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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The structural and functional integrities of porcine myocardium are mostly preserved by cryopreservation

Structural and functional studies of heart muscle are important to gain insights into the physiological bases of cardiac muscle contraction and the pathological bases of heart disease. While fresh muscle tissue works best for these kinds of studies, this is not always practical to obtain, especially for heart tissue from large animal models and humans. Conversely, tissue banks of frozen human hearts are available and could be a tremendous resource for translational research. It is not well understood, however, how liquid nitrogen freezing and cryostorage may impact the structural integrity of myocardium from large mammals. In this study, we directly compared the structural and functional integrity of never-frozen to previously frozen porcine myocardium to investigate the consequences of freezing and cryostorage. X-ray diffraction measurements from hydrated tissue under near-physiological conditions and electron microscope images from chemically fixed porcine myocardium showed that prior freezing has only minor effects on structural integrity of the muscle. Furthermore, mechanical studies similarly showed no significant differences in contractile capabilities of porcine myocardium with and without freezing and cryostorage. These results demonstrate that liquid nitrogen preservation is a practical approach for structural and functional studies of myocardium.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from Machine-Learning-Informed Sites across the Contiguous United States (v6)

This dataset supports a broader study examining hyporheic zone respiration rates to improve predictive models at a contiguous United States (CONUS) scale. The CONUS-Scale Model-Sample Study (CM) was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the CONUS. New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Sampling began in April 2022 and ended in October 2023. In addition to the widely distributed CONUS sites, a more spatially focused sampling occurred in the Yakima River Basin, WA in summer 2022. Data from this more spatially intensive sampling occurred under the label “Second Spatial Study (SSS)” and were also included in the machine learning models. Other data types collected from SSS that were not part of CM were published in a separate data package (https://data.ess-dive.lbl.gov/view/doi:10.15485/1969566). This data package was originally published in February 2023. It was updated in June 2023 (v2; new and modified files); December 2023 (v3; new and modified files); June 2024 (v4; new and modified files); April 2024 (v5; new and modified files); and September 2025 (v6; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocols; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) surface water major cations and anions and averages; (4) sediment grain size data; (5) sediment iron (II) data and averages; (6) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment specific surface area; (11) sediment percent carbon and nitrogen; (12) sediment gravimetric moisture and averages; (15) sediment X-ray diffraction (XRD) data; (16) sediment adenosine triphosphate (ATP) and averages; (17) a subfolder with sediment incubation respiration data, scripts, and plots; (18) surface water and sediment FTICR methods; and (19) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS).The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine learning model inputs, outputs, and scripts associated with “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Artificial intelligence-guided iterations between observations and modeling significantly improve environmental predictions” (Malhotra et al., in prep). This effort was designed following ICON (integrated, coordinated, open, and networked) principles to facilitate a model-experiment (ModEx) iteration approach, leveraging crowdsourced sampling across the contiguous United States (CONUS). New machine learning models were created every month to guide sampling locations. Data from the resulting samples were used to test and rebuild the machine learning models for the next round of sampling guidance. Associated sediment and water geochemistry and in situ sensor data can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1923689, https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1729719, and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1603775. This data package is associated with two GitHub repositories found at https://github.com/parallelworks/dynamic-learning-rivers and https://github.com/WHONDRS-Hub/ICON-ModEx_Open_Manuscript. In addition to this readme, this data package also includes two file-level metadata (FLMD) files that describes each file and two data dictionaries (DD) that describe all column/row headers and variable definitions. This data package consists of two main folders (1) dynamic-learning-rivers and (2) ICON-ModEx_Open_Manuscript which contain snapshots of the associated GitHub repositories. The input data, output data, and machine learning models used to guide sampling locations are within dynamic-learning-rivers. The folder is organized into five top-level directories: (1) “input_data” holds the training data for the ML models; (2) “ml_models” holds machine learning (ML) models trained on the data in “input_data”; (3) “examples” contains files for direct experimentation with the machine learning model, including scripts for setting up “hindcast” run; (4) “scripts” contains data preprocessing and postprocessing scripts and intermediate results specific to this data set that bookend the ML workflow; and (5) “output_data” holds the overall results of the ML model on that branch. Each trained ML model resides on its own branch in the repository; this means that inputs and outputs can be different branch-to-branch. There is also one hidden directory “.github/workflows”. This hidden directory contains information for how to run the ML workflow as an end-to-end automated GitHub Action but it is not needed for reusing the ML models archived here. Please see the top-level README.md in the GitHub repository for more details on the automation. The scripts and data used to create figures in the manuscript are within ICON-ModEx_Open_Manuscript. The folder is organized into four folders which contain the scripts, data, and pdf for each figure. Within the “fig-model-score-evolution” folder, there is a folder called “intermediate_branch_data” which contains some intermediate files pulled from dynamic-learning-rivers and reorganized to easily integrate into the workflows. NOTE: THIS FOLDER INCLUDES THE FILES AT THE POINT OF PAPER SUBMISSION. IT WILL BE UPDATED ONCE THE PAPER IS ACCEPTED WITH ANY REVISIONS AND WILL INCLUDE A DD/FLMD AT THAT POINT. We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Washington State Parks and Recreation Commission (Scientific Research Permit #210901), and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the samples labeled “SSS” were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview. WHONDRS consortium members were asked to provide any acknowledgments for the collection of samples labeled “CM” and the following is a list of acknowledgments that were submitted with their corresponding Site IDs: (MART) Research activities were conducted in part on the Wind River Experimental Forest within the Gifford Pinchot National Forest; (MP- 100379) Philadelphia is part of Lenapehoking, the ancestral homelands of the Lenape peoples; (MP-102398) Land surveyed is the ancestral homelands of the Nookhose'iinenno (Arapaho), Tsis tsis'tas (Cheyenne), and Nuuchu (Ute); (MP-100749 and MP- 100747) Georgia Coastal Ecosystem LTER, OCE-1832178; (SP-70 and SP-72) Eastern Shoshone, Shoshone-Bannock; (MP- 102944) Funded by Oregon Watershed Enhancement Board. On the traditional lands of the Confederated Tribes of the Siletz, Confederated Tribes of the Grand Rhonde, and the Clatsop-Nehalem Confederated Tribe; (MP- 100607) Holiday Creek is located on the traditional territory of the Monacan Indian Nation; (SP-45) Lafayette Blue Springs State Park; (MP-102420) NSF DEB-2016749; (MP-100019) New Hampshire Agriculture Experiment Station; (SP-35) Rayonier (land owner; https://www.rayonier.com/); (MP- 101276) US Department of Energy, Office of Science, Biological and Environmental Research, Subsurface Biogeochemical Research, Watershed Dynamics and Evolution SFA at ORNL; (MP- 103224) Watershed Dynamics and Evolution SFA at ORNL; (MP- 101584) Traditional lands of the Oceti Sakowin (Dakota, Lakota, Nakoda) and Anishinaabe Peoples.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

DOE Energy Frontier Research Centers Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio)

New capabilities to predict, design and control the chemistries of carbon could answer a global imperative to transition from fossil-based to sustainable transportation fuels. While the use of inexpensive hydrocarbons has been an unparalleled achievement and enabler of economic prosperity for many nations, singular dependence upon crude oil has given rise to systemic vulnerabilities in climate, energy, economic, and national security. Lignocellulosic biomass, a renewable and carbon-neutral resource, has the potential to displace an estimated annual equivalent of three billion barrels of oil in the U.S. alone (National Research Council 2009, U. S. Department of Energy, 2011). However, biomass has only one-third the energy density of crude oil (Agrawal and Singh 2009, Richard 2010) and lacks petroleum’s versatility as a feedstock for fuels and chemicals. These limitations keep biomass conversion below the efficiency level needed for strategic impact while the scientific challenge of routing carbon from one molecular context to another remains unmet. In 2009, the Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio) recognized the potential of chemical catalysis and fast pyrolysis to overcome such limitations by transforming the main components of biomass (cellulose, xylan, and lignin) from grasses and trees directly to liquid hydrocarbons and aromatic co-products. Enabled by the EFRC high-risk, high-reward approach to grand challenge science, C3Bio researchers have been key national players in disrupting the conventional paradigm of the cellulosic biorefinery into a new future of “no carbon left behind”—the full utilization of carbon from plant cell walls in energy-dense fuels (Fig. 1). We identified catalytic and fast-pyrolytic pathways that utilize cellulose, xylan and, most significantly, lignin. We developed catalytic processes that deoxygenate and transform monomers and isolated polymers into useful products and tested their use with intact biomass. We gained control of lignin synthesis within plants and initiated tailoring biomass to its end-use through the tools of plant molecular biology and genetic engineering. C3Bio breakthroughs have increased the energy density of biomass-derived substrates via catalytic and pyrolytic conversions into products such as benzoquinones, furfural and hydroxymethylfurfural, levoglucosan and levulinic acid, methoxypropylphenols and propylbenzene. Such advances in biomass conversion would not have been possible without simultaneous advances in analytical instrumentation and methodologies, and imaging technologies and applications. The legacy science developed by C3Bio enables design and control strategies for achieving a targeted product portfolio of fuel and chemical feedstocks from a diverse range of native and tailored biomass. Our research provides the knowledge base required for a bio-economy with product streams as diverse in functionality as those of the petrochemical industry. Coupling targeted computational modeling with experimentation, we achieved: (1) fundamental understanding of biopolymers and cell wall architecture assembly, (2) discovery of new chemistries that allow the development of highly selective pathways to fuels and desirable chemicals, and (3) an integrated systems-level understanding to control catalytic and pyrolytic pathways.

09 BIOMASS FUELS↗
DOE OSTI2024

A multiscale model of immune surveillance in micrometastases gives insights on cancer patient digital twins

Abstract Metastasis is the leading cause of death in patients with cancer, driving considerable scientific and clinical interest in immunosurveillance of micrometastases. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in general epithelial tissue. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, including uncontrolled growth, partial response, and complete immune response to tumor growth. We classified the virtual patients and identified key patient parameters with the greatest effect on the simulated immunosurveillance. We highlight the lessons derived from this analysis and their impact on the nascent field of cancer patient digital twins (CPDTs). While CPDTs could enable clinicians to systematically dissect the complexity of cancer in each individual patient and inform treatment choices, our work shows that key challenges remain before we can reach this vision. In particular, we show that there remain considerable uncertainties in immune responses, unreliable patient stratification, and unpredictable personalized treatment. Nonetheless, we also show that in spite of these challenges, patient-specific models suggest strategies to increase control of clinically undetectable micrometastases even without complete parameter certainty.

Mathematical & Computational Biology↗
DOE OSTI2020

Resource for the Development of Biomedical Accelerator Mass Spectrometry (AMS) Final Report

The NIH Research Resource for Biomedical AMS was originally funded at Lawrence Livermore National Laboratory in 1999 to develop and apply the technology of accelerator mass spectrometry (AMS) in broad- based biomedical research. The Resource’s niche is to fill needs for ultra high sensitivity quantitation when isotope-labeled agents are used. The Research Resource’s Technology Research and Development (TR&D) efforts will focus on the needs of the biomedical research community in the context of seven Driving Biomedical Projects (DBPs) that will drive the Center’s technical capabilities through three core TR&Ds. We will expand our present capabilities by developing a fully integrated HPLC AMS to increase our capabilities for metabolic measurements, we will develop methods to understand cellular processes and we will develop and validate methods for the application of AMS in human studies, which is a growing area of demand by collaborators and service users. In addition, we will continue to support new and ongoing collaborative and service projects that require the capabilities of the Resource. The Center will continue to train researchers in the use of the AMS capabilities being developed, and the results of all efforts will be widely disseminated to advance progress in biomedical research. Towards these goals, our specific aims are to:1.) Increase the value and information content of AMS measurements by combining molecular speciation with quantitation of defined macromolecular isolates. Specifically, develop and validate methods for macromolecule labeling, characterization and quantitation.2.) Develop and validate methods and strategies to enable AMS to become more broadly used in human studies. Specifically, demonstrate robust methods for conducting pharmacokinetic/pharmacodynamics studies in humans and model systems.3.) Increase the accessibility of AMS to the Biomedical research community and the throughput of AMS through direct coupling to separatory instruments.4.) Provide high throughput 14C BioAMS analysis for collaborative and service clients.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Hydrothermal Liquefaction and Upgrading of Wastewater-Grown Microalgae: 2021 State of Technology

The fiscal year (FY) 2021 State of Technology (SOT) Assessment for the hydrothermal liquefaction (HTL) of wastewater (WW)-grown microalgae and biocrude upgrading system was completed and reported here. An industrial partner, Gross-Wen Technologies (GWT), provided algae feedstock cultivated on a revolving algal biofilm (RAB) system by using the primary effluent from a water resource recovery facility (WRRF). This provided algae was tested at PNNL for HTL processing. The experimental results provided the major design basis of the HTL process of the SOT baseline case. The primary effluent of the Metropolitan Water Reclamation District (MWRD) of Greater Chicago was assumed to be the nutrients source for algae growth and the algae yield data per gallon wastewater provided by GWT were used to estimate the total algae production rate and thus the HTL conversion plant scale. Considering different cultivation technologies and wastewater streams with different flow rates and nutrients contents can be used to produce algae, this SOT assessment just provided an example case study for WW-grown algae based HTL conversion to fuels systems. A preliminary economic analysis was developed based on process simulation results. Sensitivity analysis was implemented to evaluate cost impacts of plant scales, potential cost improvements and other key factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Role of SaPCR2 in Zn Uptake in the Root Elongation Zone of the Zn/Cd Hyperaccumulator Sedum alfredii

Zn pollution is a potential toxicant for agriculture and the environment. Sedum alfredii is a Zn/Cd hyperaccumulator found in China and has been proven as a useful resource for the phytoremediation of Zn-contaminated sites. However, the molecular mechanism of Zn uptake in S. alfredii is limited. In this study, the function of SaPCR2 on Zn uptake in S. alfredii was identified by gene expression analysis, yeast function assays, Zn accumulation and root morphology analysis in transgenic lines to further elucidate the mechanisms of uptake and translocation of Zn in S. alfredii. The results showed that SaPCR2 was highly expressed in the root elongation zone of the hyperaccumulating ecotype (HE) S. alfredii, and high Zn exposure downregulated the expression of SaPCR2 in the HE S. alfredii root. The heterologous expression of SaPCR2 in yeast suggested that SaPCR2 was responsible for Zn influx. The overexpression of SaPCR2 in the non-hyperaccumulating ecotype (NHE) S. alfredii significantly increased the root uptake of Zn, but did not influence Mn, Cu or Fe. SR-μ-XRF technology showed that more Zn was distributed in the vascular buddle tissues, as well as in the cortex and epidermis in the transgenic lines. Root morphology was also altered after SaPCR2 overexpression, and a severe inhibition was observed. In the transgenic lines, the meristematic and elongation zones of the root were lower compared to the WT, and Zn accumulation in meristem cells was also reduced. These results indicate that SaPCR2 is responsible for Zn uptake, and mainly functions in the root elongation zone. This research on SaPCR2 could provide a theoretical basis for the use of genetic engineering technology in the modification of crops for their safe production and biological enhancement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Evidence for a genetic basis in functional trait tradeoffs with microbial growth rate but not growth yield

Tradeoffs in microbial functional traits have been a focus of recently described ecological frameworks and of mathematical models of microbial community functioning. Tradeoffs in key traits such as growth rate, growth yield, resource acquisition, and stress tolerance may have either a genetic basis or a physiological basis, and the type of tradeoff can inform how traits are modeled and measured. Here we provide evidence that growth rate/decomposition and growth rate/stress tolerance tradeoffs have a primarily genetic basis in a phylogenetically diverse suite of ten leaf litter-inhabiting fungi. In contrast, growth yield tradeoffs with functional traits are more likely to have a physiological basis. Consideration of the type of tradeoff, genetic or physiological, should help to inform efforts to model microbial contributions to ecosystem processes, especially when considering different scales. Consideration of physiological tradeoffs may be important for understanding short-term variability (e.g., pulse events) and fine spatial scales, whereas genetic tradeoffs are likely to be useful for understanding regional- to continental-scale and medium- to long-term contributions of microbes to ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multiomics and deep learning dissect regulatory syntax in human development

Transcription factors establish cell identity during development by binding regulatory DNA in a sequence-specific manner, often promoting local chromatin accessibility and regulating gene expression1. Mapping accessible chromatin offers critical insights into transcriptional control, but available datasets for human development are restricted to bulk tissue, single organs or single modalities2. Here we present the Human Development Multiomic Atlas, a single-cell atlas of chromatin accessibility and gene expression from 817,740 fetal cells across 12 organs, spanning 203 cell types and more than 1 million candidate cis-regulatory elements, many of which exhibit organ-specific in vivo enhancer activity. Deep learning models trained to predict accessibility from local DNA sequence unravel a comprehensive lexicon of motifs that influence accessibility, including composite motifs exhibiting distinct syntactic constraints that are predicted to mediate transcription factor cooperativity. We identify ‘hard’ syntactic rules requiring precise motif spacing and orientation, ‘soft’ rules allowing flexible motif arrangements, and ubiquitous motifs inhibiting accessibility. Model-based interpretation of genetic variants reveals that disruption of motifs with positive and negative effects is associated with concordant effects on gene expression. Our work delineates how motif syntax governs cell-type-specific chromatin accessibility and provides a foundational resource for decoding cis-regulatory logic and interpreting genetic variation during human development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

VA EDH Data Curation Documentation (FY22-Q3, Rev.2)

The health and well-being of the Nation’s men and women who have served in uniform is the highest priority for the U.S. Department of Veterans Affairs (VA). VA is committed to providing timely access to high-quality, recovery-oriented, evidence-based mental health care that anticipates and responds to Veterans’ needs and supports the reintegration of returning Service members into their communities. VA is working to eliminate suicide among all Veterans by developing and implementing innovative suicide prevention approaches and resources. Health outcomes, such as suicide are typically modeled as a function of genetics and environment, where environment refers to factors beyond medical, e.g., air quality, access to transportation and food, homelessness status, etc. Mental health outcomes for each individual are considered to be associated with multiple stressors that fall under a variety of categories socioeconomic, economic, physical environment. Understanding the relationships between these stressors, covariates and health outcomes, requires curated, standardized data that can be input into the VA’s Recovery Engagement and Coordination for Health - Veterans Enhanced Treatment (REACH VET) or other health outcomes model. Environmental Determinants of Health (EDH) as defined by the World Health Organization (WHO) is clean air, stable climate, adequate water, sanitation and hygiene, safe use of chemicals, protection from radiation, healthy and safe workplaces, sound agricultural practices, health-supportive cities and built environments, and a preserved nature are all prerequisites for good health.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Design and testing of ultrasound probe adapters for a robotic imaging platform

Medical imaging-based triage is a critical tool for emergency medicine in both civilian and military settings. Ultrasound imaging can be used to rapidly identify free fluid in abdominal and thoracic cavities which could necessitate immediate surgical intervention. However, proper ultrasound image capture requires a skilled ultrasonography technician who is likely unavailable at the point of injury where resources are limited. Instead, robotics and computer vision technology can simplify image acquisition. As a first step towards this larger goal, here, we focus on the development of prototypes for ultrasound probe securement using a robotics platform. The ability of four probe adapter technologies to precisely capture images at anatomical locations, repeatedly, and with different ultrasound transducer types were evaluated across more than five scoring criteria. Testing demonstrated two of the adapters outperformed the traditional robot gripper and manual image capture, with a compact, rotating design compatible with wireless imaging technology being most suitable for use at the point of injury. Next steps will integrate the robotic platform with computer vision and deep learning image interpretation models to automate image capture and diagnosis. This will lower the skill threshold needed for medical imaging-based triage, enabling this procedure to be available at or near the point of injury.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

SCOPe: improvements to the structural classification of proteins – extended database to facilitate variant interpretation and machine learning

Abstract The Structural Classification of Proteins—extended (SCOPe, https://scop.berkeley.edu) knowledgebase aims to provide an accurate, detailed, and comprehensive description of the structural and evolutionary relationships amongst the majority of proteins of known structure, along with resources for analyzing the protein structures and their sequences. Structures from the PDB are divided into domains and classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.08, we have developed search and display tools for analysis of genetic variants we mapped to structures classified in SCOPe. In order to improve the utility of SCOPe to automated methods such as deep learning classifiers that rely on multiple alignment of sequences of homologous proteins, we have introduced new machine-parseable annotations that indicate aberrant structures as well as domains that are distinguished by a smaller repeat unit. We also classified structures from 74 of the largest Pfam families not previously classified in SCOPe, and we improved our algorithm to remove N- and C-terminal cloning, expression and purification sequences from SCOPe domains. SCOPe 2.08-stable classifies 106 976 PDB entries (about 60% of PDB entries).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Development of a Modular Tissue Phantom for Evaluating Vascular Access Devices

Central vascular access (CVA) may be critical for trauma care and stabilizing the casualty. However, it requires skilled personnel, often unavailable during remote medical situations and combat casualty care scenarios. Automated CVA medical devices have the potential to make life-saving therapeutics available in these resource-limited scenarios, but they must be properly designed. Unfortunately, currently available tissue phantoms are inadequate for this use, resulting in delayed product development. Here, we present a tissue phantom that is modular in design, allowing for adjustable flow rate, circulating fluid pressure, vessel diameter, and vessel positions. The phantom consists of a gelatin cast using a 3D-printed mold with inserts representing vessels and bone locations. These removable inserts allow for tubing insertion which can mimic normal and hypovolemic flow, as well as pressure and vessel diameters. Trauma to the vessel wall is assessed using quantification of leak rates from the tubing after removal from the model. Lastly, the phantom can be adjusted to swine or human anatomy, including modeling the entire neurovascular bundle. Overall, this model can better recreate severe hypovolemic trauma cases and subject variability than commercial CVA trainers and may potentially accelerate automated CVA device development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Screening and Validation of Molecular Targeted Radiosensitizers

The development of molecular targeted drugs with radiation and chemotherapy is critically important for improving the outcomes of patients with hard-to-treat, potentially curable cancers. However, too many preclinical studies have not translated into successful radiation oncology trials. Major contributing factors to this insufficiency include poor reproducibility of preclinical data, inadequate preclinical modeling of intertumoral genomic heterogeneity that influences treatment sensitivity in the clinic, and a reliance on tumor growth delay instead of local control (TCD50) endpoints. There exists an urgent need to overcome these barriers to facilitate successful clinical translation of targeted radiosensitizers. To this end, we have used 3-dimensional (3D) cell culture assays to better model tumor behavior in vivo. Examples of successful prediction of in vivo effects with these 3D assays include radiosensitization of head and neck cancers by inhibiting epidermal growth factor receptor or focal adhesion kinase signaling, and radioresistance associated with oncogenic mutation of KRAS. To address the issue of tumor heterogeneity, we leveraged institutional resources that allow high-throughput 3D screening of radiation combinations with small-molecule inhibitors across genomically characterized cell lines from lung, head and neck, and pancreatic cancers. This high-throughput screen is expected to uncover genomic biomarkers that will inform the successful clinical translation of targeted agents from the National Cancer Institute Cancer Therapy Evaluation Program portfolio and other sources. Screening “hits” need to be subjected to refinement studies that include clonogenic assays, addition of disease-specific chemotherapeutics, target/biomarker validation, and integration of patient-derived tumor models. The chemoradiosensitizing activities of the most promising drugs should be confirmed in TCD50 assays in xenograft models with or without relevant biomarker and using clinically relevant radiation fractionation. We predict that appropriately validated and biomarker-directed targeted therapies will have a higher likelihood than past efforts of being successfully incorporated into the standard management of hard-to-treat tumors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

The gut microbiome mediates adaptation to scarce food in Coleoptera

Beetles are ubiquitous cave invertebrates worldwide that adapted to scarce subterranean resources when they colonized caves. Here, we investigated the potential role of gut microbiota in the adaptation of beetles to caves from different climatic regions of the Carpathians. The beetles’ microbiota was host-specific, reflecting phylogenetic and nutritional adaptation. The microbial community structure further resolved conspecific beetles by caves suggesting microbiota-host coevolution and influences by local environmental factors. The detritivore species hosted a variety of bacteria known to decompose and ferment organic matter, suggesting turnover and host cooperative digestion of the sedimentary microbiota and allochthonous-derived nutrients. The cave Carabidae, with strong mandibula, adapted to predation and scavenging of animal and plant remains, had distinct microbiota dominated by symbiotic lineages Spiroplasma or Wolbachia. All beetles had relatively high levels of fermentative Carnobacterium and Vagococcus involved in lipid accumulation and a reduction of metabolic activity, and both features characterize adaptation to caves.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Antibiotic resistance and host immune system-induced metal bactericidal control are key factors for microbial persistence in the developing human preterm infant gut microbiome

The human gut microbiome, which develops and stabilizes during the early stages of infant life, plays an essential role in host health through the production of metabolic resources and the stimulation and training of the immune system. To study colonization and community functional dynamics of the microbiota based on responses to host immune processes during the normal and dysbiotic establishment of the gut, metaproteomics was conducted on 91 fecal samples collected over the first 90 days of life from 17 hospitalized premature infants. Microbial responses to antibiotic administration and host-imposed metal bactericidal control correlated with community assembly and resiliency of microbes in the developing preterm gut. Specifically, proteins related to antibiotic resistance and metal homeostasis mechanisms were predominant in persisting members in the infant gut environment over the first several weeks of life. Overall, this metaproteomics study provides a unique approach to examine the temporal expansion and resilience of microbial colonization, as it allows simultaneous examination of both host and microbial metabolic activities. Understanding the interplay between host and microbes may elucidate the microbiome’s potential immunomodulatory roles relevant to necrotizing enterocolitis and other dysbiotic conditions in preterm infants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Symbiotic niche mapping reveals functional specialization by two ectomycorrhizal fungi that expands the host plant niche

Mutualisms are ubiquitous in natural systems, but less is known about how these positive interactions influence species distributions compared with antagonistic interactions, such as competition and predation. The niche concept is one useful approach for thinking about factors that shape species ranges, which we apply here towards understanding how the nature of plant-mycorrhizal symbioses change across large environmental gradients. We used a continuous niche mapping approach to examine how two ectomycorrhizal fungi (Thelephora terrestris, Suillus pungens) impact pine seedling growth across a two-dimensional soil nitrogen (N) and phosphorus (P) gradient. We found that ectomycorrhizal fungi improved plant growth most in nutrient addition treatments with highly imbalanced N:P ratios, demonstrating that mycorrhizal benefits depend on interactions between niche axes. Nevertheless, T. terrestris (highN:lowP) and S. pungens (lowN:highP) benefited plants most at opposite ends of the resource ratio spectrum, consistent with niche partitioning and functional specialization. While ectomycorrhizal fungi are often thought of as being most beneficial for nitrogen uptake, our results suggest that members of the Thelephoraceae may specialize in improving plant P uptake. Ectomycorrhizal colonization by a single fungus increased plant niche volume (calculated as convex hull volumes of plant growth response surfaces across N and P gradients) compared to non-mycorrhizal control plants and shows the overall positive effects of mutualisms on plant niche volume. Despite plant host benefits in S. pungens and T. terrestris single species treatments, the presence of both fungi together decreased plant niche volume. The lack of functional complementarity, despite functional specialization, indicates that in some environments, either fungal competition or the cost of maintaining a suboptimal mycorrhizal partner can limit the benefits of a higher quality partner. The niche mapping approach we present has the potential to answer fundamental questions about the dimensions of functional diversity in ectomycorrhizal fungi and the distributions of mycorrhizal symbioses.

59 BASIC BIOLOGICAL SCIENCES↗