1,720,973 research outputs found
Tissue Printing and Dual Excitation Flow Cytometry for Oxidative Stress—New Tools for Reactive Oxygen Species Research in Seed Biology
No full textThe intracellular homeostasis of reactive oxygen species (ROS) and especially of superoxide anion and hydrogen peroxide participate in signaling cascades which dictate developmental processes and reactions to stresses. ROS are also biological molecules that play important roles in seed dormancy and germination. Because of their rapid reactivity, short half-life and low concentration, ROS are difficult to measure directly with high accuracy and precision. In presented work tissue printing method with image analysis and dual excitation flow cytometry (FCM) were developed for rapid detection and localization of O2•− and H2O2 in different part of seed. Tissue printing and FCM detection of ROS showed that germination of wild oat seeds was associated with the accumulation of O2•− and H2O2 in embryo (coleorhiza, radicle and scutellum), aleurone layer and coat. To verify if printing and FCM signals were specified, the detection of O2•− and H2O2 in seeds incubated in presence of O2•− generation inhibitor (DPI) or H2O2 scavenger (CAT) were examined. All results were a high level of agreement among the level of ROS derived from presented procedures with the ones created from spectrophotometric measured data. In view of the data obtained, tissue printing with image analysis and FCM are recommended as a simple and fast methods, which could help researchers to detection and level determination of ROS in the external and inner parts of the seeds
Gibberellin-like effects of KAR1 on dormancy release of Avena fatua caryopses include participation of non-enzymatic antioxidants and cell cycle activation in embryos
No full textApplication of flow cytometry with a fluorescent dye to measurement of intracellular nitric oxide in plant cells
No full textInterplay between nitric oxide, ethylene, and gibberellic acid regulating the release of Amaranthus retroflexus seed dormancy
No full textNanopriming of Barley Seeds—A Shotgun Approach to Improve Germination under Salt Stress Conditions by Regulating of Reactive Oxygen Species
No full textAbiotic stresses are the most important environmental factors affecting seed germination, and negatively affect crop production worldwide. Water availability is essential for proper seed imbibition and germination. The mechanism by which seeds can germinate in areas with high soil salinity is, however, still unclear. The present study aims to investigate the protective roles of AgNPs in alleviating stress symptoms caused by salinity exposure in barley seeds. For this purpose, different treatment combinations of seed priming with PVP-AgNPs in salinity stress conditions were used. Salt stress (150 and 200 mM) was found to reduce seed germination by 100% when compared to the control. Under NaCl concentrations, seed priming with PVP-AgNPs (40 mg L−1) only for 2 h, reduced salinity effects. Salinity resulted in increased reactive oxygen species (ROS) generation compared to the control. However, increased antioxidants in the NPs treatments, such as SOD, CAT, GR, GPX (expression at both genes, such as HvSOD, HvCAT, HvGR or HvGPX, and protein levels) and glutathione content, scavenged these ROS. Considering all of the parameters under study, priming alleviated salt stress. To summarize, seed priming with AgNPs has the potential to alleviate salinity stress via reduced ROS generation and activation of the antioxidant enzymatic system during germination
Universal mtDNA fragment for Cervidae barcoding species identification using phylogeny and preliminary analysis of machine learning approach
No full textAbstract The aim of the study was to use total DNA obtained from bone material to identify species of free-living animals based on the analysis of mtDNA fragments by molecular methods using accurate bioinformatics tools Bayesian approach and the machine learning approach. In our research, we present a case study of successful species identification based on degraded samples of bone, with the use of short mtDNA fragments. For better barcoding, we used molecular and bioinformatics methods. We obtained a partial sequence of the mitochondrial cytochrome b (Cytb) gene for Capreolus capreolus, Dama dama, and Cervus elaphus, that can be used for species affiliation. The new sequences have been deposited in GenBank, enriching the existing Cervidae mtDNA base. We have also analysed the effect of barcodes on species identification from the perspective of the machine learning approach. Machine learning approaches of BLOG and WEKA were compared with distance-based (TaxonDNA) and tree-based (NJ tree) methods based on the discrimination accuracy of the single barcodes. The results indicated that BLOG and WEKAs SMO classifier and NJ tree performed better than TaxonDNA in discriminating Cervidae species, with BLOG and WEKAs SMO classifier performing the best
Data Science and Plant Metabolomics
No full textThe study of plant metabolism is one of the most complex tasks, mainly due to the huge amount and structural diversity of metabolites, as well as the fact that they react to changes in the environment and ultimately influence each other. Metabolic profiling is most often carried out using tools that include mass spectrometry (MS), which is one of the most powerful analytical methods. All this means that even when analyzing a single sample, we can obtain thousands of data. Data science has the potential to revolutionize our understanding of plant metabolism. This review demonstrates that machine learning, network analysis, and statistical modeling are some techniques being used to analyze large quantities of complex data that provide insights into plant development, growth, and how they interact with their environment. These findings could be key to improving crop yields, developing new forms of plant biotechnology, and understanding the relationship between plants and microbes. It is also necessary to consider the constraints that come with data science such as quality and availability of data, model complexity, and the need for deep knowledge of the subject in order to achieve reliable outcomes
Necessity of gibberellin for stimulatory effect of KAR1 on germination of dormant Avena fatua L. caryopses
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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