications by Publisher "Elsevier B.V."

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    Comparison of Tolerance Related Proteomic Profiles of Two Drought Tolerant Tomato Mutants Improved by Gamma Radiation
    (Elsevier B.V., 2021) ÇELİK, ÖZGE; AYAN, ALP; MERİÇ, SİNAN; ATAK, ÇİMEN
    Lycopersicon esculentum L., also known as tomato, is an important industrial plant due to its products which worth billions of dollars annually, besides its nutritional value and health benefits. In this study, we investigated the two-dimensional protein expression profiles in drought tolerant mutant plants derived from industrial 5MX12956 tomato variety by Cs-137 gamma radiation source induced mutations. Drought tolerance of mutants were evaluated and confirmed by in vivo and in vitro methods. Eleven drought responsive protein spots were identified by two-dimensional electrophoresis and MALDI-TOF-MS. Identified proteins which presented differential expression under drought conditions were clustered under six distinct groups based on their cellular functions. These clusters are ATP and carbohydrate metabolism, mRNA processing and protein phosphorylation, oxidation reduction and stress response, signaling and supporting cytoskeleton. Our results contributed proteomic data to drought tolerance of our tomato mutants which were originated from drought susceptible 5MX12956 variety. They may also facilitate basis for future investigations into the genetic and physiological aspects of this tolerance. © 2021 Elsevier B.V.
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    Semi-Quantitative Chemometric Models for Characterization of Mixtures of Sugars Using Infrared Spectral Data
    (Elsevier B.V., 2024) Brito, Anna Luiza B.; Cardoso, Inês F.; Viegas, Luís P.; FAUSTO, RUI
    Sugars (saccharides) are sweet-tasting carbohydrates that are abundant in foods and play very important roles in living organisms, particularly as sources and stores of energy, and as structural elements in cellular membranes. They are desirable therapeutic targets, as they participate in multiple metabolic processes as fundamental elements. However, the physicochemical characterization of sugars is a challenging task, mostly due to the structural similarity shared by the large diversity of compounds of this family. The need for fast, accurate enough, and cost-effective analytical methods for these substances is of extreme relevance, in particular because of the recently increasing importance of carbohydrates in Medicine and food industry. With this in view, this work focused on the development of chemometric models for semi-quantitative analysis of samples of different types of sugars (glucose, galactose, mannitol, sorbose and fructose) using infrared spectra as data, as an example of application of a novel approach, where the Principal Component Analysis (PCA) score plots are used to estimate the composition (weight-%) of the mixtures of the sugars. In these plots, polygonal geometric shapes emerge in the vectorial space of the most significant principal components, that allow grouping different types of samples on the vertices, edges, faces and interior of the polygons according to the composition of the samples. This approach was applied successfully to mixtures of up to 5 sugars and shown to appropriately extract the compositional information from the hyper-redundant complex spectral data. Thought the method has been applied here to a specific problem, it shall be considered as a general procedure for the semi-quantitative analysis of other types of mixtures and applicable to other types of data reflecting their composition. In fact, the methodology appears as an efficient tool to solve three main general problems: (i) use hyper-redundant (in variables) data, as spectral information, directly and with minimum pre-treatment, to evaluate semi-quantitatively the composition of mixtures; (ii) do this for systems which produce data that can be considered rather similar; and (iii) do it for a number of substances present in the mixtures that might be greater than that usually considered in chemistry, which in general is limited to 3 components. In addition, this work also demonstrates that, similarly to the developed analysis based on the PCA score plots, the Multivariate Curve Resolution with Alternating Least Squares (MCR-ALS) chemometric method can also be used successfully for the qualitative (when used without any previous knowledge of the components present in the samples) or semi-quantitative (when the pure components spectral profiles are provided as references) analyses of mixtures of (at least) up to 5 distinct sugars.