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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Catabolic pathway acquisition by rhizosphere bacteria readily enables growth with a root exudate component but does not affect root colonization

Horizontal gene transfer (HGT) is a fundamental evolutionary process that plays a key role in bacterial evolution. The likelihood of a successful transfer event is expected to depend on the precise balance of costs and benefits resulting from pathway acquisition. Most experimental analyses of HGT have focused on phenotypes that have large fitness benefits under appropriate selective conditions, such as antibiotic resistance. However, many examples of HGT involve phenotypes that are predicted to provide smaller benefits, such as the ability to catabolize additional carbon sources. We have experimentally simulated the consequences of one such HGT event in the laboratory, studying the effects of transferring a pathway for catabolism of the plant-derived aromatic compound salicyl alcohol between rhizosphere isolates from the Pseudomonas genus. We find that pathway acquisition enables rapid catabolism of salicyl alcohol with only minor disruptions to the existing metabolic and regulatory networks of the new host. However, this new catabolic potential does not confer a measurable fitness advantage during competitive growth in the rhizosphere. We conclude that the phenotype of salicyl alcohol catabolism is readily transferable but is selectively neutral under environmentally relevant conditions. We propose that this condition is common and that HGT of many pathways will be self-limiting because the selective benefits are small.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Urban morphology and urban water demand evolution in the Los Angeles region

Detailed description of the dataset sources used in this study, the experimental workflow, and plotting for the paper figures provided at the associated GitHub Meta Repo: https://github.com/IMMM-SFA/Ferencz_et_al_2024_ERL The future water demand projections from this study are hypothetical future water demands that reflect the population and urban land cover changes represented by the scenarios considered. The intent and emphasis of this work is investigating the interactions between population change, evolution of urban morphology, and water demand. These projections are not meant to be likely future demands for specific water providers or the LA region and should not be interpreted as such. The folders contain input and output data for each step of the "Recreate my Experiment" workflow described in the associated GitHub meta-repository as well as data used for plotting Figures for the paper that this dataset supports. Description of each folder's contents and use: Step_1a: Inputs to the associated python script provided on the GitHub repo. Step_1b: Inputs (downscaled population rasters) used by the associated python script provided on the GitHub repo. Original 1-km squared rasters that were downscaled also provided. Step_1c: Urban growth projection rasters corresponding to SSP3 and SSP5 population scenarios are provided in separate subfolders as well as the water provider boundaries used for analysis. Outputs of data processing also provided. Associated python script provided on GitHub. Step_1d: Description of Inputs used by the QGIS Model Builder GUI that automates geospatial processing and clipping the of the high-resolution 60 cm land cover data for each urban land class footprint within a defined polygon boundary. The Model Builder is provided on the GitHub repo and can be used by QGIS. The outputs of this step are in "Clipped Provider Hi Res Landcover". If the user wants to use The Model Builder for different regions of LA or to test our outputs, they will need to download the hi resolution landcover raster listed in the Readme and in Ref [2] of the GitHub Page. Step_1e: All necessary inputs to generate average monthly demand over the 2017-2021 period and the minimum and maximum demands over the 2014-2021 for each water provider. Associated python scripts are on GitHub. Step 2: Output data about land cover metrics (areas and fractions) for each urban land class for each water provider. Associated python script on GitHub. Uses outputs from Step 1d "Clipped Provider Hi Res Landcover" Step 3: Both the Inputs for and Outputs from the urban projection raster analysis Python script on GitHub. The inputs are urban land class rasters for specific SSP and zoning scenarios (low, medium, high) from Step 1c. The outputs are rasters of urban pixels that were converted to a higher land class and the number of land class units that changed (Values of 1, 2, or 3). For example, a value of 2 could be LC 21 -> 23 or LC 22 -> 24. These maps are label "intensification." The other outputs are "urban growth" rasters showing the conversion of non urban to urban land, which are indicated by pixel values of 1. These are used for the urban growth change maps in Figure 3. Step 4: Output projections of indoor and outdoor annual and monthly demands for each water provider for the average, minimum, and maximum monthly demand scenarios for each of the four urban growth scenarios (SSP3 med, SSP5 low, SSP5 med, and SSP5 high). The outputs also include metrics on each water provider used for the demand sensitivity analysis presented in Figure 8. Outputs from Step 4 are used for Figures 4 - 8 of the paper. Figures: This folder has data used for plotting Figures 1 through 5, and 8. Data for Figures 6 and 7 are sourced directly from folders associated with the Processing and Analysis Steps 1 - 4. The GitHub meta repository provides descriptions of how each figure was made and the associated plotting scripts used.

Los Angeles↗
DOE OSTI2024

Urban morphology and urban water demand evolution in the Los Angeles region

Detailed description of the dataset sources used in this study, the experimental workflow, and plotting for the paper figures provided at the associated GitHub Meta Repo: https://github.com/IMMM-SFA/Ferencz_et_al_2024_ERL The future water demand projections from this study are hypothetical future water demands that reflect the population and urban land cover changes represented by the scenarios considered. The intent and emphasis of this work is investigating the interactions between population change, evolution of urban morphology, and water demand. These projections are not meant to be likely future demands for specific water providers or the LA region and should not be interpreted as such. The folders contain input and output data for each step of the "Recreate my Experiment" workflow described in the associated GitHub meta-repository as well as data used for plotting Figures for the paper that this dataset supports. Description of each folder's contents and use: Step_1a: All necessary inputs to the associated python script provided on the GitHub repo. Step_1b: All necessary inputs (downscaled population rasters) used by the associated python script provided on the GitHub repo. Original 1-km squared rasters that were downscaled also provided. Step_1c: Urban growth projection rasters corresponding to SSP3 and SSP5 population scenarios are provided in separate subfolders as well as the water provider boundaries used for analysis. Outputs of data processing also provided. Associated python script provided on GitHub. Step_1d: Description of Inputs used by the QGIS Model Builder GUI that automates geospatial processing and clipping the of the high resolution land cover data for each urban land class footprint within a defined polygon boundary. The Model Builder is provided on the GitHub repo and can be used by QGIS. The outputs of this step are in "Clipped Provider Hi Res Landcover". If the user wants to use The Model Builder for different regions of LA or two test our outputs, they will need to download the hi resolution landcover raster listed in the Readme and in Ref [2] of the GitHub Page. Step_1e: All necessary inputs to generate average monthly demand for each water provider. Associated python script on GitHub. Step 2: Output data about land cover metrics (areas and fractions) for each urban land class for each water provider. Associated python script on GitHub. Uses outputs from Step 1d "Clipped Provider Hi Res Landcover" Step 3: Inputs for and Outputs from the urban projection raster analysis Python script on GitHub. The outputs are rasters of urban pixels that were converted to a higher land class and the number of land class units that changed (Values of 1, 2, or 3). For example, a value of 2 could be LC 21 -> 23 or LC 22 -> 24. These maps are label "intensification." The other outputs are "urban growth" rasters showing the conversion of non urban to urban land, which are indicated by pixel values of 1. Step 4: Output projections of indoor and outdoor annual and monthly demands for each water provider. These are used for Figures 4 - 7 of the paper. Figures: This folder has data used for plotting Figures 1 through 5. Data for Figures 6 and 7 are sourced directly from folders associated with the Processing and Analysis Steps 1 - 4 and the plotting scripts for Figures 6 and 7 are commented with what folder paths are needed to generate the figures. The GitHub page provides descriptions of how each figure was made and the associated plotting scripts used.

Los Angeles↗
DOE OSTI2024

AtDGCR14L contributes to salt-stress tolerance via regulating pre-mRNA splicing in Arabidopsis

In plants, the pre-mRNA alternative splicing has been demonstrated to be a crucial tier that regulates gene expression in response to salt stress. However, the underlying mechanisms remain elusive. Here, in this study, we studied the roles of DIGEORGE-SYNDROME CRITICAL REGION 14-like (AtDGCR14L) in regulating pre-mRNA splicing and salt stress tolerance. We discovered that Arabidopsis AtDGCR14L is required for maintaining plant salt stress tolerance and the constitutively spliced and active isoforms of important stress- and/or abscisic acid (ABA)-responsive genes. We also identified the interaction between AtDGCR14L and splicing factor U1-70k, which needs a highly conserved three amino acid (TWG) motif in DGCR14. Different from wild-type AtDGCR14L, the overexpression of TWG-substituted AtDGCR14L mutant did not change salt stress tolerance or pre-mRNA splicing of stress/ABA-responsive genes. Additionally, SWITCH3A (SWI3A) is a core subunit of the SWI/SUCROSE NONFERMENTING (SWI/SNF) chromatin-remodeling complexes. We found that SWI3A, whose splicing depends on AtDGCR14L, actively enhances salt stress tolerance. These results revealed that AtDGCR14L may play an essential role in crosstalk between plant salt-stress response and pre-mRNA splicing mechanisms. We also unveiled the potential role of SWI3A in controlling salt stress tolerance. The TWG motif in the intrinsically disordered region of AtDGCR14L is highly conserved and crucial for DGCR14 functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Structural and magnetic properties of CoTeMo⁢O 6

Here, we have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMo⁢O 6 . In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi et al., J. Solid State Chem. 182, 3232 (2009)], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMo⁢O 6 , with one occurring at 𝐻 𝑐⁢1 =460 Oe along the 𝑎 axis, and the other at 𝐻 𝑐⁢2 =1.16 T with the field along the 𝑏 axis. The values of 𝐻 𝑐⁢1 and 𝐻 𝑐⁢2 exhibit strong angular dependence and diverge with different rates as the applied field is rotated 90 ° within the 𝑎⁢𝑏 plane. This reflects the distinct nature of these transitions, which is further supported by the different critical behavior of 𝐻 𝑐⁢1 and 𝐻 𝑐⁢2 , characterized by the values of 𝛾, in the function of 𝐻 𝑐 =𝐻 0 ⁡(1−𝑇/𝑇 𝑐 ) 𝛾 . Furthermore, we have demonstrated that there exist structural and magnetic twin domains in CoTeMo⁢O 6 that strongly affect the experimental measurement of their macroscopic properties. Intriguingly, these twin domains can be related to the orthorhombicity/chirality of the crystal structure with the space group 𝑃⁢2 1 ⁢2 1⁢ 2. We further explored the magnetic and structural domains with uniaxial pressure and polarized light microscopy. Our results suggest that CoTeMo⁢O 6 could be used as a unique platform for investigating the intriguing physics involving intertwined degrees of freedom. The tunability of the underlying domain distribution and its strong anisotropy could also be useful for developing functional devices and applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗