Publications by authors named "T I Savchenko"

Article Synopsis
  • A transformation protocol using dual selection (fluorescent protein and herbicide resistance) was applied to create transgenic emmer and bread wheat plants aimed at increasing the production of the stress hormone jasmonates through gene overexpression.
  • The gene expression affected the growth negatively, leading to issues like reduced leaf length and fewer grains per spike in both wheat species, with a particularly severe impact on emmer wheat.
  • Among the genes tested, overexpressing one specific gene significantly enhanced levels of jasmonates, particularly in emmer wheat, but also brought about detrimental effects on plant size and reproductive success.
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In light of recent climate change, with its rising temperatures and precipitation changes, we are facing the need to increase the valuable crop's tolerance against unfavorable environmental conditions. Emmer wheat is a cereal crop with high nutritional value. We investigated the possibility of improving the stress tolerance of emmer wheat by activating the synthesis of the stress hormone jasmonate by overexpressing two genes of the jasmonate biosynthetic pathway from , () and ().

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12-Oxophytodienoate reductase is the enzyme involved in the biosynthesis of phytohormone jasmonates, which are considered to be the major regulators of plant tolerance to biotic challenges, especially necrotrophic pathogens. However, we observe compromised tolerance to the necrotrophic fungal pathogen in transgenic hexaploid bread wheat and tetraploid emmer wheat plants overexpressing gene from , while in Arabidopsis plants themselves, endogenously produced and exogenously applied jasmonates exert a strong protective effect against . Exogenous application of methyl jasmonate on hexaploid and tetraploid wheat leaves suppresses tolerance to and induces the formation of chlorotic damages.

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The aim of the study is to increase the functional efficiency of machine learning decision support system (DSS) for the diagnosis of oncopathology on the basis of tissue morphology. The method of hierarchical information-extreme machine learning of diagnostic DSS is offered. The method is developed within the framework of the functional approach to modeling of natural intelligence cognitive processes at formation and acceptance of classification decisions.

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Understanding chemical reactivity and magnetism of 3d transition metal nanoparticles is of fundamental interest for applications in fields ranging from spintronics to catalysis. Here, we present an atomistic picture of the early stage of the oxidation mechanism and its impact on the magnetism of Co nanoparticles. Our experiments reveal a two-step process characterized by (i) the initial formation of small CoO crystallites across the nanoparticle surface, until their coalescence leads to structural completion of the oxide shell passivating the metallic core; (ii) progressive conversion of the CoO shell to CoO and void formation due to the nanoscale Kirkendall effect.

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