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At least 379 records · Page 21

A core of cell wall proteins functions in wall integrity responses in Arabidopsis thaliana

Abstract Cell walls surround all plant cells, and their composition and structure are tightly regulated to maintain cellular and organismal homeostasis. In response to wall damage, the cell wall integrity (CWI) system is engaged to ameliorate effects on plant growth. Despite the central role CWI plays in plant development, our current understanding of how this system functions at the molecular level is limited. Here, we investigated the transcriptomes of etiolated seedlings of mutants of Arabidopsis thaliana with defects in three major wall polysaccharides, pectin ( quasimodo2 ), cellulose ( cellulose synthase3 je5 ), and xyloglucan ( xyloglucan xylosyltransferase1 and 2 ), to probe whether changes in the expression of cell wall‐related genes occur and are similar or different when specific wall components are reduced or missing. Many changes occurred in the transcriptomes of pectin‐ and cellulose‐deficient plants, but fewer changes occurred in the transcriptomes of xyloglucan‐deficient plants. We hypothesize that this might be because pectins interact with other wall components and/or integrity sensors, whereas cellulose forms a major load‐bearing component of the wall; defects in either appear to trigger the expression of structural proteins to maintain wall cohesion in the absence of a major polysaccharide. This core set of genes functioning in CWI in plants represents an attractive target for future genetic engineering of robust and resilient cell walls.

59 BASIC BIOLOGICAL SCIENCES↗

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Analysis and visualization of energy densities. II. Insights from linear-response time-dependent density functional theory calculations

Inspired by the analysis of Kohn–Sham energy densities by Nakai and coworkers, we extended the energy density analysis to linear-response time-dependent density functional theory (LR-TDDFT) calculations. Using ethylene–tetrafluoroethylene and oxyluciferin–water complexes as examples, distinctive distribution patterns were demonstrated for the excitation energy densities of local excitations (within a molecular fragment) and charge-transfer excitations (between molecular fragments). It also provided a simple way to compute the effective energy of both hot carriers (particle and hole) from charge-transfer excitations via an integration of the excitation energy density over the donor and acceptor grid points.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Non-TZF Protein AtC3H59/ZFWD3 Is Involved in Seed Germination, Seedling Development, and Seed Development, Interacting with PPPDE Family Protein Desi1 in Arabidopsis

Despite increasing reports on the function of CCCH zinc finger proteins in plant development and stress response, the functions and molecular aspects of many non-tandem CCCH zinc finger (non-TZF) proteins remain uncharacterized. AtC3H59/ZFWD3 is an Arabidopsis non-TZF protein and belongs to the ZFWD subfamily harboring a CCCH zinc finger motif and a WD40 domain. In this study, we characterized the biological and molecular functions of AtC3H59, which is subcellularly localized in the nucleus. The seeds of AtC3H59-overexpressing transgenic plants (OXs) germinated faster than those of wild type (WT), whereas atc3h59 mutant seeds germinated slower than WT seeds. AtC3H59 OX seedlings were larger and heavier than WT seedlings, whereas atc3h59 mutant seedlings were smaller and lighter than WT seedlings. Moreover, AtC3H59 OX seedlings had longer primary root length than WT seedlings, whereas atc3h59 mutant seedlings had shorter primary root length than WT seedlings, owing to altered cell division activity in the root meristem. During seed development, AtC3H59 OXs formed larger and heavier seeds than WT. Using yeast two-hybrid screening, we isolated Desi1, a PPPDE family protein, as an interacting partner of AtC3H59. AtC3H59 and Desi1 interacted via their WD40 domain and C-terminal region, respectively, in the nucleus. Taken together, our results indicate that AtC3H59 has pleiotropic effects on seed germination, seedling development, and seed development, and interacts with Desi1 in the nucleus via its entire WD40 domain. To our knowledge, this is the first report to describe the biological functions of the ZFWD protein and Desi1 in Arabidopsis.

59 BASIC BIOLOGICAL SCIENCES↗

Tailoring Crosslinks through Time─A Paradigm for Tough Hydrogels

The multidisciplinary applications of hydrogels have motivated a thorough exploration of the relationship between their structural and mechanical properties, i.e., spatial structure–function relationships, with particular regard to strength and toughness. While this approach has driven fundamental advancements in the design of robust hydrogel structures, further complementary perspectives are needed to enable holistic, rational design schemes that integrate considerations such as fabrication and advanced functions like response and adaptation. To these ends, this review focuses on the dynamics of temporal-function relationships and their fundamental bases in order to highlight how the dynamic regulation of polymer interactions programs: 1) polymer assembly and material structure; 2) response to deformation and fracture behavior; 3) dynamic modulation of properties and structural remodeling/self-healing. Here, by exploring this intersection of hydrogel formation, function, and remodeling, this review seeks to shed light on the fundamental relationship between molecular structure, material assembly, and performance in order to connect the emerging area of bioinspired materials processing with tough hydrogel design, and further provides a lasting inspiration and impetus for future hydrogel development that enables valuable scientific and technological advancements.

36 MATERIALS SCIENCE↗

Tracking fungal species-level responses in soil environments exposed to long-term warming and associated drying

Climate change is affecting fungal communities and their function in terrestrial ecosystems. Despite making progress in the understanding of how the fungal community responds to global change drivers in natural ecosystems, little is known on how fungi respond at the species level. Understanding how fungal species respond to global change drivers, such as warming, is critical, as it could reveal adaptation pathways to help us to better understand ecosystem functioning in response to global change. Here, we present a model study to track species-level responses of fungi to warming—and associated drying—in a decade-long global change field experiment; we focused on two free-living saprotrophic fungi which were found in high abundance in our site, Mortierella and Penicillium. Using microbiological isolation techniques, combined with whole genome sequencing of fungal isolates, and community level metatranscriptomics, we investigated transcription-level differences of functional categories and specific genes involved in catabolic processes, cell homeostasis, cell morphogenesis, DNA regulation and organization, and protein biosynthesis. We found that transcription-level responses were mostly species-specific but that under warming, both fungi consistently invested in the transcription of critical genes involved in catabolic processes, cell morphogenesis, and protein biosynthesis, likely allowing them to withstand a decade of chronic stress. Overall, our work supports the idea that fungi that invest in maintaining their catabolic rates and processes while growing and protecting their cells may survive under global climate change.

59 BASIC BIOLOGICAL SCIENCES↗

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.

Mosher, Alexander [Fermilab]↗

Perspectives on multi-material additive manufacturing

The last two decades have seen enormous gains in industrial adoption of additive manufacturing (AM) technologies. Its layer-wise approach to fabrication offers designers the opportunity to create structures with unique performance advantages over their traditionally manufactured counterparts, and have created new manufacturing business models and supply chains. While today’s AM technologies have enabled the creation of new geometries, future AM systems that offer simultaneous processing of multiple materials in a single build open opportunities for new product functionality that cannot be achieved by traditional manufacturing methods. Advances in multi-material additive manufacturing, which integrate dissimilar material into a complex, three-dimensional object, is emerging but the advances have been sporadic. Moving beyond homogenous materials, adding multi-materials, gradient, functional and responsive materials, and materials with heterogeneous and graded properties means that a single additive process based on either energy delivery or material deposition alone may not be suitable. Finally, this perspective gives a brief overview of the current status, challenges, and future recommendations for multi-material additive manufacturing. The authors aim to expand the notion of multi-material additive manufacturing beyond combining materials with dissimilar properties, to combinations of materials at different length scales, material classes as well as multiple functionalities.

36 MATERIALS SCIENCE↗

Intermittent Defect Fluctuations in Oxide Heterostructures

Abstract The heterogeneous nature, local presence, and dynamic evolution of defects typically govern the ionic and electronic properties of a wide variety of functional materials. While the last 50 years have seen considerable efforts into development of new methods to identify the nature of defects in complex materials, such as the perovskite oxides, very little is known about defect dynamics and their influence on the functionality of a material. Here, the discovery of the intermittent behavior of point defects (oxygen vacancies) in oxide heterostructures employing X‐ray photon correlation spectroscopy is reported. Local fluctuations between two ordered phases in strained SrCoO x with different degrees of stability of the oxygen vacancies are observed. Ab‐initio‐informed phase‐field modeling reveals that fluctuations between the competing ordered phases are modulated by the oxygen ion/vacancy interaction energy and epitaxial strain. The results demonstrate how defect dynamics, evidenced by measurement and modeling of their temporal fluctuations, give rise to stochastic properties that now can be fully characterized using coherent X‐rays, coupled for the first time to multiscale modeling in functional complex oxide heterostructures. The study and its findings open new avenues for engineering the dynamical response of functional materials used in neuromorphic and electrochemical applications.

36 MATERIALS SCIENCE↗

The Sorghum (Sorghum bicolor) Brown Midrib 30 Gene Encodes a Chalcone Isomerase Required for Cell Wall Lignification

In sorghum ( Sorghum bicolor ) and other C 4 grasses, brown midrib ( bmr ) mutants have long been associated with plants impaired in their ability to synthesize lignin. The brown midrib 30 ( Bmr30 ) gene, identified using a bulk segregant analysis and next-generation sequencing, was determined to encode a chalcone isomerase (CHI). Two independent mutations within this gene confirmed that loss of its function was responsible for the brown leaf midrib phenotype and reduced lignin concentration. Loss of the Bmr30 gene function, as shown by histochemical staining of leaf midrib and stalk sections, resulted in altered cell wall composition. In the bmr30 mutants, CHI activity was drastically reduced, and the accumulation of total flavonoids and total anthocyanins was impaired, which is consistent with its function in flavonoid biosynthesis. The level of the flavone lignin monomer tricin was reduced 20-fold in the stem relative to wild type, and to undetectable levels in the leaf tissue of the mutants. The bmr30 mutant, therefore, harbors a mutation in a phenylpropanoid biosynthetic gene that is key to the interconnection between flavonoids and monolignols, both of which are utilized for lignin synthesis in the grasses.

59 BASIC BIOLOGICAL SCIENCES↗

Data from: "Warming of alpine tundra enhances belowground production and shifts community towards resource acquisition traits"

This archive contains data used to draw conclusions in “Warming of alpine tundra enhances belowground production and shifts community towards resource acquisition traits”, by Yang et al. 2020. Data were collected on Niwot Ridge, in an alpine meadow within the Alpine Treeline Warming Experiment (ATWE) field sites in Colorado, USA. Samples were also processed in the U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, in Boise, Idaho. File formats in this archive include comma-separated values (.csv), portable document format (.pdf), Microsoft Excel (.xlsx), and two types of geospatial files: keyhole markup language (.kml), and ESRI shapefiles (.shp). Leaf scans are .jpg images, and root scans are .tiff/.tif images.The .csv files can be opened using R, Microsoft Excel, or any simple text-editing software such as TextEdit and Notepad. Microsoft Excel files can be opened using Microsoft Excel, and .pdf files can be opened with Adobe Acrobat Reader, Preview, or other compatible programs. Scanned images can be opened using any photo and/or picture viewing software.The .kml file can be opened using Google Earth and Google Maps, and the shapefiles can be opened by any programs compatible with shapefiles, such as the ArcGIS Desktop suite, and QGIS.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Measures of belowground net primary productivity (BNPP) are required to understand whether aboveground net primary production (ANPP) changes reflect changes in allocation or are indicative of a whole plant NPP response. Plant functional traits provide a key way to scale from the individual plant to the community level, and provide insight into drivers of NPP responses to environmental change. We used infrared heaters to warm an alpine plant community at Niwot Ridge, Colorado, and applied supplemental water to compensate for soil water loss induced by warming. We measured ANPP, BNPP, and leaf and root functional traits across treatments after 5 years of continuous warming. Community-level ANPP and total NPP (ANPP + BNPP) did not respond to heating or watering, but BNPP increased in response to heating. Heating decreased community-level leaf dry matter content and increased total root length, indicating a shift in strategy from resource conservation to acquisition in response to warming.

13C/12C isotope ratio↗

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗

Complex Functional Materials

The Complex Functional Materials (CFM) area of leadership focuses on the identification and development of materials comprised of multiple components or building blocks that are integrated or chemically bound together to achieve a desired function or response. Soft materials, such as polymers, as well as structural properties at the meso- and micro-scale that control materials function are particularly emphasized in this leadership area. Further, complex functional materials are generally developed to satisfy multiple materials design criteria all of which are essential to the overall application. CFM supports applications that are aligned with all three Los Alamos National Laboratory mission areas. These mission areas are: materials for nuclear deterrence, materials for energy security, and materials for global security

36 MATERIALS SCIENCE↗