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DOE OSTI2023

PCAfold 2.0—Novel tools and algorithms for low-dimensional manifold assessment and optimization

We describe an update to our open-source Python package, PCAfold, designed to help researchers generate, analyze and improve low-dimensional data manifolds. In the current version, PCAfold 2.0, we introduce novel tools and algorithms for assessing and optimizing low-dimensional manifolds. This includes a method that generates a “map” of local feature sizes that can help pinpoint researchers to problematic regions on a manifold. We introduce a novel cost function that characterizes the quality of a manifold topology with a single number. We develop two algorithms for feature selection based on principal component analysis (PCA) that use the cost function as an objective function to minimize. We introduce a quantity of interest (QoI)-aware dimensionality reduction strategy where data projections are computed using an artificial neural network and are directly optimized towards representing various projection-independent and projection-dependent QoIs. We also introduce an implementation of partition of unity networks (POUnets) for efficient reconstruction of QoIs from low-dimensional manifolds based on combining neural network classification with localized polynomial regression. Our software can be broadly applicable in all domains of science and engineering that aim to reduce data dimensionality, as well as in the fundamental research on representation learning.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Uncovering novel mutational signatures by de novo extraction with SigProfilerExtractor

Mutational signature analysis is commonly performed in cancer genomic studies. Here, we present SigProfilerExtractor, an automated tool for de novo extraction of mutational signatures, and benchmark it against another 13 bioinformatics tools by using 34 scenarios encompassing 2,500 simulated signatures found in 60,000 synthetic genomes and 20,000 synthetic exomes. For simulations with 5% noise, reflecting high-quality datasets, SigProfilerExtractor outperforms other approaches by elucidating between 20% and 50% more true-positive signatures while yielding 5-fold less false-positive signatures. Applying SigProfilerExtractor to 4,643 whole-genome- and 19,184 whole-exome-sequenced cancers reveals four novel signatures. Two of the signatures are confirmed in independent cohorts, and one of these signatures is associated with tobacco smoking. In summary, this report provides a reference tool for analysis of mutational signatures, a comprehensive benchmarking of bioinformatics tools for extracting signatures, and several novel mutational signatures, including one putatively attributed to direct tobacco smoking mutagenesis in bladder tissues.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Novel method for effectively amplifying human peripheral blood T cells in vitro

The use of chimeric antigen receptor-modified T cells (CAR T cells) is an effective therapy for advanced cancer, especially hematological malignancies, and this method has attracted widespread attention in the last several years. The type, number and vitality of the effector cells clearly play important roles in this approach. In this study, to expand the possibility of curing cancer through adoptive cell therapy (ACT), we developed a novel method for effectively obtaining abundant T cells in vitro. The fusion proteins of three cytokines, SA-hIL-2, SA-hIL-7 and SA-hIL-21, were anchored onto biotin magnetic beads to increase the number of cytokines on the surface of the magnetic beads, which increased the local concentration of cytokines and thus promoted the binding of cytokines to T cells. Next, we examined the effects of these modified magnetic beads on the proliferation rate of T cells and CD19 CAR T cells. In this study, we report the expression and purification of the active bifunctional fusion proteins SA-hIL-2, SA-hIL-7 and SA-hIL-21, which were bound to biotin magnetic beads to develop a platform that was employed to increase the local concentration of cytokines. When the cells had been cultured for 14 days, the proliferation rate of the CD3{sup +} T cells in the group that received cytokine-coupled biotin magnetic beads (Beads-SA-CK) was higher than that of the cells in the groups that received soluble cytokines (Soluble-SA-CK) and that of the cells in the standard group (Standard-CK). We speculate that this difference may be the result of the increased expression of Bcl-2 and the increased phosphorylation of Stat5. Moreover, our results preliminarily indicate that compared with the other two treatments, Soluble-SA-CK and Standard-CK, adding cytokine-coupled biotin magnetic beads more effectively increases the proliferation rate of CD19 CAR-T cells. As expected, the CD19 CAR-T cells stimulated by Beads-SA-CK had a stronger anticancer effect than the cells stimulated by the other two treatments. An effective method of preparing abundant T cells in vitro was developed, and it may provide a novel strategy for ACT.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Novel small molecule inhibitor of Kpnβ1 induces cell cycle arrest and apoptosis in cancer cells

Karyopherin beta 1 (Kpnβ1) is a major nuclear import receptor that mediates the import of cellular cargoes into the nucleus. Recently it has been shown that Kpnβ1 is highly expressed in several cancers, and its inhibition by siRNA induces apoptotic cancer cell death, while having little effect on non-cancer cells. This study investigated the effect of a novel small molecule, Inhibitor of Nuclear Import-60 (INI-60), on cancer cell biology, as well as nuclear import activities associated with Kpnβ1, and cancer progression in vivo using cervical and oesophageal cancer cell lines. INI-60 treatment resulted in the inhibition of cancer cell proliferation, colony formation, migration and invasion, and induced a G1/S cell cycle arrest, followed by cancer cell death via apoptosis. Non-cancer cells were minimally affected by INI-60 at concentrations that inhibited cancer cells. INI-60 treatment altered the localisation of Kpnβ1 and its cargoes, NFκB/p65, NFAT and AP-1, and the overexpression of Kpnβ1 reduced INI-60 cytotoxicity. INI-60 also inhibited KYSE 30 oesophageal cancer cell line growth in vivo. Taken together, these results show that INI-60 inhibits the nuclear import of Kpnβ1 cargoes and interferes with cancer cell biology. INI-60 presents as a potential therapeutic approach for cancers of different tissue origins and warrants further investigation as a novel anti-cancer agent.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Novel strategies for modal-based structural material identification

Here, we present modal-based methods for model calibration in structural dynamics, and address several key challenges in the solution of gradient-based optimization problems with eigenvalues and eigenvectors, including the solution of singular Helmholtz problems encountered in sensitivity calculations, non-differentiable objective functions caused by mode swapping during optimization, and cases with repeated eigenvalues. Unlike previous literature that relied on direct solution of the eigenvector adjoint equations, we present a parallel iterative domain decomposition strategy (Adjoint Computation via Modal Superposition with Truncation Augmentation) for the solution of the singular Helmholtz problems. For problems with repeated eigenvalues we present a novel Mode Separation via Projection algorithm, and in order to address mode swapping between inverse iterations we present a novel Injective mode ordering metric. We present the implementation of these methods in a massively parallel finite element framework with the ability to use measured modal data to extract unknown structural model parameters from large complex problems. A series of increasingly complex numerical examples are presented that demonstrate the implementation and performance of the methods in a massively parallel finite element framework [7], [5], using gradient-based optimization techniques in the Rapid Optimization Library (ROL) [21].

36 MATERIALS SCIENCE↗

DOE OSTI2023

RadioGalaxyNET: Dataset and novel computer vision algorithms for the detection of extended radio galaxies and infrared hosts

Abstract Creating radio galaxy catalogues from next-generation deep surveys requires automated identification of associated components of extended sources and their corresponding infrared hosts. In this paper, we introduce RadioGalaxyNET, a multimodal dataset, and a suite of novel computer vision algorithms designed to automate the detection and localization of multi-component extended radio galaxies and their corresponding infrared hosts. The dataset comprises 4 155 instances of galaxies in 2 800 images with both radio and infrared channels. Each instance provides information about the extended radio galaxy class, its corresponding bounding box encompassing all components, the pixel-level segmentation mask, and the keypoint position of its corresponding infrared host galaxy. RadioGalaxyNET is the first dataset to include images from the highly sensitive Australian Square Kilometre Array Pathfinder (ASKAP) radio telescope, corresponding infrared images, and instance-level annotations for galaxy detection. We benchmark several object detection algorithms on the dataset and propose a novel multimodal approach to simultaneously detect radio galaxies and the positions of infrared hosts.

Astronomy & Astrophysics↗

DOE OSTI2021

Modeling of Peptides with Classical and Novel Machine Learning Force Fields: A Comparison

The replacement of classical force fields (FFs) with novel neural-network-based frameworks is an emergent topic in molecular dynamics (MD) simulations. In contrast to classical FFs, which have proven their capability to provide insights into complex soft matter systems at an atomistic resolution, the machine learning (ML) potentials have yet to demonstrate their applicability for soft materials. However, the underlying philosophy, which is learning the energy of an atom in its surrounding chemical environment, makes this approach a promising tool. In particular for the exploration of novel chemical compounds, which have not been considered in the original parametrization of classical FFs. In this article, we study the performance of the ANI-2x ML model and compare the results with those of two classical FFs, namely, CHARMM27 and the GROMOS96 43a1 FF. We explore the performance of these FFs for bulk water and two model peptides, trialanine and a 9-mer of the α-aminoisobutyric acid, in vacuum and water. The results for water describe a highly ordered water structure, with a structure similar to those using ab initio molecular dynamics simulations. The energy landscape of the peptides described by Ramachandran maps show secondary structure basins similar to those of the classical FFs but differ in the position and relative stability of the basins. Details of the sampled structures show a divergent performance of the different models, which can be related either to the short-ranged nature of the ML potentials or to shortcomings of the underlying data set used for training. These findings highlight the current state of the applicability of ANI-2x ML potential for MD simulations of soft matter systems. Simultaneously, they provide insights for future improvements of current ML potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Effect of Building Block Connectivity and Ion Solvation on Electrochemical Stability and Ionic Conductivity in Novel Fluoroether Electrolytes

Novel electrolytes are required for the commercialization of batteries with high energy densities such as lithium metal batteries. Recently, fluoroether solvents have become promising electrolyte candidates because they yield appreciable ionic conductivities, high oxidative stability, and enable high Coulombic efficiencies for lithium metal cycling. However, reported fluoroether electrolytes have similar molecular structures, and the influence of ion solvation in modifying electrolyte properties has not been elucidated. In this work, we synthesize a group of fluoroether compounds with reversed building block connectivity where ether moieties are sandwiched by fluorinated end groups. These compounds can support ionic conductivities as high as 1.3 mS/cm (30 °C, 1 M salt concentration). Remarkably, we report that the oxidative stability of these electrolytes increases with decreasing fluorine content, a phenomenon not observed in other fluoroethers. Using Raman and other spectroscopic techniques, we show that lithium ion solvation is controlled by fluoroether molecular structure, and the oxidative stability correlates with the “free solvent” fraction. Finally, we show that these electrolytes can be cycled repeatedly with lithium metal and other battery chemistries. Understanding the impact of building block connectivity and ionic solvation structure on electrochemical phenomena will facilitate the development of novel electrolytes for next-generation batteries.

36 MATERIALS SCIENCE↗

DOE OSTI2026

The Novel Carbapenem, JDB/PQ-1-219, Has Potent Broad Spectrum Activity against Multi-Drug Resistant Acinetobacter baumannii

Carbapenem resistance in Acinetobacter baumannii, driven largely by class D, along with class A and class B β- lactamases, has severely compromised the utility of these last resort antibiotics. As a result, infections caused by such pathogens are characterized by extremely high mortality rates. Here we describe the antimicrobial activity of the novel C5 methyl-substituted carbapenem JDB/PQ-1−219 against multidrug resistant A. baumannii and the mechanism of its interaction with its major carbapenemase, OXA-23. JDB/PQ-1-219 exhibits potent antimicrobial activity against A. baumannii producing various carbapenemases, with MICs that are all in the clinically susceptible range. The compound has unrestricted ingress through porins and avoids egress by efflux pumps, a unique property when compared to all commercial carbapenems. Kinetic experiments demonstrated that unlike for other carbapenems, acylation of OXA-23 by JDB/ PQ-1-219 is monophasic, and mass spectrometry studies showed that this results from the conversion of all enzyme into a reversible tetrahedral intermediate which gradually transitions into the stable acyl-enzyme complex. No deacylation of this complex is observed over a physiologically relevant time period, making JDB/PQ-1−219 an extremely potent inhibitor of OXA-23. Time-resolved crystallography revealed fine details of active site dynamics, leading to complete inhibition of the enzyme. Together, these studies identify JDB/PQ-1-219 as a uniquely effective novel carbapenem with clinically significant levels of activity against multidrug resistant A. baumannii.

Acinetobacter baumannii↗

DOE OSTI2024

A Novel Membrane-Associated Protein Aids Bacterial Colonization of Maize

The soil environment affected by plant roots and their exudates, termed the rhizosphere, significantly impacts crop health and is an attractive target for engineering desirable agricultural traits. Engineering microbes in the rhizosphere is one approach to improving crop yields that directly minimizes the number of genetic modifications made to plants. Soil microbes have the potential to assist with nutrient acquisition, heat tolerance, and drought response if they can persist in the rhizosphere in the correct numbers. Unfortunately, the mechanisms by which microbes adhere and persist on plant roots are poorly understood, limiting their application. This study examined the membrane proteome shift upon adherence to roots in two bacteria of interest, Klebsiella variicola and Pseudomonas putida. From this surface proteome data, we identified a novel membrane protein from a non-laboratory isolate of P. putida that increases binding to maize roots using unlabeled proteomics. When this protein was moved from the environmental isolate to a common lab strain (P. putida KT2440), we observed increased binding capabilities of P. putida KT2440 to both abiotic mimic surfaces and maize roots. We observed a similar increased binding capability to maize roots when the protein was heterologously expressed in K. variicola and Stutzerimonas stutzeri. With the discovery of this novel binding protein, we outline a strategy for harnessing natural selection and wild isolates to build more persistent strains of bacteria for field applications and plant growth promotion.

rhizosphere, colonization, membrane proteome, plan↗

DOE OSTI2020

Structural and Enzymatic Analyses Reveal the Binding Mode of a Novel Series of Francisella tularensis Enoyl Reductase (FabI) Inhibitors

Because of structural and mechanistic differences between eukaryotic and prokaryotic fatty acid synthesis enzymes, the bacterial pathway, FAS-II, is an attractive target for the design of antimicrobial agents. We have previously reported the identification of a novel series of benzimidazole compounds with particularly good antibacterial effect against Francisella tularensis, a Category A biowarfare pathogen. Herein we report the crystal structure of the F. tularensis FabI enzyme in complex with our most active benzimidazole compound bound with NADH. The structure reveals that the benzimidazole compounds bind to the substrate site in a unique conformation that is distinct from the binding motif of other known FabI inhibitors. Detailed inhibition kinetics have confirmed that the compounds possess a novel inhibitory mechanism that is unique among known FabI inhibitors. These studies could have a strong impact on future antimicrobial design efforts and may reveal new avenues for the design of FAS-II active antibacterial compounds.

Mehboob, Shahila↗

DOE OSTI2025

E3SM‐GCAM: A Synchronously Coupled Human Component in the E3SM Earth System Model Enables Novel Human‐Earth Feedback Research

Abstract Modeling human‐environment feedbacks is critical for assessing the effectiveness of climate change mitigation and adaptation strategies under a changing climate. The Energy Exascale Earth System Model (E3SM) now includes a human component, with the Global Change Analysis Model (GCAM) at its core, that is synchronously coupled with the land and atmosphere components through the E3SM coupling software. Terrestrial productivity is passed from E3SM to GCAM to make climate‐responsive land use and CO 2 emission projections for the next 5‐year period, which are interpolated and passed to E3SM annually. Key variables affected by the incorporation of these feedbacks include land use/cover change, crop prices, terrestrial carbon, local surface temperature, and climate extremes. Regional differences are more pronounced than global differences because the effects are driven primarily by differences in land use. This novel system enables a new type of scenario development and provides a powerful modeling framework that facilitates the addition of other feedbacks between these models. This system has the potential to explore how human responses to climate change impacts in a variety of sectors, including heating/cooling energy demand, water management, and energy production, may alter emissions trajectories and Earth system changes. Plain Language Summary Earth system models help us understand how humans are changing the climate. Currently, these models do not include human systems, so predetermined greenhouse gas, aerosol, and land use change data are input to these models. These data do not reflect human responses to changes projected by Earth system models. We have added a human component to an Earth system model to represent human responses to environmental change and calculate corresponding greenhouse gas and land use change data instead of using predetermined data. Including this human component changes projections of land use, land carbon storage, and regional climate. Key Points We have incorporated a novel, advanceable human component in an Earth system model to simulate human‐Earth feedbacks Including terrestrial productivity feedbacks from the Earth to the human systems affects land change, crop prices, carbon, and climate Regional effects of including terrestrial productivity feedbacks are greater than global effects because land change is the main driver

E3SM↗

DOE OSTI2022

Toward tunable quantum transport and novel magnetic states in Eu 1– x Sr x Mn 1– z Sb 2 ( z < 0.05)

Magnetic semimetals are very promising for potential applications in novel spintronic devices. Nevertheless, realizing tunable topological states with magnetism in a controllable way is challenging. Here, we report novel magnetic states and the tunability of topological semimetallic states through the control of Eu spin reorientation in Eu 1–x Sr x Mn 1–z Sb 2 . Increasing the Sr concentration in this system induces a surprising reorientation of noncollinear Eu spins to the Mn moment direction and topological semimetallic behavior. The Eu spin reorientations to distinct collinear antiferromagnetic orders are also driven by the temperature/magnetic field and are coupled to the transport properties of the relativistic fermions generated by the 2D Sb layers. These results suggest that nonmagnetic element doping at the rare earth element site may be an effective strategy for generating topological electronic states and new magnetic states in layered compounds involving spatially separated rare earth and transition metal layers.

36 MATERIALS SCIENCE↗

DOE OSTI2023

An autonomous laboratory for the accelerated synthesis of novel materials

To close the gap between the rates of computational screening and experimental realization of novel materials, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes

Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10 –8 ) and three regions, 1q21.3 (MRPS21–PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10 –8 ) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Complex of human Melanotransferrin and SC57.32 Fab fragment reveals novel interdomain arrangement with ferric N-lobe and open C-lobe

Melanotransferrin (MTf) is an iron-binding member of the transferrin superfamily that can be membrane-anchored or secreted in serum. On cells, it can mediate transferrin-independent iron uptake and promote proliferation. In serum, it is a transcytotic iron transporter across the blood–brain barrier. MTf has been exploited as a drug delivery carrier to the brain and as an antibody-drug conjugate (ADC) target due to its oncogenic role in melanoma and its elevated expression in triple-negative breast cancer (TNBC). For treatment of TNBC, an MTf-targeting ADC completed a phase I clinical trial (NCT03316794). The structure of its murine, unconjugated Fab fragment (SC57.32) is revealed here in complex with MTf. The MTf N-lobe is in an active and iron-bound, closed conformation while the C-lobe is in an open conformation incompatible with iron binding. This combination of active and inactive domains displays a novel inter-domain arrangement in which the C2 subdomain angles away from the N-lobe. The C2 subdomain also contains the SC57.32 glyco-epitope, which comprises ten protein residues and two N-acetylglucosamines. Our report reveals novel features of MTf and provides a point of reference for MTf-targeting, structure-guided drug design.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Experimental demonstration of novel beam characterization using a polarizable X-band transverse deflection structure

The PolariX TDS (Polarizable X-Band Transverse Deflection Structure) is an innovative TDS-design operating in the X-band frequency-range. The design gives full control of the streaking plane, which can be tuned in order to characterize the projections of the beam distribution onto arbitrary transverse axes. This novel feature opens up new opportunities for detailed characterization of the electron beam. In this paper we present first measurements of the Polarix TDS at the FLASHForward beamline at DESY, including three-dimensional reconstruction of the charge-density distribution of the bunch and slice emittance measurements in both transverse directions. The experimental results open the path toward novel and more extensive beam characterization in the direction of multi-dimensional-beam-phase-space reconstruction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

A novel hardmask-to-substrate pattern transfer method for creating 3D, multi-level, hierarchical, high aspect-ratio structures for applications in microfluidics and cooling technologies

Abstract This letter solves a major hurdle that mars photolithography-based fabrication of micro-mesoscale structures in silicon. Conventional photolithography is usually performed on smooth, flat wafer surfaces to lay a 2D design and subsequently etch it to create single-level features. It is, however, unable to process non-flat surfaces or already etched wafers and create more than one level in the structure. In this study, we have described a novel cleanroom-based process flow that allows for easy creation of such multi-level, hierarchical 3D structures in a substrate. This is achieved by introducing an ultra-thin sacrificial silicon dioxide hardmask layer on the substrate which is first 3D patterned via multiple rounds of lithography. This 3D pattern is then scaled vertically by a factor of 200–300 and transferred to the substrate underneath via a single shot deep etching step. The proposed method is also easily characterizable—using features of different topographies and dimensions, the etch rates and selectivities were quantified; this characterization information was later used while fabricating specific target structures. Furthermore, this study comprehensively compares the novel pattern transfer technique to already existing methods of creating multi-level structures, like grayscale lithography and chip stacking. The proposed process was found to be cheaper, faster, and easier to standardize compared to other methods—this made the overall process more reliable and repeatable. We hope it will encourage more research into hybrid structures that hold the key to dramatic performance improvements in several micro-mesoscale devices.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗