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At least 37 records · Page 2

Genetic mapping of sorghum resistance to an Illinois isolate of Colletotrichum sublineola

Anthracnose leaf blight (ALB) is an economically important disease of sorghum [Sorghum bicolor (L.) Moench] caused by the fungal pathogen Colletotrichum sublineola Henn. ex Sacc. & Trotter. Although qualitative and quantitative resistance have been identified for ALB, the usefulness of resistance loci differs depending on the pathogen pathotype. Identifying resistance effective against unique pathogen pathotypes is critical to managing ALB, as the disease is managed primarily through the deployment of host resistance. We isolated C. sublineola from ALB-infected leaves collected in Illinois and found that the strain was a novel pathotype, as it produced a unique combination of virulence against a set of differential lines. Using this isolate, we inoculated 579 temperate-adapted sorghum conversion lines in 2019 and 2020. We then conducted a genome-wide association study (GWAS) and a metabolic pathway analysis using the Pathway Associated Study Tool (PAST). We identified 47 significant markers distributed across all chromosomes except chromosome 8. We identified 32 candidate genes based on physical proximity with significant markers, some of which have a known role in host defense. We identified 47 pathways associated with ALB resistance, indicating a role for secondary metabolism in defense to ALB. Our results are important to improve the understanding of the genetic basis of ALB resistance in sorghum and highlight the importance of developing durable resistance to ALB.

59 BASIC BIOLOGICAL SCIENCES↗

MEX3A promotes development and progression of breast cancer through regulation of PIK3CA

Breast cancer has been identified as the most common malignant tumors among women and the morbidity of breast cancer is still increasing rapidly. MEX3A possesses important functions in the regulation of mRNAs and may be involved in a variety of human diseases including cancer, whose relationship with breast cancer is still not clear. In this study, MEX3A was identified as a potential promotor in breast cancer, whose expression was strongly higher in breast cancer tissues than normal tissues. The in vitro experiments showed that MEX3A is capable of promoting the development of breast cancer through stimulating cell proliferation, inhibiting cell apoptosis, arresting cell cycle and promoting cell migration. The functions of MEX3A were also verified in vivo. Furthermore, a combination of genechip analysis and Ingenuity pathway analysis (IPA) identified PIK3CA as a potential downstream target of MEX3A, knockdown of which executes similar inhibitory effects on breast cancer and could alleviate MEX3A-induced progression of breast cancer. In conclusion, our study unveiled, as the first time, MEX3A as a tumor promotor for breast cancer, whose function was carried out probably through the regulation of PIK3CA.

60 APPLIED LIFE SCIENCES↗

Experimental and Kinetic Modeling Study of Laminar Burning Velocities of Cyclopentanone and Its Binary Mixtures with Ethanol and n-Propanol

Cyclopentanone is a promising biofuel that can enable more efficient engine operation and increase the fuel economy of the light duty fleet over current and planned technology developments. While the ignition of cyclopentanone has been investigated in detail, more studies on the laminar burning velocities of cyclopentanone are called for. In this work, the laminar burning velocities of cyclopentanone (C 5 H 8 O) have been measured using the heat flux and spherical flame methods at 1 atm, equivalence ratios from 0.7 to 1.6, and initial temperatures of 328, 353, and 428 K. To further investigate the relationship between the molecular structure and laminar burning velocity, identical experiments were also performed for binary mixtures of cyclopentanone with ethanol and n-propanol at 1:1 (mol). The consistency between the experimental data sets obtained in this work and literature data sets has been evaluated. Here, a recently published mechanism of cyclopentanone was used for simulation after adopting the submechanism of n-propanol. Good agreement has been seen between experimental and simulated results for all flames. To qualitatively explain the characteristics of the laminar burning velocity of cyclopentanone and the differences with those of ethanol and n-propanol, sensitivity analysis and reaction pathway analysis have been performed to compare the chemistry of the fuels under flame conditions, which revealed how the molecular structure of cyclopentanone could affect its laminar burning velocity. Compared to ethanol and n-propanol, cyclopentanone does not have primary carbon atoms in its molecule, leading to lower production of methyl radicals. Meanwhile, the carbonyl group in the cyclopentanone molecule is mostly released as CO in the decomposition of multiple intermediates accompanied by the production of unsaturated C 2 and C 4 species, especially C 2 H 4 and C 2 H 3 . Both features contribute to the high laminar burning velocity of cyclopentanone.

09 BIOMASS FUELS↗

Vadose Zone Flow and Transport Parameters Data Package for the Hanford Site Composite Analysis and Cumulative Impact Evaluation

This report provides a description of the basis for the development and implementation of a conceptual model for vadose zone flow and transport for the composite analysis (CA) groundwater pathway analysis and the cumulative impact evaluation (CIE). The parameterization for a numerical model is intimately linked to the conceptual model framework. The report describes the basis for the selection of hydraulic and transport parameters for the hydrostratigraphic units (HSUs) identified in the 200 East and 200 West Areas. Whenever data are sparse or unavailable, surrogate hydraulic properties are chosen based on samples collected within the 200 Areas and nearby locations that are representative of sediments characteristic of the HSUs identified elsewhere.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Integrated transcriptomic and metabolomic investigation of the genes and metabolites involved in swine follicular cyst formation

Follicular cysts are a common reproductive disorder in mammals that is usually caused by stress. However, the pathogenesis of follicular cysts in sows remains unclear. To provide new insights into the mechanisms of follicular cyst formation in pigs, we conducted a combined transcriptomic and metabolomic analysis on theca interna and mural granulosa cells of follicular cysts and mature follicles. We identified 2,533 up-regulated and 1,355 down-regulated genes in follicular cysts, compared with mature follicles. These differentially expressed genes were mainly found in signaling pathways related to tumor formation and cortisol synthesis and secretion as shown by Ingenuity Pathway Analysis, which predicted 4,362 upstream regulatory factors. The combined gene expression and pathway analysis identified the following genes as potential biomarkers for porcine follicular cysts: cytochrome P450 family 2 subfamily C polypeptide 18, L-lactate dehydrogenase, carbamoyl-phosphate synthase, fibroblast growth factor 7, integrin binding sialoprotein, interleukin 23 receptor, prolactin receptor, epiregulin, interleukin 1 receptor type II, arginine vasopressin receptor 1A, fibroblast growth factor 10, claudin 7, G Protein Subunit Gamma 3, cholecystokinin B receptor and cytosolic phospholipase A2 . Metabolomics analysis found significant differences in 87 metabolites, which were enriched in unsaturated fatty acid biosynthesis, and sphingolipid signaling pathways. These results provide valuable information on the molecular mechanisms of follicular cyst formation, which may facilitate the development of new therapeutics to prevent and treat follicular cysts.

Dai, Jiage↗

H 2 Production Pathways Cost Analysis (2016 - 2021) (Final Report)

This final report documents cost analysis conducted for the Department of Energy over a five year period (2016 to 2021) pertaining to hydrogen production and delivery system components, focusing on the key remaining challenges of the technology pathways within the Hydrogen Production and Delivery sub-program portfolio. A particular focus was placed on electrolysis for the generation of hydrogen. The effort primarily used the H2A discounted cash flow computational model as a tool to project hydrogen cost ($/kgH 2 ) and determine status improvements resulting from technology advancements. The effort also considered cost as a function of production volume, employed error bars to illustrate uncertainties in the cost estimates, and utilized sensitivity analyses to show the potential for cost reductions. The project examined a range of hydrogen production and delivery related systems. These included WireTough wire-wrapped pressure vessels for hydrogen storage, proton exchange membrane (PEM) electrolysis, solid oxide electrolysis (SOE), anion exchange membrane (AEM) electrolysis, photoelectrochemical (PEC) electrolysis, solar thermochemical hydrogen (STCH) production, the cost of energy transmission, and a study on the necessary price of hydrogen to produce competitively-priced electricity via fuel cell conversion.

08 HYDROGEN↗

Development of Genetic Algorithm Based Multi-Objective Plant Reload Optimization Platform

The U.S. nuclear industry is facing a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light-water reactor nuclear power plant operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed in the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. The Light Water Reactor Sustainability Program promotes a wide range of research and development activities to maximize both the safety and economic efficiency of nuclear power plants through improved scientific understanding, especially given that many plants are now considering second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: Deploy methodologies and technologies that better represent safety margins and cost and safety factors; Develop advanced applications that enable cost-effective plant operations. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. This report summarizes genetic-algorithm-based multi-objective fuel reload optimization activities, specifically: Developing the non-dominated sorting genetic algorithm II optimizer in the Risk Analysis and Virtual ENviroment (RAVEN); Demonstrating and validating the developed non-dominated sorting genetic algorithm II optimizer using benchmark optimization problems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Full-scale Demonstration of Pressurized Water Reactor Core Design Optimization using Multi-Cycle Optimization Methodology

The U.S. nuclear sector encounters a difficulty in upholding essential safety standards while also securing economic viability for continued operation. Safety stands as a pivotal factor across all facets of operations within light-water reactor nuclear power plants. Achieving economic feasibility alongside safety can be facilitated through the utilization of a risk-informed framework, exemplified by the ongoing development within the Risk-Informed Systems Analysis Pathway under the auspices of the U.S. Department of Energy's LWRS Program. This initiative advocates for a diverse array of research and development endeavors aimed at optimizing both safety and economic efficacy within nuclear power plants, particularly pertinent as many plants contemplate second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: deploy methodologies and technologies that better represent safety margins and cost and safety factors and develop advanced applications that enable cost-effective plant operation. This report assesses the potential for resolving multi-cycle plant reload challenges through real-world scenarios utilizing the Plant ReLoad Optimization (PRLO) framework. This framework offers reactor core design developers analytic tools of reactor safety and fuel performance with the assistance of artificial intelligence (AI) to enhance core design solutions. Multi-objective genetic algorithm alongside acceleration techniques is explored as an enabling technology for improving fuel efficiency while upholding safety thresholds. The demonstration of multi-cycle core design optimization is performed. This report investigates the practical application of the PRLO platform in addressing real-world core design challenges, supporting AI efforts, and contrasting outcomes with those derived from heuristic or conventional algorithms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Safety Analysis of FeCrAl Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The U.S. nuclear industry is facing a strong challenge to maintain regulatory-required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects related to the operation of light water reactor nuclear power plants (NPPs), and it can be achieved more economically by using a risk-informed ecosystem, such as that being developed by the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. This program is promoting a wide range of research and development activities to maximize both the safety and economically efficient performance of NPPs through improved scientific understanding, especially given that many plants are considering a second license renewal. The Risk-Informed Systems Analysis Pathway has two main goals: (1) The deployment of methodologies and technologies that enable a better representation of the safety margins and factors that contribute to cost and safety, and (2) The development of advanced applications that enable cost-effective plant operation. As part of this pathway, the Enhanced Resilient Plant project refers to an NPP where safety is improved by implementing various measures, such as accident-tolerant fuels, diverse and flexible coping strategies, enhancements to plant components and systems, incorporation of augmented or new passive cooling systems, and utilization of advanced battery technologies. The objective of the Enhanced Resilient Plant project is to use novel methods and computational tools to enhance existing reactors’ safety while reducing operational costs. This report documents research and development conducted in support of deployment of accident-tolerant fuels. This project performed safety analyses for the steady-state normal operation, anticipated operational occurrences, and design-basis accidents of a representative four-loop pressurized water reactor model with Zr and FeCrAl accident-tolerant fuel clad with higher enrichment and burnup supporting plant refueling cycles of 18 and 24 months. The source terms and environmental impacts were studied for a large-break loss of coolant accident, including uncertainty analyses.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparative Technoeconomic Analysis of Pathways for Electrochemical Reduction of CO 2 with Methanol to Produce Methyl Formate

Electrochemical CO 2 reduction has promise as a technology that could help society reach carbon neutrality while producing valuable fuels and chemicals. Herein, the electrochemical synthesis of methyl formate, a product not observed in aqueous CO 2 electrolysis, has been analyzed by a rigorous technoeconomic model to evaluate its commercial viability. Methyl formate synthesis has been demonstrated with high faradaic efficiency through the electroreduction of CO 2 in methanol. Four competing approaches were analyzed: (1) Electroreduction of captured CO 2 in a dual CH 3 OH/H 2 O electrolyzer, (2) Direct electroreduction of flue gas CO 2 in a dual CH 3 OH/H 2 O electrolyzer, (3) Electroreduction of captured CO 2 in a CH 3 OH/CH 3 OH electrolyzer, and (4) Electroreduction of captured CO 2 in a H 2 O/H 2 O electrolyzer with a downstream CH 3 OH reactor. Sensitivity analyses, cost contour plots, and comparison plots were generated. The dual methanol/water electrolysis approach was the most cost-competitive, with a levelized cost of methyl formate below the present market price. Here, the all-methanol electrolysis route was more expensive due to increased methanol consumption and greater distillation costs. Methyl formate production through aqueous CO 2 electrolysis to formic acid with a secondary esterification reaction was by far the most expensive approach, primarily due to the energy-intensive nature of distilling formic acid from water.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Genetic variations and their interaction with thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice

Thirdhand smoke (THS) is linked to adverse health effects, but the effect of genetic variations on behavioral outcomes is poorly understood. To investigate this, we assessed anxiety- and memory-related behaviors in 820 mice from 21 strains of the genetically diverse Collaborative Cross (CC) mouse that were exposed to THS from 4 through 10 weeks of age. Anxiety was evaluated with a light/dark box assay with a previously established risk score system. Females were generally more sensitive: THS reduced anxiety risk in strains CC013, CC019, and CC051, but increased risk in CC036 and CC061, while males showed no significant effects. Memory was tested using passive avoidance: impairments were observed in both sexes in CC016 and CC019, with sex-dependent effects in CC002 and CC051. A genome-wide association study identified 2,347 SNPs associated with anxiety and 1,568 SNPs with memory, with 32 and 85 SNPs, respectively, interacting with THS exposure. Enrichment analyses revealed distinct biological processes underlying susceptibility, including axonogenesis, synapse organization, cognition, and learning and memory. KEGG pathway analysis identified distinct genetic pathways, including GTPase binding and GTPase regulatory activity, that act as critical molecular switches in the brain that regulate synaptic plasticity, dendritic spine structure, and neuronal signaling, directly influencing anxiety-like behaviors and memory formation. These findings show that THS exposure affects neurobehavioral outcomes in a sex- and genotype-dependent manner, highlighting critical gene-environment interactions and providing a foundation for mechanistic insights into THS neurotoxicity

Anxiety↗

PathTrace and MPVEASI: A Path Analysis Comparative Validation Study

Developed in 2018, PathTrace is a software package built with the intention of making path analysis simple and intuitive. PathTrace is a top-down pathway analysis software where a user is able to explore vulnerable pathways into a facility. The intention of utilizing a software tool like PathTrace is to characterize an existing physical protection system (PPS) and to upgrade the system to achieve a high level of response interruption, or probability of interruption (P I ) of the adversary. There are four steps for conducting path analysis using PathTrace. The first step is to identify an image to use to build the model and scale the model within PathTrace using a section of known distance (wall or fence perimeter, for example). The scaling process will produce a grid of cells through which the user is able to build a model. The second step is to fill out the grid of cells with four categories of materials: Barriers, Detection Areas, Jumps, and Targets. These materials apply associated delay and detection values to the cells in which they are applied. The third step is to represent the adversary and response forces. The adversaries are represented by their capabilities in interacting with the materials identified in step two, and the response is represented by how quickly they will be able to respond to an adversary attack. Finally, the user is able to take all of the information from the previous three steps and perform a Most Vulnerable Path (MVP) analysis. In this stage, the user is able to visualize vulnerable adversary pathways and reason about how to upgrade these pathways to provide a high level of P I .

97 MATHEMATICS AND COMPUTING↗

ARCADE Analysis Methods & Validation Pathway

The Advanced Reactor Cyber Analysis and Development Environment (ARCADE) provides an automated analysis system which supports risk-informed performance based (RIPB) evaluations of nuclear control systems. Every possible cyber threat which could lead to consequence is identified by simulating the unsafe control action sequences which transform digital harm into physical harm. Eliminating the simulation of complex digital cyber attack chains cuts out unnecessary computational overhead and focuses directly on the physics of cyber-physical attacks. This focus enables designers to make informed decisions which can entirely eliminate categories of cyber threats against advanced reactors through the physical nature of the plant design. This narrowing of cyber threat against nuclear power plants through the physics of the system is intended to make any remaining threat management and cost efficient. This is the goal of the Tiered Cyber Analysis (TCA) outlined in NRC Draft Regulation Guide (RG) 5.96, which provides a RIPB cybersecurity approach for new reactors. ARCADE has been custom developed to meet the demands of the rigorous analysis required in Tier 1 of the TCA, which forms the foundation of the TCA process. Currently, ARCADE is still under development, but has made significant leaps in capability. A pilot analysis on the opensource Asherah simulator was performed which demonstrated key functionality goals. The next stage of ARCADE development involves improvements to the applications which support the analysis system, and enabling the analysis system to utilize the full suite of unsafe control action simulations. Since the analysis method’s core functions are complete, validation of the analysis method will be started concurrent to the next development stages. The automated analysis ARCADE will provide can radically change the cybersecurity design process for advanced reactors, reducing the cost of security implementation while enhancing cyber resilience. The pathway for ARCADE’s development to this goal has become much clearer. The majority of technical hurdles have been cleared, and the remaining development needs have been solidified. ARCADE is now capable of assisting the advanced reactor design process and directly support advanced reactor industry RIPB practices.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Examining experimental nitrogen-based emissions trends from ammonia/diesel and ammonia/hydrogen/diesel combustion

Ammonia has garnered interest as an alternative fuel for power sectors with heavy payload and distance requirements, such as shipping. In this study, ammonia was used in a dual-fuel compression-ignition combustion strategy to overcome some of its technical barriers, using a diesel pilot to ignite a premixed mixture of ammonia and air. Mixtures of premixed ammonia and hydrogen were also explored to evaluate whether the inclusion of hydrogen improves nitrogen-based emissions from the combustion process. A single-cylinder version of a Cummins ISB 6.7 L engine platform was used to experimentally study these effects at various global air/fuel ratios and hydrogen energy fractions. Hydrogen inclusion produced pronounced NOx and N2O emissions, while inclusion of trapped residuals increased N2O but reduced NOx. The two most recent and relevant mechanisms available in the literature—those from Xu and Zhang-Ren-Kokjohn—were used in a chemical kinetics analysis to examine the observed differences in the NOx trends from two dual-fuel ammonia/diesel datasets: (1) in which a portion of the premixed ammonia was substituted with hydrogen and (2) in which the effect of hot trapped residuals was evaluated with only ammonia/air premixed mixtures. The analysis with both mechanisms showed agreement with experimental trends; however, contributions from thermal vs. fuel-borne NOx pathways showed disagreement. A reaction pathway analysis showed that the HNO to NO pathway was the key to NO formation in the mixture.

Tyrewala, Daanish [ORNL] (ORCID:0000000208599324)↗

Experimental Ignition Delay Time Measurements and Chemical Kinetics Modeling of Hydrogen/Ammonia/Natural Gas Fuels

In recent years, hydrogen-carrying compounds have accrued interest as an alternative to traditional fossil fuels due to their function as zero-emission fuels. As such, there is interest in investigating hydrogen-carrying compounds to improve understanding of the fuels' characteristics for use in high pressure systems. In the current study, the oxidation of ammonia/natural gas/hydrogen mixtures was carried out to study carbon monoxide (CO) formation profiles as well as the ignition delay times (IDTs) behind reflected shock waves in order to refine chemical kinetic models. Experiments were carried out in the University of Central Florida's shock tube facility by utilizing chemiluminescence to obtain OH* emission and laser absorption spectroscopy to obtain CO profiles over a temperature range between 1200 K and 1800 K with an average pressure of 2.2 atm. Experimental mixtures included both neat and combination natural gas/hydrogen with ammonia addition, with all mixtures except one having an equivalence ratio of 1. Results were then compared with the GRI 3.0 mechanism, as well as the newly developed UCF 2022 mechanism utilizing chemkin-pro software. In general, both models were able to capture the trend in auto-ignition delay times and CO time histories for natural gas and ammonia mixtures. However, for ammonia–hydrogen mixtures, GRI 3.0 failed to predict ignition delay times, whereas the UCF 2022 mechanism was able to capture the IDTs within the uncertainty limits of the experiments. A sensitivity analysis was conducted for different mixtures to understand the important reactions at the experimental conditions. Lastly, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.

33 ADVANCED PROPULSION SYSTEMS↗

Autoignition Delay Time Measurements and Chemical Kinetic Modeling of Hydrogen/Ammonia/Natural Gas Mixtures

Abstract In recent years, hydrogen-carrying compounds have accrued interest as an alternative to traditional fossil fuels due to their function as zero-emission fuels. As such, there is interest in investigating hydrogen-carrying compounds to improve understanding of the fuels’ characteristics for use in high-pressure systems. In the current study, the oxidation of ammonia/natural gas/hydrogen mixtures was carried out to study CO formation profiles as well as the ignition delay times behind reflected shock waves in order to refine chemical kinetic models. Experiments were carried out in the University of Central Florida’s shock tube facility by utilizing chemiluminescence to obtain OH* emission and laser absorption spectroscopy to obtain CO profiles. Experimental results were then compared with the GRI 3.0 mechanism, as well as the proprietary UCF 2022 mechanism utilizing CHEMKIN-Pro software. In general, both models were able to capture the trend in autoignition delay times and CO time histories for natural gas and ammonia mixtures. However, for ammonia-hydrogen mixtures, GRI 3.0 failed to predict ignition delay times whereas the UCF 2022 mechanism was able to capture the IDTs within the uncertainty limits of the experiments. A sensitivity analysis was conducted for different mixtures to understand the important reactions at the experimental conditions. Finally, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.

Baker, Jessica B.↗

A deep redox proteome profiling workflow and its application to skeletal muscle of a Duchenne Muscular Dystrophy model

Perturbation to the redox state accompanies many diseases and its effects are viewed through oxidation of biomolecules, including proteins, lipids, and nucleic acids. The thiol groups of protein cysteine residues undergo an array of redox post-translational modifications (PTMs) that are important for regulation of protein and pathway function. To better understand what proteins are redox regulated following a perturbation, it is important to be able to comprehensively profile protein thiol oxidation at the proteome level. Herein, we report a deep redox proteome profiling workflow and demonstrate its application in measuring the changes in thiol oxidation along with global protein expression in skeletal muscle from mdx mice, a model of Duchenne Muscular Dystrophy (DMD). In depth coverage of the thiol proteome was achieved with >18,000 Cys sites from 5608 proteins in muscle being quantified. Compared to the control group, mdx mice exhibit markedly increased thiol oxidation, where ~2% shift in the median oxidation occupancy was observed. Further, pathway analysis for the redox data revealed that coagulation system and immune-related pathways were among the most susceptible to increased thiol oxidation in mdx mice, whereas protein abundance changes were more enriched in pathways associated with bioenergetics. This study illustrates the importance of deep redox profiling in gaining greater insight into oxidative stress regulation and pathways/processes that are perturbed in an oxidizing environment.

60 APPLIED LIFE SCIENCES↗