scholarly journals Combined multivariate analysis and machine learning reveals a predictive module of metabolic stress response in Arabidopsis thaliana

2018 ◽  
Vol 14 (6) ◽  
pp. 437-449 ◽  
Author(s):  
Lisa Fürtauer ◽  
Alice Pschenitschnigg ◽  
Helene Scharkosi ◽  
Wolfram Weckwerth ◽  
Thomas Nägele
Keyword(s):  
Machine Learning ◽  
Arabidopsis Thaliana ◽  
Multivariate Analysis ◽  
Stress Response ◽  
Environmental Conditions ◽  
Metabolic Stress ◽  
Molecular Core ◽  
Core Module ◽  
Biochemical Regulation

A stress-responsive molecular core module was identified which supports the prediction of complex biochemical regulation under changing environmental conditions.

scholarly journals Brain Activity-Based Metrics for Assessing Learning States in VR under Stress among Firefighters: An Explorative Machine Learning Approach in Neuroergonomics

2021 ◽  
Vol 11 (7) ◽  
pp. 885
Author(s):  
Maher Abujelala ◽  
Rohith Karthikeyan ◽  
Oshin Tyagi ◽  
Jing Du ◽  
Ranjana K. Mehta
Keyword(s):  
Machine Learning ◽  
Environmental Conditions ◽  
Brain Activity ◽  
Memory Task ◽  
Classification Problem ◽  
Brain Regions ◽  
Training Data ◽  
Information Encoding ◽  
Machine Learning Approach ◽  
Encoding And Retrieval

The nature of firefighters` duties requires them to work for long periods under unfavorable conditions. To perform their jobs effectively, they are required to endure long hours of extensive, stressful training. Creating such training environments is very expensive and it is difficult to guarantee trainees’ safety. In this study, firefighters are trained in a virtual environment that includes virtual perturbations such as fires, alarms, and smoke. The objective of this paper is to use machine learning methods to discern encoding and retrieval states in firefighters during a visuospatial episodic memory task and explore which regions of the brain provide suitable signals to solve this classification problem. Our results show that the Random Forest algorithm could be used to distinguish between information encoding and retrieval using features extracted from fNIRS data. Our algorithm achieved an F-1 score of 0.844 and an accuracy of 79.10% if the training and testing data are obtained at similar environmental conditions. However, the algorithm’s performance dropped to an F-1 score of 0.723 and accuracy of 60.61% when evaluated on data collected under different environmental conditions than the training data. We also found that if the training and evaluation data were recorded under the same environmental conditions, the RPM, LDLPFC, RDLPFC were the most relevant brain regions under non-stressful, stressful, and a mix of stressful and non-stressful conditions, respectively.

scholarly journals Alternative Oxidase Involvement in Cold Stress Response of Arabidopsis thaliana fad2 and FAD3+ Cell Suspensions Altered in Membrane Lipid Composition

2007 ◽  
Vol 48 (6) ◽  
pp. 856-865 ◽  
Author(s):  
Ana Rita Matos ◽  
Cécile Hourton-Cabassa ◽  
Dominique Ciçek ◽  
Nathalie Rezé ◽  
Joao Daniel Arrabaça ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Stress Response ◽  
Cold Stress ◽  
Lipid Composition ◽  
Alternative Oxidase ◽  
Membrane Lipid ◽  
Cell Suspensions ◽  
Membrane Lipid Composition

scholarly journals Grain filling parameters in high-yielding ns wheat cultivars

2008 ◽  
pp. 53-58
Author(s):  
Milka Brdar ◽  
Marija Kraljevic-Balalic ◽  
Borislav Kobiljski
Keyword(s):  
Multivariate Analysis ◽  
Nonlinear Regression ◽  
Environmental Conditions ◽  
Dry Weight ◽  
Grain Filling ◽  
Grain Weight ◽  
Cultivar Differences ◽  
Wheat Cultivars ◽  
Estimated Parameters ◽  
Grain Filling Duration

Grain yield of wheat is dependent on grain weight, which is the result of grain filling duration and rate. The study was undertaken to examine the relation between grain weight and rate and duration of grain filling in five high-yielding NS wheat cultivars. Stepwise multivariate analysis of nonlinear regression estimated grain filling parameters was used to examine cultivar differences in grain filling. On the basis of three-year average, the highest grain dry weight had cultivar Renesansa, and the lightest grains were measured for cultivar Evropa 90. Stepwise multivariate analysis indicated that all three nonlinear regression estimated parameters (grain weight, rate and duration of grain filling) were equally important in characterizing the grain filling curves of the cultivars studied, although sequence of their significance varied in different years, which is probably caused by different environmental conditions in three years of experiment.

scholarly journals Cloning and Functional Identification of Phosphoethanolamine Methyltransferase in Soybean (Glycine max)

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaomin Ji ◽  
Xiaoyue Wu ◽  
Wei Chen ◽  
Qianhui Yuan ◽  
Yixin Shen ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Glycine Max ◽  
Stress Response ◽  
Cell Metabolism ◽  
Plant Stress ◽  
Lipid Synthesis ◽  
Normal Growth ◽  
Functional Identification ◽  
Short Root ◽  
Response Elements

Phosphoethanolamine methyltransferase (PEAMT), a kind of S-adenosylmethionine-dependent methyltransferases, plays an essential role in many biological processes of plants, such as cell metabolism, stress response, and signal transduction. It is the key rate-limiting enzyme that catalyzes the three-step methylation of ethanolamine-phosphate (P-EA) to phosphocholine (P-Cho). To understand the unique function of PEAMT in soybean (Glycine max) lipid synthesis, we cloned two phosphoethanolamine methyltransferase genes GmPEAMT1 and GmPEAMT2, and performed functional identification. Both GmPEAMT1 and GmPEAMT2 contain two methyltransferase domains. GmPEAMT1 has the closest relationship with MtPEAMT2, and GmPEAMT2 has the closest relationship with CcPEAMT. GmPEAMT1 and GmPEAMT2 are located in the nucleus and endoplasmic reticulum. There are many light response elements and plant hormone response elements in the promoters of GmPEAMT1 and GmPEAMT2, indicating that they may be involved in plant stress response. The yeast cho2 opi3 mutant, co-expressing Arabidopsis thaliana phospholipid methyltransferase (PLMT) and GmPEAMT1 or GmPEAMT2, can restore normal growth, indicating that GmPEAMTs can catalyze the methylation of phosphoethanolamine to phosphate monomethylethanolamine. The heterologous expression of GmPEAMT1 and GmPEAMT2 can partially restore the short root phenotype of the Arabidopsis thaliana peamt1 mutant, suggesting GmPEAMTs have similar but different functions to AtPEAMT1.

Identification of IAA-regulated genes in Pseudomonas syringae pv. tomato strain DC3000

2021 ◽  
Author(s):  
Arnaud-Thierry Djami-Tchatchou ◽  
Zipeng Alex Li ◽  
Paul Stodghill ◽  
Melanie J. Filiatrault ◽  
Barbara N. Kunkel
Keyword(s):  
Gene Expression ◽  
Arabidopsis Thaliana ◽  
Acetic Acid ◽  
Stress Response ◽  
Pseudomonas Syringae ◽  
Plant Pathogen ◽  
Type Iii Secretion ◽  
Plant Hormone ◽  
Indole 3 Acetic Acid ◽  
Exogenous Iaa

The auxin indole-3-acetic acid (IAA) is a plant hormone that not only regulates plant growth and development but also plays important roles in plant-microbe interactions. We previously reported that IAA alters expression of several virulence-related genes in the plant pathogen Pseudomonas syringae pv. tomato strain DC3000 ( Pto DC3000). To learn more about the impact of IAA on regulation of Pto DC3000 gene expression we performed a global transcriptomic analysis of bacteria grown in culture, in the presence or absence of exogenous IAA. We observed that IAA repressed expression of genes involved in the Type III secretion (T3S) system and motility and promoted expression of several known and putative transcriptional regulators. Several of these regulators are orthologs of factors known to regulate stress responses and accordingly expression of several stress response-related genes was also upregulated by IAA. Similar trends in expression for several genes were also observed by RT-qPCR. Using an Arabidopsis thaliana auxin receptor mutant that accumulates elevated auxin, we found that many of the P. syringae genes regulated by IAA in vitro were also regulated by auxin in planta . Collectively the data indicate that IAA modulates many aspects of Pto DC3000 biology, presumably to promote both virulence and survival under stressful conditions, including those encountered in or on plant leaves. IMPORTANCE Indole-3-acetic acid (IAA), a form of the plant hormone auxin, is used by many plant-associated bacteria as a cue to sense the plant environment. Previously, we showed that IAA can promote disease in interactions between the plant pathogen Pseudomonas syringae strain Pto DC000 and one of its hosts, Arabidopsis thaliana . However, the mechanisms by which IAA impacts the biology of Pto DC3000 and promotes disease are not well understood. Here we demonstrate that IAA is a signal molecule that regulates gene expression in Pto DC3000. The presence of exogenous IAA affects expression of over 700 genes in the bacteria, including genes involved in Type III secretion and genes involved in stress response. This work offers insight into the roles of auxin promoting pathogenesis.

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