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At least 199 records · Page 11

Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment

Abstract The Columbia Stellarator eXperiment (CSX), currently being designed at Columbia University, aims to test theoretical predictions related to QA plasma behavior, and to pioneer the construction of an optimized stellarator using three-dimensional, non-insulated high-temperature superconducting (NI-HTS) coils. The magnetic configuration is generated by a combination of two circular planar poloidal field (PF) coils and two 3D-shaped interlinked (IL) coils, with the possibility to add windowpane coils to enhance shaping and experimental flexibility. The PF coils and vacuum vessel are repurposed from the former Columbia Non-Neutral Torus experiment, while the IL coils will be custom-wound in-house using NI-HTS tapes. To obtain a plasma shape that meets the physics objectives with a limited number of coils, novel single-stage optimization techniques are employed, optimizing both the plasma and coils concurrently, in particular targeting a tight aspect ratio QA plasma and minimized strain on the HTS tape. Despite the increased complexity due to the expanded degrees of freedom, these methods successfully identify optimized plasma geometries that can be realized by coils meeting engineering specifications. This paper discusses the derivation of the constraints and objectives specific to CSX, and describe how two recently developed single-stage optimization methodologies are applied to the design of CSX. A set of selected configurations for CSX is then described in detail.

Baillod, A. (ORCID:0000000303529180)↗

Nitrogen precooling heat exchanger replacement and control system upgrade in superfluid cryoplant at CMTF

Liquid nitrogen precooling is used in most cryoplants to achieve cooldown to 80 K temperature range. In one such system at Fermilab’s CMTF superfluid cryoplant, where the helium supply directly exchanges heat with liquid nitrogen, freezing of nitrogen occurred inside the heat exchanger due to heat exchanger flow imbalance during a cryoplant trip. Trapped vapor pockets of nitrogen within the frozen heat exchanger channels were formed while warming up the heat exchanger, creating high localized pressure and subsequent damage/rupture of the heat exchanger. Replacement of the heat exchanger was done, and modifications were made in the system to rectify future occurrences. The control system was updated to bypass the heat exchanger entirely if the incoming helium stream temperature drops below 76 K. This was done by repurposing two control valves as heat exchanger bypass valves that were previously used for a redundant 80 K adsorber in the coldbox. Additional modifications were made to further prevent return of large amount of cold helium gas from cold end during abrupt cryoplant shutdown. This modification has ensured high reliability of heat exchanger with prevention of freezing of nitrogen which can damage the heat exchanger.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Fermilab Cryogenic Test Facilities

Fermi National Accelerator Laboratory (Fermilab) has multiple cryogenic test facilities, undertaking testing of superconducting magnets, Superconducting Radio Frequency (SRF) cavities, SRF cryomodules and other helium cryogenic components. The test areas within Fermilab include: Meson Cryogenic Test facility (Meson), Industrial Building 1 (IB-1), Heavy Assembly Building/Illinois Accelerator Research Center (HAB/IARC), New Muon Lab, (NML) and the Cryomodule Test Facility (CMTF). Meson and HAB/IARC utilize repurposed Tevatron era reciprocating engine based cryogenic refrigerator systems, whereas CMTF and IB-1 utilize gas bearing turbine based coldboxes. Each of these test areas support the various Fermilab projects and collaborations including the Linear Coherent Light Source II (LCLS-II), Proton Improvement Plan II (PIP-II), High Luminosity Large Hadron Collider (HL-LHC), and Mu2e. This paper outlines the diverse and extensive cryogenic test capabilities within Fermilab.

43 PARTICLE ACCELERATORS↗

KG-Hub—building and exchanging biological knowledge graphs

Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract–transform–load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial–environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification.

59 BASIC BIOLOGICAL SCIENCES↗

Island of misfit tortoises: waif gopher tortoise health assessment following translocation

Translocation, the intentional movement of animals from one location to another, is a common management practice for the gopher tortoise (Gopherus polyphemus). Although the inadvertent spread of pathogens is a concern with any translocation effort, waif tortoises—individuals that have been collected illegally, injured and rehabilitated or have unknown origins—are generally excluded from translocation efforts due to heightened concerns of introducing pathogens and subsequent disease to naïve populations. However, repurposing these long-lived animals for species recovery is desirable when feasible, and introducing waif tortoises may bolster small populations facing extirpation. The objective of this study was to assess the health of waif tortoises experimentally released at an isolated preserve in Aiken County, SC, USA. Our assessments included visual examination, screening for 14 pathogens using conventional or quantitative polymerase chain reaction (qPCR) and haematological evaluation. Of the 143 individuals assessed in 2017 and 2018, most individuals (76%; n = 109 of 143) had no overt clinical evidence of disease and, when observed, clinical findings were mild. In both years, we detected two known tortoise pathogens, Mycoplasma agassizii and Mycoplasma testudineum, at a prevalence of 10.2–13.9% and 0.0–0.8%, respectively. Additionally, we found emydid Mycoplasma, a bacterium commonly found in box turtles (Terrapene spp.), in a single tortoise that showed no clinical evidence of infection. The presence of nasal discharge was an important, but imperfect, predictor of Mycoplasma spp. infection in translocated tortoises. Hemogram data were comparable with wild populations. Our study is the first comprehensive effort to assess pathogen prevalence and hemogram data of waif gopher tortoises following translocation. Although caution is warranted and pathogen screening necessary, waif tortoises may be an important resource for establishing or augmenting isolated populations when potential health risks can be managed.

60 APPLIED LIFE SCIENCES↗

Mondo: integrating disease terminology across communities

Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities⁠—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.

biomedical informatics↗

Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on 2 selected novel protein-encoding genes, GOLM1 and B4GALT1, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC.

60 APPLIED LIFE SCIENCES↗

Identification of blood protein biomarkers associated with prostate cancer risk using genetic prediction models: analysis of over 140,000 subjects

Prostate cancer (PCa) brings huge public health burden in men. A growing number of conventional observational studies report associations of multiple circulating proteins with PCa risk. However, the existing findings may be subject to incoherent biases of conventional epidemiologic studies. To better characterize their associations, herein, we evaluated associations of genetically predicted concentrations of plasma proteins with PCa risk. In this study, we developed comprehensive genetic prediction models for protein levels in plasma. After testing 1308 proteins in 79 194 cases and 61 112 controls of European ancestry included in the consortia of BPC3, CAPS, CRUK, PEGASUS, and PRACTICAL, 24 proteins showed significant associations with PCa risk, including 16 previously reported proteins and eight novel proteins. Of them, 14 proteins showed negative associations and 10 showed positive associations with PCa risk. For 18 of the identified proteins, potential functional somatic changes of encoding genes were detected in PCa patients in The Cancer Genome Atlas (TCGA). Genes encoding these proteins were significantly involved in cancer-related pathways. We further identified drugs targeting the identified proteins, which may serve as candidates for drug repurposing for treating PCa. In conclusion, this study identifies novel protein biomarker candidates for PCa risk, which may provide new perspectives on the etiology of PCa and improve its therapeutic strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Super-Resolution Ptychography with Small Segmented Detectors

To overcome the spatial resolution limit set by aperture-limited diffraction in traditional scanning transmission electron microscopy, microscopists have developed ptychography enabled by iterative phase retrieval algorithms and high-dynamic-range pixel array detectors. Current detector designs are limited by the data rate off chip, so a high-pixel-count detector has a proportionally lower frame rate than the few-segment detectors used for differential phase contrast (DPC) imaging. This slower acquisition speed leads to heightened vulnerability to scan noise, drift, and potential sample damage. This creates opportunities for repurposing fast segmented detectors for ptychography by trading a reduction in reciprocal space pixels for an increase in real space pixels. Here, we explore a strategy of oversampling in real space and instead apply detector pixel upsampling during the reconstruction process. Further, we demonstrate the viability of achieving super-resolution ptychography on thin objects using only 2 × 2 detector pixels, surpassing the resolution of integrated DPC (iDPC) imaging. With optimization using simulated datasets and experiments on MoTe 2 /WSe 2 bilayer moiré superlattices, we achieved super-resolution ptychography reconstructions under rapid acquisition conditions (37.5 pA, 1 μs dwell time), yielding over 50% improvements in contrast and information limit compared to annular dark field and iDPC imaging on the same detectors.

2D materials↗

DNA Breaks-Mediated Fitness Cost Reveals RNase HI as a New Target for Selectively Eliminating Antibiotic-Resistant Bacteria

Abstract Antibiotic resistance often generates defects in bacterial growth called fitness cost. Understanding the causes of this cost is of paramount importance, as it is one of the main determinants of the prevalence of resistances upon reducing antibiotics use. Here we show that the fitness costs of antibiotic resistance mutations that affect transcription and translation in Escherichia coli strongly correlate with DNA breaks, which are generated via transcription–translation uncoupling, increased formation of RNA–DNA hybrids (R-loops), and elevated replication–transcription conflicts. We also demonstrated that the mechanisms generating DNA breaks are repeatedly targeted by compensatory evolution, and that DNA breaks and the cost of resistance can be increased by targeting the RNase HI, which specifically degrades R-loops. We further show that the DNA damage and thus the fitness cost caused by lack of RNase HI function drive resistant clones to extinction in populations with high initial frequency of resistance, both in laboratory conditions and in a mouse model of gut colonization. Thus, RNase HI provides a target specific against resistant bacteria, which we validate using a repurposed drug. In summary, we revealed key mechanisms underlying the fitness cost of antibiotic resistance mutations that can be exploited to specifically eliminate resistant bacteria.

Balbontín, Roberto↗

A CRISPR-Cas9–integrase complex generates precise DNA fragments for genome integration

CRISPR-Cas9 is an RNA-guided DNA endonuclease involved in bacterial adaptive immunity and widely repurposed for genome editing in human cells, animals and plants. In bacteria, RNA molecules that guide Cas9 s activity derive from foreign DNA fragments that are captured and integrated into the host CRISPR genomic locus by the Cas1-Cas2 CRISPR integrase. How cells generate the specific lengths of DNA required for integrase capture is a central unanswered question of type II-A CRISPR-based adaptive immunity. Here, we show that an integrase supercomplex comprising guide RNA and the proteins Cas1, Cas2, Csn2 and Cas9 generates precisely trimmed 30-base pair DNA molecules required for genome integration. The HNH active site of Cas9 catalyzes exonucleolytic DNA trimming by a mechanism that is independent of the guide RNA sequence. These results show that Cas9 possesses a distinct catalytic capacity for generating immunological memory in prokaryotes.

59 BASIC BIOLOGICAL SCIENCES↗

An LCO-responsive homolog of NODULE INCEPTION positively regulates lateral root formation in Populus sp.

Abstract The transcription factor NODULE INCEPTION (NIN) has been studied extensively for its multiple roles in root nodule symbiosis within plants of the nitrogen-fixing clade (NFC) that associate with soil bacteria, such as rhizobia and Frankia. However, NIN homologs are present in plants outside the NFC, suggesting a role in other developmental processes. Here, we show that the biofuel crop Populus sp., which is not part of the NFC, contains eight copies of NIN with diversified protein sequence and expression patterns. Lipo-chitooligosaccharides (LCOs) are produced by rhizobia and a wide range of fungi, including mycorrhizal ones, and act as symbiotic signals that promote lateral root formation. RNAseq analysis of Populus sp. treated with purified LCO showed induction of the PtNIN2 subfamily. Moreover, the expression of PtNIN2b correlated with the formation of lateral roots and was suppressed by cytokinin treatment. Constitutive expression of PtNIN2b overcame the inhibition of lateral root development by cytokinin under high nitrate conditions. Lateral root induction in response to LCOs likely represents an ancestral function of NIN retained and repurposed in nodulating plants, as we demonstrate that the role of NIN in LCO-induced root branching is conserved in both Populus sp. and legumes. We further established a visual marker of LCO perception in Populus sp. roots, the putative sulfotransferase PtSS1 that can be used to study symbiotic interactions with the bacterial and fungal symbionts of Populus sp.

Irving, Thomas B. (ORCID:0000000330404543)↗

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

97 MATHEMATICS AND COMPUTING↗

Shear Is Not Always Simple: Rate-Dependent Effects of Flow Type on Granular Rheology

we report that despite there being an infinite variety of types of flow, most rheological studies focus on a single type such as simple shear. Using discrete element simulations, we explore bulk granular systems in a wide range of flow types at large strains and characterize invariants of the stress tensor for different inertial numbers and interparticle friction coefficients. We identify a strong dependence on the type of flow, which grows with increasing inertial number or friction. Standard models of yielding, repurposed to describe the dependence of the stress on flow type in steady-state flow and at finite rates, are compared with data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Constraints on the Decay of 180⁢𝑚 Ta

180m Ta is a rare nuclear isomer whose decay has never been observed. Its remarkably long lifetime surpasses the half-lives of all other known β and electron capture decays due to the large K-spin differences and small energy differences between the isomeric and lower energy states. Detecting its decay presents a significant experimental challenge but could shed light on neutrino-induced nucleosynthesis mechanisms, the nature of dark matter and K-spin violation. For this study, we repurposed the Majorana Demonstrator, an experimental search for the neutrinoless double-beta decay of 76 Ge using an array of high-purity germanium detectors, to search for the decay of 180m Ta. More than 17 kilograms, the largest amount of tantalum metal ever used for such a search was installed within the ultra-low background Majorana Demonstrator detector array. In this paper we present results from the first year of Ta data taking and provide an updated limit for the 180m Ta half-life on the different decay channels. With new limits up to 1.5 × 10 19 years, we improved existing limits by one to two orders of magnitude. Furthermore, this result is the most sensitive search for a single β and electron capture decay ever achieved.

150 ≤ A ≤ 189↗

Absorption of Axion Dark Matter in a Magnetized Medium

Detection of axion dark matter heavier than an meV is hindered by its small wavelength, which limits the useful volume of traditional experiments. This problem can be avoided by directly detecting in-medium excitations, whose ∼ meV – eV energies are decoupled from the detector size. We show that for any target inside a magnetic field, the absorption rate of electromagnetically coupled axions into in-medium excitations is determined by the dielectric function. As a result, the plethora of candidate targets previously identified for sub-GeV dark matter searches can be repurposed as broadband axion detectors. We find that a kg yr exposure with noise levels comparable to recent measurements is sufficient to probe parameter space currently unexplored by laboratory tests. Noise reduction by only a few orders of magnitude can enable sensitivity to the QCD axion in the ∼ 10 meV – 10 eV mass range. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

X-ray crystal structure of a designed rigidified imaging scaffold in the ligand-free conformation

Imaging scaffolds composed of designed protein cages fused to designed ankyrin repeat proteins (DARPins) have enabled the structure determination of small proteins by cryogenic electron microscopy (cryo-EM). One particularly well characterized scaffold type is a symmetric tetrahedral assembly composed of 24 subunits, 12 A and 12 B, which has three cargo-binding DARPins positioned on each vertex. Here, the X-ray crystal structure of a representative tetrahedral scaffold in the apo state is reported at 3.8 Å resolution. The X-ray crystal structure complements recent cryo-EM findings on a closely related scaffold, while also suggesting potential utility for crystallographic investigations. As observed in this crystal structure, one of the three DARPins, which serve as modular adaptors for binding diverse `cargo' proteins, present on each of the vertices is oriented towards a large solvent channel. The crystal lattice is unusually porous, suggesting that it may be possible to soak crystals of the scaffold with small (≤30 kDa) protein cargo ligands and subsequently determine cage–cargo structures via X-ray crystallography. The results suggest the possibility that cryo-EM scaffolds may be repurposed for structure determination by X-ray crystallography, thus extending the utility of electron-microscopy scaffold designs for alternative structural biology applications.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal structure of N-terminally hexahistidine-tagged Onchocerca volvulus macrophage migration inhibitory factor-1

Onchocerca volvulus causes blindness, onchocerciasis, skin infections and devastating neurological diseases such as nodding syndrome. New treatments are needed because the currently used drug, ivermectin, is contraindicated in pregnant women and those co-infected with Loa loa . The Seattle Structural Genomics Center for Infectious Disease (SSGCID) produced, crystallized and determined the apo structure of N-terminally hexahistidine-tagged O. volvulus macrophage migration inhibitory factor-1 (His- Ov MIF-1). Ov MIF-1 is a possible drug target. His- Ov MIF-1 has a unique jellyfish-like structure with a prototypical macrophage migration inhibitory factor (MIF) trimer as the `head' and a unique C-terminal `tail'. Deleting the N-terminal tag reveals an Ov MIF-1 structure with a larger cavity than that observed in human MIF that can be targeted for drug repurposing and discovery. Removal of the tag will be necessary to determine the actual biological oligomer of Ov MIF-1 because size-exclusion chomatographic analysis of His- Ov MIF-1 suggests a monomer, while PISA analysis suggests a hexamer stabilized by the unique C-terminal tails.

Kimble, Amber D. (ORCID:0000000167851596)↗