Bradyrhizobium japonicum, a gram-negative soil bacterium that establishes an N(2)-fixing symbiosis with its legume host soybean (Glycine max), has been used as a symbiosis model system. Using a sensitive geLC-MS/MS proteomics approach, we report the identification of 2315 B. japonicum strain USDA110 proteins (27.8% of the theoretical proteome) that are expressed 21 days post infection in symbiosis with soybean cultivated in growth chambers, substantially expanding the previously known symbiosis proteome. Integration of transcriptomics data generated under the same conditions (2780 expressed genes) allowed us to compile a comprehensive expression profile of B. japonicum during soybean symbiosis, which comprises 3587 genes/proteins (43% of the predicted B. japonicum genes/proteins). Analysis of this data set revealed both the biases and the complementarity of these global profiling technologies. A functional classification and pathway analysis showed that most of the proteins involved in carbon and nitrogen metabolism are expressed, including a complete set of tricarboxylic acid cycle enzymes, several gluconeogenesis and pentose phosphate pathway enzymes, as well as several proteins that were previously not considered to be present during symbiosis. Congruent results were obtained for B. japonicum bacteroids harvested from soybeans grown under field conditions.
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http://dx.doi.org/10.1002/pmic.200900710 | DOI Listing |
Conventional control charts track changes in the process by using predefined process parameters. Conversely, during online monitoring, adaptive control charts modify the process parameters. To improve the process dispersion monitoring in various operational environments, this study presents an adaptive exponentially weighted moving average (AEWMA) control chart based on support vector regression (SVR).
View Article and Find Full Text PDFBiomarkers that aid in early detection of neurodegeneration are needed to enable early symptomatic treatment and enable identification of people who may benefit from neuroprotective interventions. Increasing evidence suggests that sleep biomarkers may be useful, given the bi-directional relationship between sleep and neurodegeneration and the prominence of sleep disturbances and altered sleep architectural characteristics in several neurodegenerative disorders. This study aimed to demonstrate that sleep can accurately characterize specific neurodegenerative disorders (NDD).
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December 2024
Department of Mathematics, University of Gujrat, Gujrat, 50700, Pakistan.
This study is the application of a recurrent neural networks with Bayesian regularization optimizer (RNNs-BRO) to analyze the effect of various physical parameters on fluid velocity, temperature, and mass concentration profiles in the Darcy-Forchheimer flow of propylene glycol mixed with carbon nanotubes model across a stretched cylinder. This model has significant applications in thermal systems such as in heat exchangers, chemical processing, and medical cooling devices. The data-set of the proposed model has been generated with variation of various parameters such as, curvature parameter, inertia coefficient, Hartmann number, porosity parameter, Eckert number, Prandtl number, radiation parameter, activation energy variable, Schmidt number and reaction rate parameter for different scenarios.
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December 2024
Westlake Center for Intelligent Proteomics, Westlake Laboratory of Life Sciences and Biomedicine, No. 18 Shilongshan Road, Hangzhou, 310024, China.
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December 2024
Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
Abscisic acid (ABA) is a crucial phytohormone that regulates plant growth and stress responses. While substantial knowledge exists about transcriptional regulation, the molecular mechanisms underlying ABA-triggered translational regulation remain unclear. Recent advances in deep sequencing of ribosome footprints (Ribo-seq) enable the mapping and quantification of mRNA translation efficiency.
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