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DOE OSTI2020

Bent DNA Bows as Sensing Amplifiers for Detecting DNA-Interacting Salts and Molecules

Due to the central role of DNA, its interactions with inorganic salts and small organic molecules are important. For example, such interactions play important roles in various fundamental cellular processes in living systems and are involved in many DNA-damage related diseases. Strategies to improve the sensitivity of existing techniques for studying DNA interactions with other molecules would be appreciated in situations where the interactions are too weak. Here we report our development and demonstration of bent DNA bows for amplifying, sensing, and detecting the interactions of 14 inorganic salts and small organic molecules with DNA. With the bent DNA bows, these interactions were easily visualized and quantified in gel electrophoresis, which were difficult to measure without bending. In addition, the strength of the interactions of DNA with the various salts/molecules were quantified using the modified Hill equation. This work highlights the amplification effects of the bending elastic energy stored in the DNA bows and the potential use of the DNA bows for quantitatively measuring DNA interactions with small molecules as simple economic methods; it may also pave the way for exploiting the bent DNA bows for other applications such as screening DNA-interacting molecules and drugs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Structural basis for C-degron selectivity across KLHDCX family E3 ubiquitin ligases

Abstract Specificity of the ubiquitin-proteasome system depends on E3 ligase-substrate interactions. Many such pairings depend on E3 ligases binding to peptide-like sequences - termed N- or C-degrons - at the termini of substrates. However, our knowledge of structural features distinguishing closely related C-degron substrate-E3 pairings is limited. Here, by systematically comparing ubiquitylation activities towards a suite of common model substrates, and defining interactions by biochemistry, crystallography, and cryo-EM, we reveal principles of C-degron recognition across the KLHDCX family of Cullin-RING ligases (CRLs). First, a motif common across these E3 ligases anchors a substrate’s C-terminus. However, distinct locations of this C-terminus anchor motif in different blades of the KLHDC2, KLHDC3, and KLHDC10 β-propellers establishes distinct relative positioning and molecular environments for substrate C-termini. Second, our structural data show KLHDC3 has a pre-formed pocket establishing preference for an Arg or Gln preceding a C-terminal Gly, whereas conformational malleability contributes to KLHDC10’s recognition of varying features adjacent to substrate C-termini. Finally, additional non-consensus interactions, mediated by C-degron binding grooves and/or by distal propeller surfaces and substrate globular domains, can substantially impact substrate binding and ubiquitylatability. Overall, the data reveal combinatorial mechanisms determining specificity and plasticity of substrate recognition by KLDCX-family C-degron E3 ligases.

Science & Technology - Other Topics↗

DOE OSTI2021

Lack of long-term effect of coarse woody debris dam restoration on ecosystem functioning and water quality in Coastal Plain streams

Coarse woody debris (CWD) addition is a restoration technique that has been used to reduce effects of landscape disturbance on instream habitat. However, efficacy of this technique for improving ecosystem condition is not well established, in part because monitoring designed to evaluate long-term efficacy is rare. We assessed the effectiveness of CWD additions in disturbed Coastal Plain streams at Fort Benning Military Installation, Georgia, USA, 14 y after initial restoration. In October 2003, 4 disturbed streams received CWD additions (restored streams), and 4 streams were left as unrestored controls. Pre-restoration (2001–2003) and post-restoration (2003–2006) monitoring of nutrient uptake, stream metabolism, and water-quality variables revealed 1) minimal change in water-quality variables, 2) increased stream metabolism and nutrient-uptake rates immediately following restoration, and 3) decreased metabolism and uptake over the remainder of the 3-y post-restoration period. We returned to these streams in 2017 and 2018, measured the same variables, and found minimal long-term effects of restoration on water quality, nutrient uptake, and whole-stream metabolism indicators; however, streamwater pH decreased in all streams 14 y after restoration, and there was a weak treatment × period interaction, indicating that CWD additions may decrease pH in the long term. Further, we found few relationships between watershed disturbance and water-quality variables and ecosystem function metrics, although some relationships were apparent during certain seasons and years. Furthermore, our study is one of the few that have assessed the long-term effects of CWD additions, or any other stream-restoration technique, on ecosystem function. These long-term assessments may be necessary to determine if restorations are a good use of limited resources.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Multiple interaction points in ghost collisions

The Ghost Collider makes use of unique “ghost” bunches, which are electrically neutral combinations of electrons and positrons within the same RF bucket, eliminates the beam-beam effects typically present at the interaction point (IP) in conventional colliders. This allows for the novel possibility of placing multiple interaction regions in series, achieving additive luminosity without introducing significant disruption. However, to get higher luminosity, the beta functions at the IP reaches millimeter scale, which in turn adds significant chromatic contribution to the collider. Correcting these chromatic effects is essential to maintain beam stability and ensure high luminosity during collider operation. By carefully adjusting the phase advance between two IRs that are placed in series, it becomes possible to cancel chromaticity globally, enabling stable collider operation while preserving high luminosity. In this paper we discuss the design of such IR/IRs to be used in a ghost collider.

Accelerator Physics↗

DOE OSTI2020

Dynamics of millicharged dark matter in supernova remnants

Dark matter could have a small electromagnetic charge, provided the charge-to-mass ratio is much less than that of electrons or protons. This candidate, commonly known as millicharged dark matter (mDM), would form a plasma and interact with the interstellar medium and electromagnetic fields within galaxies. In general, understanding the dynamics of mDM requires consideration of collective plasma effects. It has been proposed that mDM can be accelerated in supernova remnants, forming a dark cosmic ray population that would leave distinct experimental signatures. In this work, we study a microphysical model where mDM is shocked by a supernova remnant and isotropized in the frame of the expanding fluid. We find that for | q χ / m χ | ≳ 10 – 13 e / MeV , the isotropization length for electromagnetic plasma instabilities is much shorter than the size of the supernova remnant. This is a necessary, though not sufficient, first step for formation of a Fermi-accelerated mDM component, and determining the size of this component requires further study. Finally, we discuss additional implications of mDM interactions in supernova remnants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Improving missing transverse momentum estimation with a deep neural network

At hadron colliders, the net transverse momentum of particles that do not interact with the detector (missing transverse momentum, $^→_𝑝$$^{miss}_{T}$) is a crucial observable in many analyses. In the standard model, $^→_𝑝$$^{miss}_{T}$ originates from neutrinos. Many beyond-the-standard-model particles, such as dark matter candidates, are also expected to leave the experimental apparatus undetected. This paper presents a novel deep neural network based $^→_𝑝$$^{miss}_{T}$ estimator, DeepMET, developed by the CMS Collaboration at the LHC. The DeepMET algorithm produces a weight for each reconstructed particle based on its properties. The estimator is based on the negative vector sum of the weighted transverse momenta of all reconstructed particles in an event. Compared with other estimators currently employed by CMS, DeepMET improves the $^→_𝑝$$^{miss}_{T}$ resolution by 10%–30%, shows improvement for a wide range of final states, is easier to train, and is more resilient against the effects of additional proton-proton interactions accompanying the collision of interest.

artificial neural networks↗

DOE OSTI2023

Towards Resilient Design of Leader-following Consensus with Attack Identification and Privacy Preservation Capabilities

This paper considers a leader-following consensus in the presence of unknown but bounded cyber-attacks. Specifically, we consider the following cyber-attack scenarios: (i) an attacker aims to destabilize the consensus dynamics by injecting exogenous signals to both the actuators of the followers and/or the communication network, (ii) an eavesdropper adversary aims to obtain information on the physical state of the agents. To this end, a novel resilient leader-following consensus algorithm based on a competitive interaction method is proposed. In addition, it is demonstrated that by appropriately choosing the information exchanged between the agents, the proposed control framework also enables the cooperative system to either distributively identify the compromised communication links in real-time or to protect the privacy of the physical state of the agents from the eavesdropper. Here, a numerical example is provided to illustrate the proposed resilient control algorithms.

Gusrialdi, Azwirman↗

DOE OSTI2024

Factor VIII moiety of recombinant Factor VIII Fc fusion protein impacts Fc effector function and CD16 + NK cell activation

Recombinant Factor VIII-Fc fusion protein (rFVIIIFc) is an enhanced half-life therapeutic protein product used for the management of hemophilia A. Recent studies have demonstrated that rFVIIIFc interacts with Fc gamma receptors (FcγR) resulting in the activation or inhibition of various FcγR-expressing immune cells. We previously demonstrated that rFVIIIFc, unlike recombinant Factor IX-Fc (rFIXFc), activates natural killer (NK) cells via Fc-mediated interactions with FcγRIIIA (CD16). Additionally, we showed that rFVIIIFc activated CD16 + NK cells to lyse a FVIII-specific B cell clone. Here, we used human NK cell lines and primary NK cells enriched from peripheral blood leukocytes to study the role of the FVIII moiety in rFVIIIFc-mediated NK cell activation. Following overnight incubation of NK cells with rFVIIIFc, cellular activation was assessed by measuring secretion of the inflammatory cytokine IFNγ by ELISA or by cellular degranulation. We show that anti-FVIII, anti-Fc, and anti-CD16 all inhibited indicating that these molecules were involved in rFVIIIFc-mediated NK cell activation. To define which domains of FVIII were involved, we used antibodies that are FVIII domain-specific and demonstrated that blocking FVIII C1 or C2 domain-mediated membrane binding potently inhibited rFVIIIFc-mediated CD16 + NK cell activation, while targeting the FVIII heavy chain domains did not. We also show that rFVIIIFc binds CD16 with about five-fold higher affinity than rFIXFc. Based on our results we propose that FVIII light chain-mediated membrane binding results in tethering of the fusion protein to the cell surface, and this, together with increased binding affinity for CD16, allows for Fc-CD16 interactions to proceed, resulting in NK cellular activation. Our working model may explain our previous results where we observed that rFVIIIFc activated NK cells via CD16, whereas rFIXFc did not despite having identical IgG1 Fc domains.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Compatibility of molten plutonium with wrought and additively manufactured metal crucibles

Understanding plutonium’s interaction with metals is crucial for optimizing pyrochemical operations, nuclear fuel containment, and various actinide processing techniques. Traditionally, tantalum crucibles are employed for plutonium processing due to their high durability, excellent temperature stability, and low solubility in plutonium. However, tantalum faces challenges such as plutonium wetting and diffusion, making surface coatings particularly important for crucibles in pyrochemical applications to enhance corrosion resistance against plutonium. Tantalum is also expensive and difficult to machine, prompting the need for advanced manufacturing techniques to address these challenges. Here, in this work, we investigate the interaction of Pu with tantalum and titanium crucibles fabricated using both traditional machining methods and laser powder bed fusion (LPBF) additive manufacturing (AM). LPBF-AM is an advanced technique that allows for the creation of complex geometries from traditionally difficult-to-machine metals by using a high-powered laser to build parts. Previous studies of conventional manufactured tantalum have utilized oxidation and carburization of the surface to mitigate plutonium wetting; however, no studies of surface modified LPBF-AM material have been undertaken. These studies are crucial, given the typical differences in the grain structure between conventional and LPBF-AM materials. All crucibles underwent differential scanning calorimetry to confirm the melting of plutonium. Subsequently, the crucibles were sectioned and mounted in epoxy for microstructural analysis using optical microscopy and scanning electron microscopy. This investigation, comparing the performance of wrought vs AM metal crucibles, provides a basis for future tooling applications in actinide processing techniques and can address the challenges associated with traditional machining, particularly in pyrochemical applications.

Actinides↗

DOE OSTI2025

Accuracy and capacity of modern Hopfield networks with synaptic noise.

We study the retrieval accuracy and capacity of modern Hopfield networks of with two-state (Ising) spins interacting via modified Hebbian 𝑛 -spin interactions. In particular, we consider systems where the interactions deviate from the Hebb rule through additive or multiplicative noise or through clipping or deleting interactions. We find that the capacity scales as 𝑁𝑛−1 with the number of spins 𝑁 in all cases, but with a prefactor reduced compared to the Hebbian case. For 𝑛=2 our results agree with the previously known results for the conventional 𝑛=2 Hopfield network.

Bhattacharjee, Sharba↗

DOE OSTI2023

Nitrogen addition alters soil fungal communities, but root fungal communities are resistant to change

Plants are colonized by numerous microorganisms serving important symbiotic functions that are vital to plant growth and success. Understanding and harnessing these interactions will be useful in both managed and natural ecosystems faced with global change, but it is still unclear how variation in environmental conditions and soils influence the trajectory of these interactions. In this study, we examine how nitrogen addition alters plant-fungal interactions within two species of Populus - Populus deltoides and P. trichocarpa. In this experiment, we manipulated plant host, starting soil (native vs. away for each tree species), and nitrogen addition in a fully factorial replicated design. After ~10 weeks of growth, we destructively harvested the plants and characterized plant growth factors and the soil and root endosphere fungal communities using targeted amplicon sequencing of the ITS2 gene region. Overall, we found nitrogen addition altered plant growth factors, e.g., plant height, chlorophyll density, and plant N content. Interestingly, nitrogen addition resulted in a lower fungal alpha diversity in soils but not plant roots. Further, there was an interactive effect of tree species, soil origin, and nitrogen addition on soil fungal community composition. Starting soils collected from Oregon and West Virginia were dominated by the ectomycorrhizal fungi Inocybe (55.8% relative abundance), but interestingly when P. deltoides was grown in its native West Virginia soil, the roots selected for a high abundance of the arbuscular mycorrhizal fungi, Rhizophagus. These results highlight the importance of soil origin and plant species on establishing plant-fungal interactions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Probing earth-bound dark matter with nuclear reactors

Strongly-interacting dark matter can be accumulated in large quantities inside the Earth, and for dark matter particles in a few GeV mass range, it can exist in large quantities near the Earth’s surface. We investigate the constraints imposed on such dark matter properties by its upscattering by fast neutrons in nuclear reactors with subsequent scattering in nearby well-shielded dark matter detectors, schemes which are already used for searches of the coherent reactor neutrino scattering. We find that the existing experiments cover new parameter space on the spin-dependent interaction between dark matter and the nucleon. Similar experiments performed with research reactors, and lesser amount of shielding, may provide additional sensitivity to strongly-interacting dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

Abstract In droplet-on-demand liquid metal jetting (DoD-LMJ) additive manufacturing, complex physical interactions govern the droplet characteristics, such as size, velocity, and shape. These droplet characteristics, in turn, determine the functional quality of the printed parts. Hence, to ensure repeatable and reliable part quality it is necessary to monitor and control the droplet characteristics. Existing approaches for in-situ monitoring of droplet behavior in DoD-LMJ rely on high-speed imaging sensors. The resulting high volume of droplet images acquired is computationally demanding to analyze and hinders real-time control of the process. To overcome this challenge, the objective of this work is to use time series data acquired from an in-process millimeter-wave sensor for predicting the size, velocity, and shape characteristics of droplets in DoD-LMJ process. As opposed to high-speed imaging, this sensor produces data-efficient time series signatures that allows rapid, real-time process monitoring. We devise machine learning models that use the millimeter-wave sensor data to predict the droplet characteristics. Specifically, we developed multilayer perceptron-based non-linear autoregressive models to predict the size and velocity of droplets. Likewise, a supervised machine learning model was trained to classify the droplet shape using the frequency spectrum information contained in the millimeter-wave sensor signatures. High-speed imaging data served as ground truth for model training and validation. These models captured the droplet characteristics with a statistical fidelity exceeding 90%, and vastly outperformed conventional statistical modeling approaches. Thus, this work achieves a practically viable sensing approach for real-time quality monitoring of the DoD-LMJ process, in lieu of the existing data-intensive image-based techniques.

Gaikwad, Aniruddha (ORCID:0000000285642621)↗

DOE OSTI2020

Thermodynamic Modeling of the Al-Ce-Cu-Mg-Si System and Its Application to Aluminum-Cerium Alloy Design

Recently discovered AlCe alloys have shown promise in a number of applications, but the propensity of Ce to react with Al and other alloying elements can complicate the phase equilibria and design approach. To solve this, the CALPHAD method is used to explore an alloy within the quinary Al-Ce-Cu-Mg-Si system by developing a thermodynamic database with self-consistent parameters. The database includes a description of all 10 binary systems and 8 ternary systems consisting of: (i) 6 Al-containing ternaries (Al-Ce-Cu, Al-Ce-Mg, Al-Ce-Si, Al-Cu-Mg, Al-Cu-Si and Al-Mg-Si); and (ii) 2 additional ternaries that include Mg and Si (i.e., Ce-Mg-Si and Cu-Mg-Si). The thermodynamic description for the Al-Ce-Mg and Al-Mg-Si systems were reassessed to ensure consistency with the binary systems and the Ce-Mg-Si system is presented for the first time and compared to theoretical data from DFT (Density Functional Theory). In addition to the ternary interactions, the quaternary compound Al3Cu2Mg9Si7 and solid solution extending from the ternary Al2CuMg phase (Al,Si)2CuMg are incorporated. The CALPHAD method is employed and leveraged through the use of a Materials Design Simulator (MDS) to accelerate the design of novel aluminum-cerium-based alloys. The combination of a CALPHAD-based framework with experimental efforts and industrial insight permits the development of three new Al-Ce alloys: Al-3.5Ce-0.4Mg-7Si (Ce-modified A356), Al-5Ce-1Cu-0.5Mg-10Si and Al-19Ce-0.9Mg-1.1Si.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Advantages of tandem versus simultaneous operation: The case of isomerization/hydrogenation of terpinolene epoxide to Terpinen-4-ol using a Ni/TiO 2 -SiO 2 bifunctional catalyst

The conversion of terpinolene epoxide to terpinen-4-ol is a desirable chemical transformation for the production of a valuable intermediate. Here this report describes a one-pot, two-step system for the reaction that uses a bifunctional Ni/TiO 2 -SiO 2 catalyst with isomerization and hydrogenation capabilities. The TiO 2 -SiO 2 serves to isomerize the starting epoxide. The Ni component works to hydrogenate the allylic double bond. The tandem system achieves a high 64% yield of terpinen-4-ol. X-ray diffraction analysis showed that TiO 2 -SiO 2 was a mixed binary oxide, and Fourier transform infrared spectroscopy of adsorbed pyridine suggested that acid sites were mainly Lewis acid sites. Electron microscopy showed that the Ni/TiO 2 -SiO 2 catalyst consisted of spherical particles comprising a titanosilicate phase with highly dispersed zero-valent Ni or anatase on the surface. Additionally, there was strong interaction between Ni and the TiO 2 -SiO 2 mixed oxides. Control kinetic experiments demonstrated that the tandem use of the catalysts was more effective than simultaneous operation.

42 ENGINEERING↗

DOE OSTI2020

Tracking natural CO 2 migration through a sandstone aquifer using Sr, U and C isotopes: Chimayó, New Mexico, USA

The geochemical and isotopic characteristics of groundwaters in Chimayó, New Mexico, reflect processes that affect water quality in the Tesuque Aquifer, which overlies a leaking natural CO 2 source in a structurally complex region. In this study, select isotopes (δ 13 C, 87 Sr/ 86 Sr, 234 U/ 238 U) are applied to groundwaters to better understand CO 2 transport mechanisms and related water-rock interactions that impact Chimayó groundwater. Carbon stable isotope ratios of dissolved inorganic carbon (DIC; δ 13 CDIC = -15.10‰ to 4.50‰) identify a distinct source of upward-migrating CO 2 that interacts with the groundwater. Additionally, groundwater 87 Sr/ 86 Sr compositions (0.7098 to 0.7154) reflect intrusion of varying amounts of saline water associated with the high CO 2 source, while 234 U/ 238 U ratios corroborate presence of deep groundwater and suggest impacts from distinctive natural uranium sources are affecting groundwater. Previous work proposed two CO 2 transport mechanisms at the site: (1) dissolved in deep brine that underlies the aquifer and (2) in the gas phase; this study uses isotope mixing models to identify wells that are affected by these CO 2 transport mechanisms and demonstrates that both transport mechanisms are associated with impaired groundwaters. Overall, this study demonstrates that applying multiple isotope systems (δ 13 CDIC, 87 Sr/ 86 Sr, 234 U/ 238 U) is a dynamic tool for identifying and measuring the impact of CO 2 leakage from a sequestration site.

58 GEOSCIENCES↗

DOE OSTI2024

Estimating soil N 2 O emissions induced by organic and inorganic fertilizer inputs using a Tier-2, regression-based meta-analytic approach for U.S. agricultural lands

Consistent methods are essential for generating country and region-specific estimates of greenhouse gas (GHG) emissions used for reporting and policymaking. The estimates of direct N 2 O emissions from U.S. agricultural soils have primarily relied on the use of emission factors (EFs, Tier-1) and process-based models (Tier-3). However, Tier-1 estimates are relatively crude while Tier-3 calculations can be costly. This work addressed this gap by developing a Tier-2, regression-based approach by leveraging a meta-database containing 1883 field N 2 O observations together with environmental and management covariates from 139 studies. Our results estimated higher monthly soil N 2 O emissions (N 2 O m , kg N/ha) during the growing season (0.38) than the fallow period (0.15), highlighting the importance of considering measurement periods when utilizing meta-databases for analyzing N 2 O drivers. Significantly different N 2 O m were found for tillage practices (conventional > no-till: 0.42 > 0.27), fertilizer type (liquid > solid manure: 0.55 > 0.32), and soil texture (fine > coarse: 0.36 > 0.22). The comparisons of the influence of crop type and rotation, water management, and soil order on N 2 O emissions are complicated by regional data availability and interactions among different factors. Additionally, the finding that N 2 O emissions reported based on area (N 2 O m ), N input rate (EF), or yield can alter treatment rankings underscores the need to establish transparent criteria for rewarding or discouraging regionally-based management practices using N 2 O metrics. Finally, we show how General Linear Models (GLMs) can be used to estimate country and regional Tier-2 N 2 O m using a suite of covariates. Our GLMs identified tillage, water management, N input type and rate, soil properties, and elevation as the most influential covariates for the conterminous U.S. The limited accuracy of regional-scale GLMs, however, suggests the need to further improve the quality and availability of GHG and covariate data through concerted efforts in data collection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

LncRNA DLEU2 promotes cervical cancer cell proliferation by regulating cell cycle and NOTCH pathway

Highlights: • LncRNA DLEU2 is upregulated and related to tumor topography in cervical cancer. • LncRNA DLEU2 promotes cervical cancer cell proliferation. • LncRNA DLEU2 promotes the progression of the cell cycle. • LncRNA DLEU2 inhibits the activity of the Notch signaling pathway. Long noncoding RNAs (lncRNAs) are known to play a crucial role in the onset and progression of cervical cancer (CC). Here, the results of RNA microarray and RNA-sequencing dataset analysis showed that lncRNA DLEU2 was significantly upregulated in CC tissues. Clinicopathologic analysis indicated that lncRNA DLEU2 was closely related to tumor topography. Functional experiments and bioinformatics analysis revealed that lncRNA DLEU2 promoted CC cell proliferation and accelerated the cell cycle. Mechanistically, lncRNA DLEU2 promoted the progression of the cell cycle and inhibited the activity of the Notch signaling pathway by inhibiting p53 expression. Additionally, lncRNA DLEU2 probably interacted with ZFP36 Ring Finger Protein (ZFP36) to inhibit the expression of p53. In conclusion, this study revealed the function of lncRNA DLEU2 in CC tumorigenesis, suggesting new therapeutic targets in CC.

60 APPLIED LIFE SCIENCES↗