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NIX knockdown abrogates this upregulation of glycolysis, mitophagy, and secretion of pro-inflammatory cytokines in BCG infected cells, indicating that mycobacterial infection-induced immunometabolic changes are executed via NIX mediated mitophagy and are essential for macrophage differentiation and resolution of infection.Excess moisture in the form of waterlogging or full submergence can cause severe conditions of hypoxia or anoxia compromising several physiological and biochemical processes. A decline in photosynthetic rate due to accumulation of ROS and damage of leaf tissue are the main consequences of excess moisture. These effects compromise crop yield and quality, especially in sensitive species, such as soybean (Glycine max.). Phytoglobins (Pgbs) are expressed during hypoxia and through their ability to scavenge nitric oxide participate in several stress-related responses. Soybean plants over-expressing or suppressing the Pgb1 gene GmPgb1 were generated and their ability to cope with waterlogging and full submergence conditions was assessed. Plants over-expressing GmPgb1 exhibited a higher retention of photosynthetic rate during waterlogging and survival rate during submergence relative to wild type plants. The same plants also had lower levels of ROS due to a reduction in expression of Respiratory Burst Oxidase Homologs (RBOH), components of the NADPH oxidase enzyme, and enhanced antioxidant system characterized by higher expression of catalases (CAT) and superoxide dismutase (SOD), as well as elevated expression and activity of ascorbate peroxidase (APX). Plants over-expressing GmPgb1 also exhibited an expression pattern of aquaporins typical of excess moisture resilience. This was in contrast to plants downregulating GmPgb1 which were characterized by the lowest photosynthetic rates, higher ROS signal, and reduced expression and activities of many antioxidant enzymes. Results from these studies suggest that GmPgb1 exercises a protective role during conditions of excess moisture with similar mechanisms operating during waterlogging and submergence.Poa pratensis is a perennial turfgrass used worldwide. However, shortage of irrigation and drought induced by climate change adversely affect plant growth and turf quality. Cuticular wax covers plant aerial parts and plays important roles in decreasing plant water loss under drought-stressed conditions. Previous research proposed two candidate genes that were involved in wax very-long-chain alkane biosynthesis based on the transcriptome of Poa pratensis leaf. Here, one of the candidate genes, PpCER1-2 was further characterized. A subcellular localization study revealed that PpCER1-2 was localized on the endoplasmic reticulum. [https://www.selleckchem.com/products/epalrestat.html Epalrestat] The expression of PpCER1-2 could be induced by drought and salt stresses. Overexpression of PpCER1-2 in Brachypodium distachyon increased the alkane amount, whereas decreased the amounts of primary alcohols and total wax. The relative abundance of C25 and C27 alkane and C26 aldehyde increased significantly, but the relative abundance of C29 and C31 alkane and C28 aldehyde decreased. Meanwhile, PpCER1-2 overexpression lines exhibited reduced cuticle permeability and enhanced drought tolerance. These results suggested that PpCER1-2 relatively promoted alkane biosynthesis by converting more very long chain fatty acids precursors into the decarbonylation pathway from the acyl-reduction pathway. Taken together, our data suggest that PpCER1-2 is involved in wax alkane biosynthesis in P. pratensis and plays important roles in improving plant drought tolerance.We outline recent developments in artificial intelligence (AI) and machine learning (ML) techniques for integrative structural biology of intrinsically disordered proteins (IDP) ensembles. IDPs challenge the traditional protein structure-function paradigm by adapting their conformations in response to specific binding partners leading them to mediate diverse, and often complex cellular functions such as biological signaling, self-organization and compartmentalization. Obtaining mechanistic insights into their function can therefore be challenging for traditional structural determination techniques. Often, scientists have to rely on piecemeal evidence drawn from diverse experimental techniques to characterize their functional mechanisms. Multiscale simulations can help bridge critical knowledge gaps about IDP structure-function relationships-however, these techniques also face challenges in resolving emergent phenomena within IDP conformational ensembles. We posit that scalable statistical inference techniques can effectively integrate information gleaned from multiple experimental techniques as well as from simulations, thus providing access to atomistic details of these emergent phenomena.We evaluate the ability of the Canberra Alpha Beta Environmental Continuous Air Monitor (ECAM) to detect and quantify airborne radiological contamination. The ECAM essentially consists of a passively-implanted planar silicon (PIPS) detector near a particulate filter through which outside air is pulled. Three years' worth of background measurements on three different systems were assessed and calibrated to compensate for changing conditions and develop an average background response for the systems. The ECAM was also exposed to several radionuclides of interest, including 235U and 239Pu, to measure the response to alpha and beta particle sources. Both standard calibration sources and custom sources consisting of aqueous radioisotope solutions absorbed into clean filters. The ECAM responses to these sources were then scaled to quantities of interest and injected on the averaged background. Various alarm algorithms were evaluated on the source-injected spectra for minimum detectable air concentration for a given false alarm rate. Even in the worst case, the ECAM was able to detect radionuclides of interest at 10% of the Derived Response Level (DRL) for each isotope based on early-phase Protective Action Guides (PAG). Quantification of the radionuclides was also evaluated for the various algorithms, with mixed results, but overall clearly indicating the optimal algorithms for alpha and beta particle alarm and quantification. Finally, a limited evaluation of the beta particle detection efficiency points to a detection energy threshold of approximately 290 keV.