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All sources NASA NTRS DOE OSTI

DOE OSTI2024

Novel, active, and uncultured hydrocarbon-degrading microbes in the ocean

ABSTRACT Given the vast quantity of oil and gas input to the marine environment annually, hydrocarbon degradation by marine microorganisms is an essential ecosystem service. Linkages between taxonomy and hydrocarbon degradation capabilities are largely based on cultivation studies, leaving a knowledge gap regarding the intrinsic ability of uncultured marine microbes to degrade hydrocarbons. To address this knowledge gap, metagenomic sequence data from the Deepwater Horizon (DWH) oil spill deep-sea plume was assembled to which metagenomic and metatranscriptomic reads were mapped. Assembly and binning produced new DWH metagenome-assembled genomes that were evaluated along with their close relatives, all of which are from the marine environment (38 total). These analyses revealed globally distributed hydrocarbon-degrading microbes with clade-specific substrate degradation potentials that have not been reported previously. For example, methane oxidation capabilities were identified in all Cycloclasticus . Furthermore, all Bermanella encoded and expressed genes for non-gaseous n -alkane degradation; however, DWH Bermanella encoded alkane hydroxylase, not alkane 1-monooxygenase. All but one previously unrecognized DWH plume member in the SAR324 and UBA11654 have the capacity for aromatic hydrocarbon degradation. In contrast, Colwellia were diverse in the hydrocarbon substrates they could degrade. All clades encoded nutrient acquisition strategies and response to cold temperatures, while sensory and acquisition capabilities were clade specific. These novel insights regarding hydrocarbon degradation by uncultured planktonic microbes provides missing data, allowing for better prediction of the fate of oil and gas when hydrocarbons are input to the ocean, leading to a greater understanding of the ecological consequences to the marine environment. IMPORTANCE Microbial degradation of hydrocarbons is a critically important process promoting ecosystem health, yet much of what is known about this process is based on physiological experiments with a few hydrocarbon substrates and cultured microbes. Thus, the ability to degrade the diversity of hydrocarbons that comprise oil and gas by microbes in the environment, particularly in the ocean, is not well characterized. Therefore, this study aimed to utilize non-cultivation-based ‘omics data to explore novel genomes of uncultured marine microbes involved in degradation of oil and gas. Analyses of newly assembled metagenomic data and previously existing genomes from other marine data sets, with metagenomic and metatranscriptomic read recruitment, revealed globally distributed hydrocarbon-degrading marine microbes with clade-specific substrate degradation potentials that have not been previously reported. This new understanding of oil and gas degradation by uncultured marine microbes suggested that the global ocean harbors a diversity of hydrocarbon-degrading bacteria, which can act as primary agents regulating ecosystem health.

Howe, Kathryn L.↗

DOE OSTI2025

Nanolipoprotein particle (NLP) vaccine confers protection against Yersinia pestis aerosol challenge in a BALB/c mouse model

Introduction: Yersinia pestis is the etiological agent of plague, a disease that remains a concern as demonstrated by recent outbreaks in Madagascar. Infection with Y. pestis results in a rapidly progressing illness that can only be successfully treated with antibiotics given shortly after symptom onset. Live attenuated or whole cell inactivated vaccines confer protection against bubonic plague, but pneumonic plague has been more difficult to prevent. Novel effective subunit vaccine formulations may circumvent some of these shortfalls. Here, we compare the immunogenicity generated by an advanced subunit vaccine (F1V fusion protein) and a nanolipoprotein particle (NLP)-based vaccine. Methods: The NLP, a high-density lipoprotein mimetic, provides a nanoscale delivery platform for recombinant Y. pestis antigens LcrV (V) and F1. BALB/c mice were immunized via subcutaneous injection twice, three or four weeks apart. Four weeks later, splenocytes and sera were collected for immune profiling, and mice were challenged with aerosolized Y. pestis CO92. Results: Both formulations induced a strong IgG response against the F1 and V proteins, along with a robust memory B cell response and a balanced cell-mediated immune response as evidenced by both Th1- and Th2-related cytokines. The NLP-based vaccine induced a stronger cytokine response against F1, V, and F1V proteins relative to the F1V vaccine. As with F1V, the inclusion of Alhydrogel (Alu) in NLP vaccine formulations was critical for enhanced immunogenicity and protective efficacy. Mice that received two doses of F1:V:NLP + Alu and CpG were completely protected from a challenge with approximately eight median lethal doses of aerosolized Y. pestis CO92 and this protection confirmed the well-documented synergy between the F1 and V antigens in context of pneumonic plague. The NLPs have defined regions of polarity that facilitates the incorporation of a wide range of adjuvants and antigens with distinct physicochemical properties and are an excellent candidate platform for the development of multi-antigen vaccines.

F1↗

NASA NTRS2004

Design of Hybrid Mobile Communication Networks for Planetary Exploration

The Mobile Exploration System Project (MEX) at NASA Ames Research Center has been conducting studies into hybrid communication networks for future planetary missions. These networks consist of space-based communication assets connected to ground-based Internets and planetary surface-based mobile wireless networks. These hybrid mobile networks have been deployed in rugged field locations in the American desert and the Canadian arctic for support of science and simulation activities on at least six occasions. This work has been conducted over the past five years resulting in evolving architectural complexity, improved component characteristics and better analysis and test methods. A rich set of data and techniques have resulted from the development and field testing of the communication network during field expeditions such as the Haughton Mars Project and NASA Mobile Agents Project.

Alena, Richard L.↗

NASA NTRS2025

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.

Yeji Kim↗

NASA NTRS1992

Human-like agents with posture planning ability

Human body models are geometric structures which may be ultimately controlled by kinematically manipulating their joints, but for animation, it is desirable to control them in terms of task-level goals. We address a fundamental problem in achieving task-level postural goals: controlling massively redundant degrees of freedom. We reduce the degrees of freedom by introducing significant control points and vectors, e.g., pelvis forward vector, palm up vector, and torso up vector, etc. This reduced set of parameters are used to enumerate primitive motions and motion dependencies among them, and thus to select from a small set of alternative postures (e.g., bend vs. squat to lower shoulder height). A plan for a given goal is found by incrementally constructing a goal/constraint set based on the given goal, motion dependencies, collision avoidance requirements, and discovered failures. Global postures satisfying a given goal/constraint set are determined with the help of incremental mental simulation which uses a robust inverse kinematics algorithm. The contributions of the present work are: (1) There is no need to specify beforehand the final goal configuration, which is unrealistic for the human body, and (2) the degrees of freedom problem becomes easier by representing body configurations in terms of 'lumped' control parameters, that is, control points and vectors.

Jung, Moon R.↗

DOE OSTI2025

Porous CeO 2 /CuO Heterostructure for Efficient Hydrogen Evolution Reaction in an Acidic Medium

A composite electrocatalyst CeO 2 /CuO is fabricated for the hydrogen evolution reaction (HER) via a simple, facile, one‐step hydrothermal method, using F‐127 as a template and structure directing agent. The prepared composite CeO 2 /CuO shows top‐notch HER activities with a small overpotential of 98 mV at 10 mA cm −2 and just 160 mV overpotential to attain a current density of 50 mA cm −2 with good stability for 20 h in an acidic medium. The enhanced catalytic activities of CeO 2 /CuO nanocomposite are attributed to their synergetic interface interaction, which lead to improved conductivity, reactive sites, and oxygen vacancies in their lattices. This study aims to advance the development of earth‐abundant transition metal oxides–based electrocatalysts as economical, durable, and efficient HER electrocatalysts to replace noble metal–based materials in the future.

Chemistry↗

DOE OSTI2023

p -Azaquinodimethane: A Versatile Quinoidal Moiety for Functional Materials Discovery

The past 50 years of discovery in organic electronics have been driven in large part by the donor–acceptor design principle, wherein electron-rich and electron-poor units are assembled in conjugation with each other to produce small band gap materials. While the utility of this design strategy is undoubtable, it has been largely exhausted as a frontier of new avenues to produce and tune novel functional materials to meet the needs of the ever-increasing world of organic electronics applications. Its sister strategy of joining quinoidal and aromatic groups in conjugation has, by comparison, received much less attention, to a great extent due to the categorically poor stability of quinoidal conjugated motifs. In 2017 though, the p-azaquinodimethane (AQM) motif was first unveiled, which showed a remarkable level of stability despite being a close structural analogue to p-quinodimethane, a notably reactive compound. In contrast, dialkoxy AQM small molecules and polymers are stable even under harsh conditions and could thus be incorporated into conjugated polymers. When polymerized with aromatic subunits, these AQM-based polymers show notably reduced band gaps that follow reversed structure–property trends to some of their donor–acceptor polymer counterparts and yield organic field-effect transistor (OFET) hole mobilities above 5 cm 2 V –1 s –1 . Additionally, in an ongoing study, these AQM-based compounds are also showing promise as singlet fission (SF) active materials due to their mild diradicaloid character. An expanded world of AQMs was accessed through their ditriflate derivatives, which were first used to produce ionic AQMs (iAQMs) sporting two directly attached cationic groups that significantly affect the AQM motif’s electronics, producing strongly electron-withdrawing quinoidal building blocks. Conjugated polyelectrolytes (CPEs) created with these iAQM building blocks exhibit optical band gaps stretching into the near-infrared I (NIR-I) region and showed exemplary behavior as photothermal therapy agents. In contrast to these stable AQM examples, the synthetic exploration of AQMs also produced examples of more typical diradicaloid reactivity but in forms that were controllable and produced intriguing and high-value products. With certain substitution patterns, AQMs were found to dimerize to form highly substituted [2.2]paracyclophanes in distinctly more appreciable yields than typical cyclophane formation reactions. Certain AQM ditriflates, when crystallized, undergo light-induced topochemical polymerization to form ultrahigh molecular weight (>10 6 Da) polymers that showed excellent performances as dielectric energy storage materials. These same AQM ditriflates could be used to produce the strongly electron-donating redox-active pentacyclic structure: pyrazino[2,3-b:5,6-b']diindolizine (PDIz). Importantly, the PDIz motif allowed for the synthesis of exceedingly small band gap (0.7 eV) polymers with absorbances reaching all the way into the NIR-II region that were also found to produce strong photothermal effects. Both as stable quinoidal building blocks and through their controllable diradicaloid reactivity, AQMs have already proven to be versatile and effective as functional organic electronics materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

An Edge-Cloud Integrated Solution for Buildings Demand Response Using Reinforcement Learning

Buildings, as major energy consumers, can provide great untapped demand response (DR) resources for grid services. However, their participation remains low in real-life. One major impediment for popularizing DR in buildings is the lack of cost-effective automation systems that can be widely adopted. Existing optimization-based smart building control algorithms suffer from high costs on both building-specific modeling and on-demand computing resources. To tackle these issues, this paper proposes a cost-effective edge-cloud integrated solution using reinforcement learning (RL). Beside RL’s ability to solve sequential optimal decision-making problems, its adaptability to easy-to-obtain building models and the off-line learning feature are likely to reduce the controller’s implementation cost. Using a surrogate building model learned automatically from building operation data, an RL agent learns an optimal control policy on cloud infrastructure, and the policy is then distributed to edge devices for execution. Simulation results demonstrate the control efficacy and the learning efficiency in buildings of different sizes. A preliminary cost analysis on a 4-zone commercial building shows the annual cost for optimal policy training is only 2.25% of the DR incentive received. Results of this study show a possible approach with higher return on investment for buildings to participate in DR programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Do Melamine and Melamine-Formaldehyde Surface Modifiers Improve Fuel Cell Activity and Durability?

Precious group metal-based catalysts based on Pt- and Pt-alloys are currently used as catalysts for the kinetically sluggish Oxygen Reduction Reaction (ORR) on the cathode of fuel cells. The activity of Pt or Pt-alloy catalysts towards ORR is severely compromised by the adsorption of spectator-species such as sulfonate anions from perfluorosulfonic acid (PFSA) ionomer or Pt-O(H) ad via water activation. Considering recent evidence pointing to the improvement in ORR activity via the use of melamine organic molecule or melamine-formaldehyde copolymeric additives as surface blocking agents for the prevention of sulfonate or Pt-OH ad adsorption, we evaluated these additives in fuel cells. The catalysts were modified with either of these additives and characterized using ex situ and in situ methods to verify successful adsorption and eventual performance in fuel cells. These surface modifying agents were found to suppress Pt-OH ad formation as well as suppress ORR activity. There was no evidence to point out that these additives improved ORR activity and H 2 /air polarization performance in a fuel cell MEA on supported, polycrystalline Pt catalyst.

08 HYDROGEN↗

DOE OSTI2024

XA21-mediated resistance to Xanthomonas oryzae pv. oryzae is dose dependent

The rice receptor kinase XA21 confers broad-spectrum resistance to Xanthomonas oryzae pv. oryzae ( Xoo ), the causal agent of rice bacterial blight disease. To investigate the relationship between the expression level of XA21 and resulting resistance, we generated independent HA-XA21 transgenic rice lines accumulating the XA21 immune receptor fused with an HA epitope tag. Whole-genome sequence analysis identified the T-DNA insertion sites in sixteen independent T0 events. Further, through quantification of the HA-XA21 protein and assessment of the resistance to Xoo strain PXO99 in six independent transgenic lines, we observed that XA21-mediated resistance is dose dependent. In contrast, based on the four agronomic traits quantified in these experiments, yield is unlikely to be affected by the expression level of HA-XA21 . These findings extend our knowledge of XA21-mediated defense and contribute to the growing number of well-defined genomic landing pads in the rice genome that can be targeted for gene insertion without compromising yield.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2003

Macromolecular Expression and Function: A New Paradigm for NASA Risk Assessment

Predicting risks in humans of either acute effects such as bone loss or muscle wasting, or late effects such as cancer, is challenging. To an approximation, this is because uncertainties of exposure to stress factors or toxic agents and the uniformity of processing subsequent damage at the cellular level within a complex set of biological variables degrade the confidence of predicting pathologic outcome. A cellular biodosimeter that simultaneously reports 1) the type of damage due to that exposure, 2) the quantity of damage incurred by that exposure, and 3) the dataset used to assess risk of developing pathologic outcome caused by that exposure would therefore be useful for predicting ultimate risks faced by an individual, such as an astronaut. It is suggested that such a biodosimeter can be based upon analyses of gene-expression and protein expression whereby large datasets of cellular response to damage are obtained and analyzed for expression-profiles correlated with established end points and molecular markers predictive for risks being assessed. The usefulness of multiparametric cellular biodosimeters could be realized by quantitatively profiling these datasets using techniques of bioinformatics. Such an approach contributes to the foundation of molecular epidemiology as a new scientific discipline, and represents a new paradigm of risk assessment.

Richmond, Robert↗

NASA NTRSDate not supplied

Modeling Distributed Situation Awareness in Resilience-based Design of Complex Systems

Human operators play a major role in the resilience of complex systems–while human error is one of the biggest contributors to hazardous events, operators additionally play a critical role in mitigating hazardous events. A key factor underlying this operator resilience is situation awareness–the ability of operators to understand their environment and each other to achieve desired system functions. In contrast to situation awareness-related accident models in the literature, which are largely conceptual in nature, this work proposes the use of a dynamic simulation framework to concretely model both the effects of situation awareness-related human errors and situation awareness-related hazard-mitigating properties using the distributed situation awareness theory. This work then presents specialized model constructs to enable agents’ individual perceptions of the system state and transactions with other agents (and thus distributed situation awareness) to be represented in simulation. To demonstrate this framework, it is then adapted to an aircraft taxiway case study, where it is used to model aircraft conflicts due to lack of vision and poor communications from the air traffic controller. This demonstration shows the potential of using simulation models to rigorously understand situation awareness-related human errors and thus inform the design of resilience.

Resilience Modeling↗

DOE OSTI2026

Discovering the Most Severe K-Point Failure Based on Reinforcement Learning: Preprint

Smart devices are essential to ensure the stability of the power grid and resilience to intermittent energy production. However, smart devices can also be the target of cyber adversaries that may exploit false data injection attacks (FDIAs) to induce unstable grid conditions. A practical consideration of FDIA mitigation approaches is addressed here: given a finite available budget, for which smart device should cyber-threat mitigation be deployed first? In this work, this question is answered by identifying the so-called most-sensitive devices, i.e., the devices that, if compromised, can let an adversary induce the most serious grid instabilities. The method proposed utilizes an adversarial reinforcement learning (RL) framework to identify the k-mostsensitive smart devices (here, smart inverters). The adversarial agent can tamper with the compromised inverters' active and reactive operating power setup points, with the goal of maximizing voltage deviations. Numerical results show that the proposed RL method finds the optimal attack scenarios for 1-point failure and the near-optimal solution for the 2-point case. Additionally, the proposed RL method achieves an 8.8 speed-up ratio in running time compared to the brute force method for the 2-point case.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Modeling Distributed Situation Awareness in Resilience-Based Design of Complex Engineered Systems

Resilience Modeling↗

DOE OSTI2020

Phenanthroline-strapped calix[4]pyrroles: anion receptors displaying affinity reversal as a function of solvent polarity

Calix[4]pyrroles 1 and 2, diametrically strapped with a phenanthroline via ester and amide linkages, respectively, have been synthesized as anion receptors. It was revealed by 1 H NMR spectroscopic analysis that receptors 1 and 2 possessing both hydrogen bonding donors and acceptors were able to bind the bicarbonate anion (as its tetraethylammonium (TEA + ) or sodium salt) in CDCl 3 , as well as in 15% aqueous DMSO with high affinity and selectivity over other anions. The amide-based receptor 2 contains additional potential hydrogen bonding donors relative to its ester-based congener 1. Nevertheless, in CDCl 3 receptor 1 was found to display a higher affinity for all test anions than receptor 2. In contrast, in 15% aqueous DMSO solution the affinities of receptor 2 for anions, in particular chloride, bicarbonate, and dihydrogen phosphate, were enhanced, whereas those of receptor 1 were reduced dramatically with no appreciable interaction being seen in the case of most test anions considered in this study. These reversals in selectivity and affinities underscore the importance of solvent in regulating the recognition features of seemingly similiar anion binding agents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Multiscale modeling of HBV infection integrating intra- and intercellular viral propagation to analyze extracellular viral markers

Chronic infection with hepatitis B virus (HBV) is caused by the persistence of closed circular DNA (cccDNA) in the nucleus of infected hepatocytes. Despite available therapeutic anti-HBV agents, eliminating the cccDNA remains challenging. Thus, quantifying and understanding the dynamics of cccDNA are essential for developing effective treatment strategies and new drugs. However, such study requires repeated liver biopsy to measure the intrahepatic cccDNA, which is basically not accepted because liver biopsy is potentially morbid and not common during hepatitis B treatment. We here aimed to develop a noninvasive method for quantifying cccDNA in the liver using surrogate markers in peripheral blood. We constructed a multiscale mathematical model that explicitly incorporates both intracellular and intercellular HBV infection processes. The model, based on age-structured partial differential equations, integrates experimental data from in vitro and in vivo investigations. By applying this model, we roughly predicted the amount and dynamics of intrahepatic cccDNA within a certain range using specific viral markers in serum samples, including HBV DNA, HBsAg, HBeAg, and HBcrAg. Our study represents a significant step towards advancing the understanding of chronic HBV infection. The noninvasive quantification of cccDNA using our proposed method holds promise for improving clinical analyses and treatment strategies. By comprehensively describing the interactions of all components involved in HBV infection, our multiscale mathematical model provides a valuable framework for further research and the development of targeted interventions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A Retrospective Analysis Reveals That the 2021 Outbreaks of African Swine Fever Virus in Ghana Were Caused by Two Distinct Genotypes

African swine fever virus (ASFV) is the causative agent of African swine fever (ASF), a highly infectious and lethal disease of domesticated swine. Outbreaks of ASF have been mostly restricted to the continent of Africa. The outbreaks that have occurred outside of Africa were controlled by extensive depopulation of the domesticated pig population. However, in 2007, an outbreak occurred in the country of Georgia, where ASFV infected wild pigs and quickly spread across eastern Europe. Since the reintroduction of ASF into Europe, variants of the current pandemic strain, ASFV Georgia 2007/01 (ASFV-G), which is classified as Genotype 2 based on p72 sequencing, have been reported in countries within western Europe, Asia, and the island of Hispaniola. Additionally, isolates collected in 2020 confirmed the presence of variants of ASFV-G in Nigeria. Recently, we reported similar variants of ASFV-G collected from domestic pigs suspected of dying of ASF in Ghana in 2022. Here, we retroactively report, based on full-length sequencing, that similar variants were present in Ghana in 2021. The SNP analysis revealed derivatives of ASFV with distinct genetic markers. Furthermore, we identified three full-length ASFV genomes as Genotype 1, indicating that there were two genotypes circulating in proximity during the 2021 ASF outbreaks in Ghana.

Virology↗

DOE OSTI2021

Chloropyridinyl Esters of Nonsteroidal Anti-Inflammatory Agents and Related Derivatives as Potent SARS-CoV-2 3CL Protease Inhibitors

We report the design and synthesis of a series of new 5-chloropyridinyl esters of salicylic acid, ibuprofen, indomethacin, and related aromatic carboxylic acids for evaluation against SARS-CoV-2 3CL protease enzyme. These ester derivatives were synthesized using EDC in the presence of DMAP to provide various esters in good to excellent yields. Compounds are stable and purified by silica gel chromatography and characterized using 1 H-NMR, 13 C-NMR, and mass spectral analysis. These synthetic derivatives were evaluated in our in vitro SARS-CoV-2 3CLpro inhibition assay using authentic SARS-CoV-2 3CLpro enzyme. Compounds were also evaluated in our in vitro antiviral assay using quantitative VeroE 6 cell-based assay with RNAqPCR. A number of compounds exhibited potent SARS-CoV-2 3CLpro inhibitory activity and antiviral activity. Compound 9a was the most potent inhibitor, with an enzyme IC 50 value of 160 nM. Compound 13b exhibited an enzyme IC 50 value of 4.9 µM. However, it exhibited a potent antiviral EC 50 value of 24 µM in VeroE6 cells. Remdesivir, an RdRp inhibitor, exhibited an antiviral EC 50 value of 2.4 µM in the same assay. We assessed the mode of inhibition using mass spectral analysis which suggested the formation of a covalent bond with the enzyme. To obtain molecular insight, we have created a model of compound 9a bound to SARS-CoV-2 3CLpro in the active site.

3CLpro inhibitors↗