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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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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Transcriptional networks underlying a primary ovarian insufficiency disorder in alligators naturally exposed to EDCs

Interactions between the endocrine system and environmental contaminants are responsible for impairing reproductive development and function. Despite the taxonomic diversity of affected species and attendant complexity inherent to natural systems, the underlying signaling pathways and cellular consequences are mostly studied in lab models. To resolve the genetic and endocrine pathways that mediate affected ovarian function in organisms exposed to endocrine disrupting contaminants in their natural environments, we assessed broad-scale transcriptional and steroidogenic responses to exogenous gonadotropin stimulation in juvenile alligators (Alligator missippiensis) originating from a lake with well-documented pollution (Lake Apopka, FL) and a nearby reference site (Lake Woodruff, FL). Here, we found that individuals from Lake Apopka are characterized by hyperandrogenism and display hyper-sensitive transcriptional responses to gonadotropin stimulation when compared to individuals from Lake Woodruff. Site-specific transcriptomic divergence appears to be driven by wholly distinct subsets of transcriptional regulators, indicating alterations to fundamental genetic pathways governing ovarian function. Consistent with broad-scale transcriptional differences, ovaries of Lake Apopka alligators displayed impediments to folliculogenesis, with larger germinal beds and decreased numbers of late-stage follicles. After resolving the ovarian transcriptome into clusters of co-expressed genes, most site-associated modules were correlated to ovarian follicule phenotypes across individuals. However, expression of two site-specific clusters were independent of ovarian cellular architecture and are hypothesized to represent alterations to cell-autonomous transcriptional programs. Collectively, our findings provide high resolution mapping of transcriptional patterns to specific reproductive function and advance our mechanistic understanding regarding impaired reproductive health in an established model of environmental endocrine disruption.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent results have shown that HNF4a defective function and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein an integrative analysis of hepatic RNAseq and liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to identify plasma protein signatures for mild and severe AH patients. Alcohol-related liver disease cirrhosis (ALD)(AC), non-alcoholic fatty liver disease (NALFD), and healthy subjects (HC) were used as comparator groups. Identified proteins primarily involved in hepatocellular function were decreased in AH patients which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified including thrombin (THRB), hepatocyte growth factor alpha (HGFA), clusterin (CLUS), human serum factor H-related protein (FHR1) and kallistatin (KAIN), which exhibited large abundance shifts between severe and non-severe AH. The combination of THRB and HGFA discriminated between severe and non-severe AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Cellular response of keratinocytes to the entry and accumulation of nanoplastic particles

Plastic accumulation in the environment is rapidly increasing, and nanoplastics (NP), byproducts of environmental weathering of bulk plastic waste, pose a significant public health risk. Particles may enter the human body through many possible routes such as ingestion, inhalation, and skin absorption. However, studies on NP penetration and accumulation in human skin are limited. Loss or reduction of the keratinized skin barrier may enhance the skin penetration of NPs. The present study investigated the entry of NPs into a human skin system modeling skin with compromised barrier functions and cellular responses to the intracellular accumulations of NPs. Two in vitro models were employed to simulate human skin lacking keratinized barriers. The first model was an ex vivo human skin culture with the keratinized dermal layer (stratum corneum) removed. The second model was a 3D keratinocyte/dermal fibroblast cell co-culture model with stratified keratinocytes on the top and a monolayer of skin fibroblast cells co-cultured at the bottom. The penetration and accumulation of the NPs in different cell types were observed using fluorescent microscopy, confocal microscopy, and cryogenic electron microscopy (cryo-EM). The cellular responses of keratinocytes and dermal fibroblast cells to stress induced by NPs stress were measured. The genetic regulatory pathway of keratinocytes to the intracellular NPs was identified using transcript analyses and KEGG pathway analysis. The cellular uptake of NPs by skin cells was confirmed by imaging analyses. Transepidermal transport and penetration of NPs through the skin epidermis were observed. According to the gene expression and pathway analyses, an IL-17 signaling pathway was identified as the trigger for cellular responses to internal NP accumulation in the keratinocytes. The transepidermal NPs were also found in co-cultured dermal fibroblast cells and resulted in a large-scale transition from fibroblast cells to myofibroblast cells with enhanced production of α-smooth muscle actin and pro-Collagen Ia. The upregulation of inflammatory factors and cell activation may result in skin inflammation and ultimately trigger immune responses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dose estimates and their uncertainties for use in epidemiological studies of radiation-exposed populations in the Russian Southern Urals

Many residents of the Russian Southern Urals were exposed to radioactive environmental pollution created by the operations of the Mayak Production Association in the mid- 20 th century. There were two major releases: the discharge of about 1x10 17 Bq of liquid waste into the Techa River between 1949 and 1959; and the atmospheric release of 7.4 * 10 16 Bq as a result an explosion in the radioactive waste-storage facility in 1957. The releases into the Techa River resulted in the exposure of more than 30,000 people who lived in riverside villages between 1950 and 1961. The 1957 accident contaminated a larger area with the highest exposure levels in an area that is called the East Urals Radioactive Trace (EURT). Current epidemiologic studies of the exposed populations are based on dose estimates obtained using a Monte-Carlo dosimetry system (TRDS-2016MC) that provides multiple realizations of the annual doses for each cohort member. These dose realizations provide a central estimate of the individual dose and information on the uncertainty of these dose estimates. In addition, the correlation of individual annual doses over realizations provides important information on shared uncertainties that can be used to assess the impact of shared dose uncertainties on risk estimate uncertainty.This paper considers dose uncertainties in the TRDS-2016MC. Individual doses from external and internal radiation sources were reconstructed for 48,036 people based on environmental contamination patterns, residential histories, individual 90 Sr body-burden measurements and dietary intakes. Dietary intake of 90 Sr resulted in doses accumulated in active bone marrow (or simply, marrow) that were an order of magnitude greater than those in soft tissues. About 84% of the marrow dose and 50% of the stomach dose was associated with internal exposures. The lognormal distribution is well-fitted to the individual dose realizations, which, therefore, could be expressed and easily operated in terms of geometric mean (GM) and geometric standard deviation (GSD). Cohort average GM for marrow and stomach cumulative doses are 0.21 and 0.03 Gy, respectively. Cohort average dose uncertainties in terms of GSD are as follows: for marrow it is 2.93 (90%CI: 2.02–4.34); for stomach and the other non-calcified tissues it is 2.32 (90% CI: 1.78–2.9).

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Removal of primary nutrient degrading members severely reduces growth of soil microbial communities even when additional degraders are present

Understanding how microorganisms within a soil community interact to support collective respiration and growth remains challenging. Here we used a model substrate, chitin, and a Model Soil Consortium, MSC-2, to investigate how individual members of a microbial community contribute to decomposition and community growth. While MSC-2 can grow using chitin as the sole carbon source, we do not yet know how the growth kinetics or final biomass yields of MSC-2 vary when certain chitin degraders, or other important members, are absent. To characterize specific roles within this representative community, we carried out experiments leaving out members of MSC-2 and measuring biomass yields and CO2 production. We chose two members to iteratively leave out (referred to by genus name): Streptomyces, as it is predicted via gene expression analysis to be a major chitin degrader in the community, and Rhodococcus as it is predicted via species co-abundance analysis to interact with several other members. Our results showed that when MSC-2 lacked Streptomyces, growth and respiration of the community was severely reduced. Removal of either Streptomyces or Rhodococcus led to major changes in abundance for several other species, pointing to a comprehensive shifting of the microbial community when important members are removed as well as alterations in the metabolic profile, especially when Streptomyces was removed. These results show that when keystone, chitin degrading members are removed, other members, even those with the potential to degrade chitin, do not fill the same metabolic niche to promote community growth. In addition, highly connected members may be removed with similar or even increased levels of growth and respiration. Our findings are critical to a better understanding of soil microbiology, specifically in how communities maintain activity when biotic or abiotic factors lead to changes in biodiversity in soil systems.

McClure, Ryan S↗
DOE OSTI2023

Removal of primary nutrient degraders reduces growth of soil microbial communities with genomic redundancy

Understanding how microorganisms within a soil community interact to support collective respiration and growth remains challenging. Here, we used a model substrate, chitin, and a synthetic Model Soil Consortium (MSC-2) to investigate how individual members of a microbial community contribute to decomposition and community growth. While MSC-2 can grow using chitin as the sole carbon source, we do not yet know how the growth kinetics or final biomass yields of MSC-2 vary when certain chitin degraders, or other important members, are absent. To characterize specific roles within this synthetic community, we carried out experiments leaving out members of MSC-2 and measuring biomass yields and CO 2 production. We chose two members to iteratively leave out (referred to by genus name): Streptomyces, as it is predicted via gene expression analysis to be a major chitin degrader in the community, and Rhodococcus as it is predicted via species co-abundance analysis to interact with several other members. Our results showed that when MSC-2 lacked Streptomyces, growth and respiration of the community was severely reduced. Removal of either Streptomyces or Rhodococcus led to major changes in abundance for several other species, pointing to a comprehensive shifting of the microbial community when important members are removed, as well as alterations in the metabolic profile, especially when Streptomyces was lacking. These results show that when keystone, chitin degrading members are removed, other members, even those with the potential to degrade chitin, do not fill the same metabolic niche to promote community growth. In addition, highly connected members may be removed with similar or even increased levels of growth and respiration. Our findings are critical to a better understanding of soil microbiology, specifically in how communities maintain activity when biotic or abiotic factors lead to changes in biodiversity in soil systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

Abstract mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Cetnar, Daniel P.↗
DOE OSTI2024

Mitochondrial ATP generation is more proteome efficient than glycolysis

Metabolic efficiency profoundly influences organismal fitness. Nonphotosynthetic organisms, from yeast to mammals, derive usable energy primarily through glycolysis and respiration. Although respiration is more energy efficient, some cells favor glycolysis even when oxygen is available (aerobic glycolysis, Warburg effect). A leading explanation is that glycolysis is more efficient in terms of ATP production per unit mass of protein (that is, faster). Through quantitative flux analysis and proteomics, we find, however, that mitochondrial respiration is actually more proteome efficient than aerobic glycolysis. This is shown across yeast strains, T cells, cancer cells, and tissues and tumors in vivo. Instead of aerobic glycolysis being valuable for fast ATP production, it correlates with high glycolytic protein expression, which promotes hypoxic growth. Aerobic glycolytic yeasts do not excel at aerobic growth but outgrow respiratory cells during oxygen limitation. Here, we accordingly propose that aerobic glycolysis emerges from cells maintaining a proteome conducive to both aerobic and hypoxic growth.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Gapped lineon and fracton models on graphs

We introduce a $\mathbb{Z}_N$ stabilizer code that can be defined on any spatial lattice of the form $\Gamma\times C_{L_z}$, where $\Gamma$ is a general graph. We also present the low-energy limit of this stabilizer code as a Euclidean lattice action, which we refer to as the anisotropic $\mathbb{Z}_N$ Laplacian model. It is gapped, robust (i.e., stable under small deformations), and has lineons. Its ground state degeneracy (GSD) is expressed in terms of a "mod $N$-reduction" of the Jacobian group of the graph $\Gamma$. In the special case when space is an $L\times L\times L_z$ cubic lattice, the logarithm of the GSD depends on $L$ in an erratic way and grows no faster than $O(L)$. Furthermore, we also discuss another gapped model, the $\mathbb{Z}_N$ Laplacian model, which can be defined on any graph. It has fractons and a similarly strange GSD.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Metabolic engineering to improve production of 3-hydroxypropionic acid from corn-stover hydrolysate in Aspergillus species

Fuels and chemicals derived from non-fossil sources are needed to lessen human impacts on the environment while providing a healthy and growing economy. 3-hydroxypropionic acid (3-HP) is an important chemical building block that can be used for many products. Biosynthesis of 3-HP is possible; however, low production is typically observed in those natural systems. Biosynthetic pathways have been designed to produce 3-HP from a variety of feedstocks in different microorganisms. In this study, the 3-HP β-alanine pathway consisting of aspartate decarboxylase, β-alanine-pyruvate aminotransferase, and 3-hydroxypropionate dehydrogenase from selected microorganisms were codon optimized for Aspergillus species and placed under the control of constitutive promoters. The pathway was introduced into Aspergillus pseudoterreus and subsequently into Aspergillus niger, and 3-HP production was assessed in both hosts. A. niger produced higher initial 3-HP yields and fewer co-product contaminants and was selected as a suitable host for further engineering. Proteomic and metabolomic analysis of both Aspergillus species during 3-HP production identified genetic targets for improvement of flux toward 3-HP including pyruvate carboxylase, aspartate aminotransferase, malonate semialdehyde dehydrogenase, succinate semialdehyde dehydrogenase, oxaloacetate hydrolase, and a 3-HP transporter. Overexpression of pyruvate carboxylase improved yield in shake-flasks from 0.09 to 0.12 C-mol 3-HP C-mol -1 glucose in the base strain expressing 12 copies of the β-alanine pathway. Deletion or overexpression of individual target genes in the pyruvate carboxylase overexpression strain improved yield to 0.22 C-mol 3-HP C-mol -1 glucose after deletion of the major malonate semialdehyde dehydrogenase. Further incorporation of additional β-alanine pathway genes and optimization of culture conditions (sugars, temperature, nitrogen, phosphate, trace elements) for 3-HP production from deacetylated and mechanically refined corn stover hydrolysate improved yield to 0.48 C-mol 3-HP C-mol -1 sugars and resulted in a final titer of 36.0 g/L 3-HP. The results of this study establish A. niger as a host for 3-HP production from a lignocellulosic feedstock in acidic conditions and demonstrates that 3-HP titer and yield can be improved by a broad metabolic engineering strategy involving identification and modification of genes participated in the synthesis of 3-HP and its precursors, degradation of intermediates, and transport of 3-HP across the plasma membrane.

09 BIOMASS FUELS↗
DOE OSTI2026

Leveraging a synthetic biology approach to enhance BCG-mediated expansion of Vγ9Vδ2 T cells

There is an urgent need to develop a more efficacious anti-tuberculosis vaccine as the current live-attenuated vaccine strain BCG fails to prevent pulmonary infection in adults. In this study, we leverage a synthetic biology approach to engineer BCG to produce more (E)-4-hydroxy-3-methyl-but-2-enyl pyrophosphate (HMBPP), an intermediate of bacterial—but not host—isoprenoid biosynthesis via the methylerythritol phosphate (MEP) pathway. HMBPP strongly activates and expands Vγ9Vδ2 T cells, which are unique to higher-order primates and protect against Mycobacterium tuberculosis infection. BCG has been engineered to produce specific ligands and antigens to some success; in contrast, our strategy exploits a self-nonself recognition mechanism in the host via HMBPP sensing, which has not been attempted before. To inform the design of our recombinant strains, we performed synteny analyses of >63 mycobacterial species and found that isoprenoid biosynthetic genes are not operonic across all the 356 surveyed genomes, but some genes are frequently found in pairs. Thus, we generated synthetic loci with the goal of specifically overproducing HMBPP and tested the ability of these engineered strains to induce human Vγ9Vδ2 expansion in an in vitro stimulation assay. We found that BCG expressing a synthetic MEP locus significantly enhanced Vγ9Vδ2 T cell expansion over the wild-type vaccine strain, and overexpression of the HMBPP synthase GcpE alone potently induced Vγ9Vδ2 T cell expansion with no downregulation of other pathway genes. Together these engineered strains present two successful strategies to accumulate HMBPP and overcome feedback inhibition of the MEP pathway.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Sorafenib derivatives-functionalized gold nanoparticles confer protection against tumor angiogenesis and proliferation via suppression of EGFR and VEGFR-2

Sorafenib is a multi-kinase inhibitor that has been highlighted as a tumor suppressor due to its anti-proliferative and anti-angiogenic properties, whereas the clinical application of Sorafenib is restricted by the side effects it may cause. The past decade has witnessed the development of a series of sorafenib derivatives to improve the clinical performance of sorafenib. Gold nanoparticles (AuNPs) have been widely utilized in drug delivery systems due to their unique properties, including biocompatible nature, simple preparation, and easy surface modification. Herein, this study is aimed to investigate the anti-tumor effects of new sorafenib derivatives-capped gold nanoparticles (AuNPs-New Sor) in tumor formation and metastasis as well as the underlying mechanisms. Initially, new sorafenib derivatives were constructed and combined with AuNPs to form AuNPs-New Sor, and the properties of synthesized AuNPs-New Sor were identified in a mouse model of tumorigenesis. The effect of AuNPs-New Sor on tumor vascular normalization was investigated by assessing vascular permeability and perfusion rate. Next, we evaluated the effect of AuNPs-New Sor on migration and viability of tumor cells and human umbilical vein endothelial cells (HUVECs) as well as on HUVEC angiogenesis in vitro. A melanoma mouse model was further established for in vivo substantiation of the anti-tumor effect of AuNPs-New Sor. According to the results, AuNPs could deliver new sorafenib derivatives into tumor tissues and downregulate the expression of epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor-2 (VEGFR-2), thereby suppressing tumor migration, EMT, and angiogenesis in vitro. In addition, AuNPs-New Sor displayed competitive anti-tumor activities in vivo. Taken together, AuNPs-New Sor may attenuate tumor development and angiogenesis through downregulation of EGFR and VEGFR-2.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

International Symposium on Transport Security of Nuclear and other Radioactive Material; Tokyo, Japan, November 2019

As an outcome of the Fourth Nuclear Security Summit of 2016, held in Washington D.C., the Governments of Australia, Canada, Czech Republic, Finland, France, Hungary, Italy, Japan, Kazakhstan, Morocco, Spain, the Republic of Korea, Thailand, the United Kingdom, and the United States reaffirmed, through INFCIRC/909, their will to further improve the overall security in the transport of nuclear and other radioactive materials. With this goal in mind, each expressed their commitment to further exchange national practices with other countries through the IAEA and the Global Initiative to Combat Nuclear Terrorism (GICNT). They also committed to actively support the IAEA as the central organization for coordinating activities and developing guidance documents and to support the GICNT and the Global Partnership Against the Spread of Weapons and Materials of Mass Destruction in developing and implementing its nuclear transport security activities. Both of these organizations address the commitments regarding nuclear transport security as outcomes of the Nuclear Security Summit 2016. In an effort to continue the momentum from the Nuclear Security Summit, the Government of Japan, in cooperation with the Integrated Support Center for Nuclear Nonproliferation and Nuclear Security of Japan Atomic Energy Agency (ISCN/JAEA), hosted the International Transport Security Symposium in November 2019. With over fifty countries invited to attend, the event exchanged and promoted good practices in several topical area sessions related to the security of nuclear and other radioactive material in transport. Topical sessions included Laws and Regulatory Framework, Physical Protection Systems, Response Actions, and Insider/Information Security. The Symposium built support for transport security and encouraged IAEA Member States to actively work regionally and internationally with the IAEA’s transport security programme through the practical implementation and incorporation of IAEA Nuclear Security Series recommendations and guidance into their national frameworks for transport security. From these sessions, to the host detailed a recommended path forward for future engagements in the security of nuclear and radioactive material in transport. The paper will discuss the Symposium’s outcomes and highlight the forward momentum made by both signatories and non-signatories for the strengthening of all the critical elements of a State’s transport security regime, including physical protection systems, insider threats to the nuclear and radioactive material supply chains, planning and capabilities for law enforcement response to malicious transport security events, and employment of technology to address critical vulnerabilities to the transport of nuclear and other radioactive materials.

Holt, Katherine↗
DOE OSTI2024

IPD3, a master regulator of arbuscular mycorrhizal symbiosis, affects genes for immunity and metabolism of non-host Arabidopsis when restored long after its evolutionary loss

Abstract Arbuscular mycorrhizal symbiosis (AM) is a beneficial trait originating with the first land plants, which has subsequently been lost by species scattered throughout the radiation of plant diversity to the present day, including the model Arabidopsis thaliana . To explore if elements of this apparently beneficial trait are still present and could be reactivated we generated Arabidopsis plants expressing a constitutively active form of Interacting Protein of DMI3 , a key transcription factor that enables AM within the Common Symbiosis Pathway, which was lost from Arabidopsis along with the AM host trait. We characterize the transcriptomic effect of expressing IPD3 in Arabidopsis with and without exposure to the AM fungus (AMF) Rhizophagus irregularis , and compare these results to the AM model Lotus japonicus and its ipd3 knockout mutant cyclops-4 . Despite its long history as a non-AM species, restoring IPD3 in the form of its constitutively active DNA-binding domain to Arabidopsis altered expression of specific gene networks. Surprisingly, the effect of expressing IPD3 in Arabidopsis and knocking it out in Lotus was strongest in plants not exposed to AMF, which is revealed to be due to changes in IPD3 genotype causing a transcriptional state, which partially mimics AMF exposure in non-inoculated plants. Our results indicate that molecular connections to symbiosis machinery remain in place in this nonAM species, with implications for both basic science and the prospect of engineering this trait for agriculture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models

Abstract Background A mechanistic understanding of the spread of SARS-CoV-2 and diligent tracking of ongoing mutagenesis are of key importance to plan robust strategies for confining its transmission. Large numbers of available sequences and their dates of transmission provide an unprecedented opportunity to analyze evolutionary adaptation in novel ways. Addition of high-resolution structural information can reveal the functional basis of these processes at the molecular level. Integrated systems biology-directed analyses of these data layers afford valuable insights to build a global understanding of the COVID-19 pandemic. Results Here we identify globally distributed haplotypes from 15,789 SARS-CoV-2 genomes and model their success based on their duration, dispersal, and frequency in the host population. Our models identify mutations that are likely compensatory adaptive changes that allowed for rapid expansion of the virus. Functional predictions from structural analyses indicate that, contrary to previous reports, the Asp 614 Gly mutation in the spike glycoprotein (S) likely reduced transmission and the subsequent Pro 323 Leu mutation in the RNA-dependent RNA polymerase led to the precipitous spread of the virus. Our model also suggests that two mutations in the nsp13 helicase allowed for the adaptation of the virus to the Pacific Northwest of the USA. Finally, our explainable artificial intelligence algorithm identified a mutational hotspot in the sequence of S that also displays a signature of positive selection and may have implications for tissue or cell-specific expression of the virus. Conclusions These results provide valuable insights for the development of drugs and surveillance strategies to combat the current and future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗
DOE OSTI2023

Succinate based polymers drive immunometabolism in dendritic cells to generate cancer immunotherapy

Boosting the metabolism of immune cells while restricting cancer cell metabolism is challenging. Herein, we report that using biomaterials for the controlled delivery of succinate metabolite to phagocytic immune cells activates them and modulates their metabolism in the presence of metabolic inhibitors. In young immunocompetent mice, polymeric microparticles, with succinate incorporated in the backbone, induced strong pro-inflammatory anti-melanoma responses. Administration of poly(ethylene succinate) (PES MP)-based vaccines and glutaminase inhibitor to young immunocompetent mice with aggressive and large, established B16F10 melanoma tumors increased their survival three-fold, a result of increased cytotoxic T cells expressing RORγT (Tc17). Mechanistically, PES MPs directly modulate glutamine and glutamate metabolism, upregulate succinate receptor SUCNR1, activate antigen presenting cells through and HIF-1alpha, TNFa and TSLP-signaling pathways, and are dependent on alpha-ketoglutarate dehydrogenase for their activity, which demonstrates correlation of succinate delivery and these pathways. Altogether, our findings suggest that immunometabolism-modifying PES MP strategies provide an approach for developing robust cancer immunotherapies.

59 BASIC BIOLOGICAL SCIENCES↗