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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Probing substrate water access through the O1 channel of Photosystem II by single site mutations and membrane inlet mass spectrometry

Abstract Light-driven water oxidation by photosystem II sustains life on Earth by providing the electrons and protons for the reduction of CO 2 to carbohydrates and the molecular oxygen we breathe. The inorganic core of the oxygen evolving complex is made of the earth-abundant elements manganese, calcium and oxygen (Mn 4 CaO 5 cluster), and is situated in a binding pocket that is connected to the aqueous surrounding via water-filled channels that allow water intake and proton egress. Recent serial crystallography and infrared spectroscopy studies performed with PSII isolated fromThermosynechococcus vestitus(T. vestitus) support that one of these channels, the O1 channel, facilitates water access to the Mn 4 CaO 5 cluster during its S 2 →S 3 and S 3 →S 4 →S 0 state transitions, while a subsequent CryoEM study concluded that this channel is blocked in the cyanobacteriumSynechocystis sp.PCC 6803, questioning the role of the O1 channel in water delivery. Employing site-directed mutagenesis we modified the two O1 channel bottleneck residues D1-E329 and CP43-V410 (T. vestitusnumbering) and probed water access and substrate exchange via time resolved membrane inlet mass spectrometry. Our data demonstrates that water reaches the Mn 4 CaO 5 cluster via the O1 channel in both wildtype and mutant PSII. In addition, the detailed analysis provides functional insight into the intricate protein-water-cofactor network near the Mn 4 CaO 5 cluster that includes the pentameric, near planar ‘water wheel’ of the O1 channel.

Plant Sciences↗
DOE OSTI2023

Neutralization profiles of HIV-1 viruses from the VRC01 Antibody Mediated Prevention (AMP) trials

The VRC01 Antibody Mediated Prevention (AMP) efficacy trials conducted between 2016 and 2020 showed for the first time that passively administered broadly neutralizing antibodies (bnAbs) could prevent HIV-1 acquisition against bnAb-sensitive viruses. HIV-1 viruses isolated from AMP participants who acquired infection during the study in the sub-Saharan African (HVTN 703/HPTN 081) and the Americas/European (HVTN 704/HPTN 085) trials represent a panel of currently circulating strains of HIV-1 and offer a unique opportunity to investigate the sensitivity of the virus to broadly neutralizing antibodies (bnAbs) being considered for clinical development. Pseudoviruses were constructed using envelope sequences from 218 individuals. The majority of viruses identified were clade B and C; with clades A, D, F and G and recombinants AC and BF detected at lower frequencies. We tested eight bnAbs in clinical development (VRC01, VRC07-523LS, 3BNC117, CAP256.25, PGDM1400, PGT121, 10–1074 and 10E8v4) for neutralization against all AMP placebo viruses (n = 76). Compared to older clade C viruses (1998–2010), the HVTN703/HPTN081 clade C viruses showed increased resistance to VRC07-523LS and CAP256.25. At a concentration of 1μg/ml (IC80), predictive modeling identified the triple combination of V3/V2-glycan/CD4bs-targeting bnAbs (10-1074/PGDM1400/VRC07-523LS) as the best against clade C viruses and a combination of MPER/V3/CD4bs-targeting bnAbs (10E8v4/10-1074/VRC07-523LS) as the best against clade B viruses, due to low coverage of V2-glycan directed bnAbs against clade B viruses. Overall, the AMP placebo viruses represent a valuable resource for defining the sensitivity of contemporaneous circulating viral strains to bnAbs and highlight the need to update reference panels regularly. Our data also suggests that combining bnAbs in passive immunization trials would improve coverage of global viruses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Case studies in bias reduction and inference for electronic health record data with selection bias and phenotype misclassification

Electronic health records (EHR) are not designed for population‐based research, but they provide easy and quick access to longitudinal health information for a large number of individuals. Many statistical methods have been proposed to account for selection bias, missing data, phenotyping errors, or other problems that arise in EHR data analysis. However, addressing multiple sources of bias simultaneously is challenging. We developed a methodological framework (R package, SAMBA ) for jointly handling both selection bias and phenotype misclassification in the EHR setting that leverages external data sources. These methods assume factors related to selection and misclassification are fully observed, but these factors may be poorly understood and partially observed in practice. As a follow‐up to the methodological work, we demonstrate how to apply these methods for two real‐world case studies, and we evaluate their performance. In both examples, we use individual patient‐level data collected through the University of Michigan Health System and various external population‐based data sources. In case study (a), we explore the impact of these methods on estimated associations between gender and cancer diagnosis. In case study (b), we compare corrected associations between previously identified genetic loci and age‐related macular degeneration with gold standard external summary estimates. These case studies illustrate how to utilize diverse auxiliary information to achieve less biased inference in EHR‐based research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children With Medical Complexity Presenting With Severe Sepsis

Objectives: Of the Social Determinants of Health (SDoH), we evaluated socioeconomic and neighborhood-related factors which may affect children with medical complexity (CMC) admitted to a Pediatric Intensive Care Unit (PICU) in Shelby County, Tennessee with severe sepsis and their association with PICU length of stay (LOS). We hypothesized that census tract-level socioeconomic and neighborhood factors were associated with prolonged PICU LOS in CMC admitted with severe sepsis in the underserved community. Methods: This single-center retrospective observational study included CMC living in Shelby County, Tennessee admitted to the ICU with severe sepsis over an 18-month period. Severe sepsis CMC patients were identified using an existing algorithm incorporated into the electronic medical record at a freestanding children's hospital. SDoH information was collected and analyzed using patient records and publicly available census-tract level data, with ICU length of stay as the primary outcome. Results: 83 encounters representing 73 patients were included in the analysis. The median PICU LOS was 9.04 days (IQR 3.99–20.35). The population was 53% male with a median age of 4.1 years (IQR 1.96–12.02). There were 57 Black/African American patients (68.7%) and 85.5% had public insurance. Based on census tract-level data, about half (49.4%) of the CMC severe sepsis population lived in census tracts classified as suffering from high social vulnerability. There were no statistically significant relationships between any socioeconomic and neighborhood level factors and PICU LOS. Conclusion: Pediatric CMC severe sepsis patients admitted to the PICU do not have prolonged lengths of ICU stay related to socioeconomic and neighborhood-level SDoH at our center. A larger sample with the use of individual-level screening would need to be evaluated for associations between social determinants of health and PICU outcomes of these patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Lipid droplet-associated proteins in alcohol-associated fatty liver disease: A proteomic approach

The earliest manifestation of alcohol-associated liver disease (ALD) is steatosis characterized by deposition of fat in specialized organelles called lipid droplets (LDs). While alcohol administration causes a rise in LD numbers in the hepatocytes, little is known regarding their characteristics that allow their accumulation and size to increase. The aim of the present study is to gain insights into underlying pathophysiological mechanisms by investigating the ethanol-induced changes in hepatic LD proteome as a function of LD size. Adult male Wistar rats (180–200 g BW) were fed with ethanol liquid diet for 6 weeks. At sacrifice, large-, medium-, and small-sized hepatic LD subpopulations (LD1, LD2, and LD3, respectively) were isolated and subjected to morphological and proteomic analyses. Morphological analysis of LD1-LD3 fractions of ethanol-fed rats clearly demonstrated that LD1 contained larger LDs compared with LD2 and LD3 fractions. Our preliminary results from principal component analysis showed that the proteome of different-sized hepatic LD fractions was distinctly different. Proteomic data analysis identified over 2000 proteins in each LD fraction with significant alterations in protein abundance among the three LD fractions. Among the altered proteins, several were related to fat metabolism, including synthesis, incorporation of fatty acid, and lipolysis. Ingenuity pathway analysis revealed increased fatty acid synthesis, fatty acid incorporation, LD fusion, and reduced lipolysis in LD1 compared to LD3. Overall, the proteomic findings indicate that the increased level of protein that facilitates fusion of LDs combined with an increased association of negative regulators of lipolysis dictates the generation of large-sized LDs during the development of alcohol-associated hepatic steatosis. Several significantly altered proteins were identified in different-sized LDs isolated from livers of ethanol-fed rats. Ethanol-induced increases in specific proteins that hinder LD lipid metabolism led to the accumulation and persistence of large-sized LDs in the liver.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Rhizosphere Microbiome Diversity Potentially Supports Robust Nature of Field Pennycress ( Thlaspi arvense L.) in Dryland Cropping Systems of Eastern Washington

ABSTRACT Field pennycress ( Thlaspi arvense L.) is an annual in the Brassicaceae family and is currently being developed as an oilseed intermediate crop suitable for renewable biodiesel and jet fuel. It displays many desirable characteristics for this role including cold tolerance, a rapid life cycle, and a seed fatty acid profile conducive to bioenergy generation. These traits make field pennycress favorable for winter oilseed cultivation in the inland Pacific Northwest (iPNW). Simultaneously, intermediate crops are an increasingly recognized component of both agronomic sustainability and soil health management. Intermediate crops enhance soil microbial diversity, which benefits both soil and plant health. To understand the impact of field pennycress on soil microbial diversity, two natural accessions and seven experimental accessions were grown at three sites in Eastern Washington. Aboveground biomass and rhizosphere soil were then collected. Soil genomic DNA was extracted from rhizosphere samples and used to generate an amplicon library for bacterial (16S) and fungal (ITS) rRNA sequences. The resulting libraries were analyzed in QIIME2, which revealed that not only did the fad2 deficient line from the Spring32‐10 background have significantly increased aboveground biomass production compared to other pennycress genotypes, but also displayed significantly higher β‐diversity in the rhizosphere community specifically at the site experiencing the driest conditions. ANCOM analysis showed that multiple sequences similar to beneficial plant and soil health enhancing organisms such as Trichoderma spirale , Pseudomonas spp., and Methylobacterium goesingense were found to be enriched in the microbiome of the fad2 Spring32‐10 background also at that site. To add additional context to rhizosphere community data, root exudates from two pennycress genotypes were captured in magenta boxes and analyzed using HPLC. Future work will expand our understanding of the mechanisms by which field pennycress creates diversity in the rhizosphere, thus expanding our ability to cultivate this crop in the iPNW.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Benchmarking blockchain-based gene-drug interaction data sharing methods: A case study from the iDASH 2019 secure genome analysis competition blockchain track

Blockchain distributed ledger technology is just starting to be adopted in genomics and healthcare applications. Despite its increased prevalence in biomedical research applications, skepticism regarding the practicality of blockchain technology for real-world problems is still strong and there are few implementations beyond proof-of-concept. We focus on benchmarking blockchain strategies applied to distributed methods for sharing records of gene-drug interactions. We expect this type of sharing will expedite personalized medicine. We generated gene-drug interaction test datasets using the Clinical Pharmacogenetics Implementation Consortium (CPIC) resource. We developed three blockchain-based methods to share patient records on gene-drug interactions: Query Index, Index Everything, and Dual-Scenario Indexing. We achieved a runtime of about 60 s for importing 4,000 gene-drug interaction records from four sites, and about 0.5 s for a data retrieval query. Our results demonstrated that it is feasible to leverage blockchain as a new platform to share data among institutions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Learning to Count Grave Sites for Cemetery Observation Models With Satellite Imagery

Understanding how people occupy open spaces is important for research in support of population modeling, policy, national security, emergency response, and sustainability. For the past decade, there has been an increase in research toward capturing and reporting population dynamics and patterns of life at the building level and in some open public spaces such as cemeteries and parks. This is done through observation models developed from local sociocultural information acquired at various spatiotemporal scales to inform night, day, and episodic population occupancy estimates (people/1000 sq ft). Sociocultural information for cemeteries and parks is scarcely available and often collected manually. The process is not only marred by inconsistencies but is laborious and time consuming. In this study, we leverage convolutional neural networks (CNNs) and satellite imagery to derive grave site counts as proxy variables to support scalable and accurate sociocultural data required in a population observation model. Through a hybrid workflow (weak localization plus regression model), we characterize a large scale automation process to counting of grave sites. We evaluate and demonstrate the efficacy of proposed workflow using out-of-data set large satellite imagery and establish its broader impact on cemetery observation models.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Advances in statistical methods for cancer surveillance research: an age-period-cohort perspective

Background: Analysis of Lexis diagrams (population-based cancer incidence and mortality rates indexed by age group and calendar period) requires specialized statistical methods. However, existing methods have limitations that can now be overcome using new approaches. Methods: We assembled a “toolbox” of novel methods to identify trends and patterns by age group, calendar period, and birth cohort. We evaluated operating characteristics across 152 cancer incidence Lexis diagrams compiled from United States (US) Surveillance, Epidemiology and End Results Program data for 21 leading cancers in men and women in four race and ethnicity groups (the “cancer incidence panel”). Results: Nonparametric singular values adaptive kernel filtration (SIFT) decreased the estimated root mean squared error by 90% across the cancer incidence panel. A novel method for semi-parametric age-period-cohort analysis (SAGE) provided optimally smoothed estimates of age-period-cohort (APC) estimable functions and stabilized estimates of lack-of-fit (LOF). SAGE identified statistically significant birth cohort effects across the entire cancer panel; LOF had little impact. As illustrated for colon cancer, newly developed methods for comparative age-period-cohort analysis can elucidate cancer heterogeneity that would otherwise be difficult or impossible to discern using standard methods. Conclusions: Cancer surveillance researchers can now identify fine-scale temporal signals with unprecedented accuracy and elucidate cancer heterogeneity with unprecedented specificity. Birth cohort effects are ubiquitous modulators of cancer incidence in the US. The novel methods described here can advance cancer surveillance research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A Dynamic Trajectory Fit to Multisensor Fireball Observations

Meteorites with known orbital origins are key to our understanding of solar system formation and the source of life on Earth. Fireball networks have been developed globally in a unified effort to record and ultimately retrieve these cosmic samples. However, the accuracy of the determined orbit and the likelihood of meteorite recovery depend directly on the accuracy of the chosen meteoroid triangulation method. There are three leading techniques for meteoroid triangulation discussed in the literature: the method of planes, the straight-line least-squares method, and the multiparameter fit method. Here we describe an alternative method to meteoroid triangulation, called the dynamic trajectory fit. This approach uses the meteoroid’s 3D dynamic equations of motion to fit a realistic trajectory directly to multisensor line-of-sight observations. This method has the ability to resolve fragmentation events, fit systematic observatory timing offsets, and determine mass estimates of the meteoroid along its observable trajectory. Through a comprehensive Monte Carlo analysis of over 100,000 trajectory simulations, we find this new method to more accurately estimate meteoroid trajectories of slow entry events (<25 km s{sup −1}) and events observed from low convergence angles (<10°) compared to existing meteoroid triangulation techniques. Additionally, we triangulate an observed fireball event with visible fragmentation using the various triangulation methods to show that the proposed dynamic trajectory fit implementing fragmentation to best match the captured multisensor line-of-sight data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

FaceBase 3: analytical tools and FAIR resources for craniofacial and dental research

ABSTRACT The FaceBase Consortium was established by the National Institute of Dental and Craniofacial Research in 2009 as a ‘big data’ resource for the craniofacial research community. Over the past decade, researchers have deposited hundreds of annotated and curated datasets on both normal and disordered craniofacial development in FaceBase, all freely available to the research community on the FaceBase Hub website. The Hub has developed numerous visualization and analysis tools designed to promote integration of multidisciplinary data while remaining dedicated to the FAIR principles of data management (findability, accessibility, interoperability and reusability) and providing a faceted search infrastructure for locating desired data efficiently. Summaries of the datasets generated by the FaceBase projects from 2014 to 2019 are provided here. FaceBase 3 now welcomes contributions of data on craniofacial and dental development in humans, model organisms and cell lines. Collectively, the FaceBase Consortium, along with other NIH-supported data resources, provide a continuously growing, dynamic and current resource for the scientific community while improving data reproducibility and fulfilling data sharing requirements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Out-of-Pile Testing and Instrumentation Transient Water Irradiation System

Current initiatives to increase the burnup of conventional nuclear fuels past the approximate 62 GWd/t limit have been spurred on by direct savings to refueling and waste storage. The technical justification for a new license limit requires extensive qualification through experimental testing. Unlike beginning-of-life fuels, high-burnup fuels are more susceptible to fuel fragmentation, relocation, and dispersal (FFRD), therefore more data is needed to characterize fuels under key accident scenarios. The Transient Reactor Test Facility (TREAT) located at the Idaho National Laboratory has developed a testing apparatus architecture to test fuels and claddings at prototypic conditions. The Transient Water Irradiation System (TWIST) is the latest iteration of a testing device capable of conducting loss of coolant accidents (LOCAs) in TREAT. The Out-of-Pile Testing and Instrumentation TWIST (OPTI-TWIST) is an electrically heated device that is analogous to TWIST. OPTI-TWIST allows for detailed instrumentation and thermal-hydraulic characterization. TWIST ultimately aims to conduct the most advanced in-situ diagnostics to evaluate FFRD in a prototypic LOCA. Moreover, it will explore the phenomenological bifurcation of a decay-energy heat up driven LOCA and a stored-energy heat up driven LOCA. The instrumentation suite includes conventional thermocouples and pressure transducers in addition to an electro impedance sensor, an acoustic emission sensor, an optical pressure sensor, and an optical pyrometer. Characterizing these instruments in OPTI-TWIST eliminates complications of irradiation effects while preserving extreme thermal-hydraulic conditions. Finally, benchmarking both devices to a thermal-hydraulic code like the Reactor Excursion and Leak Analysis Program (RELAP)5-3D provides a unique opportunity for iteration. Pre-test predictions and post-test interpretations inform the physical designs, operational procedures, test conditions, and instrumentation types and positions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Clinical pharmacology information in regulatory submissions and labeling: A comparative analysis of orphan and non-orphan drugs approved by the FDA

Clinical pharmacology is an integral discipline supporting the development, regulatory evaluation, and clinical use of drugs for the treatment of both common and rare diseases. Here, we evaluated the recommendations and information available from select clinical pharmacology studies in the therapeutic product labeling of new molecular entities (NMEs) approved from 2017 to 2019 for both common and rare diseases. A total of 151 NMEs, including 72 orphan and 79 non-orphan drugs, were analyzed for recommendations and information available related to food–drug interaction, drug–drug interaction, renal impairment, hepatic impairment, QT assessment, and human radiolabeled mass balance studies using data collected from the original labeling and other regulatory documents. The analysis showed no statistically significant difference in the recommendations between orphan and non-orphan drugs except for renal impairment related recommendations in section 8 of the labeling. Although not significant, fewer hepatic impairment labeling recommendations were available for orphan drugs when compared with non-orphan drugs. At the time of initial approval, 79 postmarketing requirements (PMRs) and postmarketing commitments (PMCs) for 33 orphan drugs and 39 PMRs and PMCs for 19 non-orphan drugs were established; with most difference observed for drug–drug interaction, hepatic impairment, and QT assessment. Overall, although there was a trend for more labeling recommendations and fewer postmarketing studies and clinical trials for non-orphan drugs, there appeared to be no substantial differences in how these select clinical pharmacology studies are leveraged during the development and approval of orphan and non-orphan drugs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A dehydrated, aseptically-processed human amnion/chorion allograft accelerates healing in a delayed murine excisional wound model

Since chronic, non-healing wounds represent an increasing source of economic and temporal burden for patients who suffer from them and healthcare professionals that treat them, therapeutic modalities that promote closure of delayed and non-healing wounds are of utmost importance. Recent clinical results of allografts derived from amnion and chorion placental layers encourage further investigation of the mechanisms underlying clinical efficacy of these products for treatment of wounds. Here, we utilized a diabetic murine splinted excisional wound model to investigate the effects of a dehydrated human amnion/chorion-derived allograft (dHACA) on delayed wound healing, as well as the effects of dehydrated allograft derived solely from amnion tissue of the same donor. We examined wound healing by histological endpoint analysis, and we assessed other parameters relevant to functional wound healing in the wound bed including angiogenesis, macrophage phenotypes, proliferative activity, and gene expression. Herein we demonstrate that application of dHACA to a murine diabetic model of delayed wound progression results in better macroscale wound resolution outcomes, including rate of closure, compared to unaided wound progression, while dehydrated human amnion allograft (dHAA) fails to improve outcomes. Improved gross wound resolution observed with dHACA was accompanied by increased granulation tissue formation, proliferation and vascular ingrowth observed in the wound bed, early macrophage polarization towards anti-inflammatory phenotypes, and downregulation of pro-fibrotic gene expression. Overall, our data suggest that improvements in the rates of delayed wound closure observed from combined amnion/chorion allografts are associated with modulation of critical cellular and tissue processes commonly found to be dysregulated in delayed healing wounds, including proliferation, vascularization, inflammation, and re-epithelialization.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Role of karyopherin nuclear transport receptors in nuclear transport by nuclear trafficking peptide

Nuclear trafficking peptide (NTP), a cell-penetrating peptide (CPP) composed of 10 amino acids (aa) (RIFIHFRIGC), has potent nuclear trafficking activity. Recently, we established a protein-based cell engineering system by using NTP, but it remained elusive how NTP functions as a CPP with nuclear orientation. In the present study, we identified importin subunit β1 (IMB1) and transportin 1 (TNPO1) as cellular proteins underlying the activity of NTP. These karyopherin nuclear transport receptors were identified as candidate molecules by liquid chromatography/mass spectrometry analysis, and downregulation of each protein by small interfering RNA significantly reduced NTP activity (P < 0.01). Biochemical analyses revealed that NTP bound directly to both molecules, and the forced expression of an IMB1 fragment (296–516 aa) or TNPO1 fragment (1–297 aa), which both contain binding sites to NTP, reduced nuclear NTP-green fluorescent protein (GFP) levels when it was added to cell culture medium. NTP is derived from viral protein R (Vpr) of human immunodeficiency virus-1, and Vpr enters the nucleus and exerts pleiotropic functions. Notably, Vpr bound directly to IMB1 and TNPO1, and its function was significantly impaired by the forced expression of the 296–516-aa fragment of IMB1 and 1–297-aa fragment of TNPO1. Interestingly, NTP completely blocked the physical association of Vpr with IMB1 and TNPO1. Although the nuclear localization mechanism of Vpr remains unknown, our data suggest that NTP functions as a novel nuclear localization signal of Vpr.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Investigation of Coincidence Counting for Improving Minimal Detectable Activity of 110m Ag in Single Particle Gamma Analysis

Post-irradiation examination (PIE) of fuel particles from the fourth Advanced Gas Reactor Fuel Development and Qualification (AGR) Program irradiation (AGR-5/6/7) is being performed at Oak Ridge National Laboratory (ORNL). Tristructural isotropic (TRISO)-coated particles and associated compacts for the AGR-5/6/7 experiment fabricated by BWX Technologies Nuclear Operations Group were formed into a graphite matrix compact and irradiated at the Advanced Test Reactor at Idaho National Laboratory. At ORNL, particles are deconsolidated from the graphite matrix compact and individually scanned for emitted gamma rays with the Irradiated Microsphere Gamma Analyzer (IMGA). The IMGA system comprises a single high purity germanium (HPGe) detector, an automated particle handling vacuum system, and an ORTEC DSPEC-50 digital spectrometer for gamma ray analysis. IMGA quantifies gamma ray-emitting fission product inventories of individual TRISO particles, and these inventories can be compared with the measured average inventories per particle and radionuclide inventories predicted by AGR-5/6/7 physics calculations to determine if a particle experienced radionuclide release. Details on IMGA data collection methods can be found in the literature. The TRISO particle’s SiC layer provides structural support, as well as a barrier for fission product release during irradiation or subsequent safety testing. A weakened or compromised SiC layer can be identified by the release of radionuclides, such as 137 Cs, which is detected by IMGA. However, select radionuclides, such as 90 Sr, 110 mAg, and 154 Eu have been shown to migrate through an intact SiC layer. Measurement of the radionuclide 110 mAg is significant as its release has been shown to be particularly sensitive to in-reactor conditions (e.g., temperature) with broad variable particle to-particle release behaviors observed within a single compact. As such, 110 mAg activity is often used for particle selection for comprehensive PIE as bounding 110 mAg retention particles are hypothesized to represent limits in particle behaviors within a compact. As TRISO particle fuel PIE activities continue over time, IMGA measurements of the 110 mAg inventory are eventually hindered because of its relatively short half-life (~250 days). As the fuel ages from its end of irradiation (EOI) date, the measurement uncertainty and minimum detectable activity (MDA) of 110m Ag increase because the detector background continuum begins to dominate. For particles from the second AGR irradiation experiment (AGR-2), the 110m Ag MDA was above 20% of the calculated average particle inventory after approximately five half-lives, and 110m Ag activity was no longer measurable with IMGA after approximately seven half-lives. Therefore, coincidence counting approaches have been explored to determine feasibility of leveraging new approaches to overcome limitations associated with increasing MDA over time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Endogeneity of pedestrian survival time and emergency medical service response time: Variations across disadvantaged and non-disadvantaged communities

The Vision Zero-Safe Systems Approach prioritizes fast access to Emergency Medical Services (EMS) to improve the survivability of road users in transportation crashes, especially concerning the recent increase in pedestrian-involved crashes. Pedestrian crashes resulting in immediate or early death are considerably more severe than those taking longer. The time gap between injury and fatality is known as survival time, and it heavily relies on EMS response time. The characteristics of the crash location may be associated with EMS response and survival time. A US Department of Transportation initiative identifies communities often facing challenges. Six disadvantaged community (DAC) indicators, including economy, environment, equity, health, resilience, and transportation access, enable an analysis of how survival and EMS response times vary across DACs and non-DACs. To this end, this study created a unique and comprehensive database by linking DACs data with 2017–2021 pedestrian-involved fatal crashes. This study utilizes two-stage residual inclusion models with segmentation for DACs and non-DACs accounting for the endogenous relationship between EMS response and pedestrian survival time. The results indicate that EMS response time is higher and pedestrian survival time is lower in DACs than in non-DACs. A delayed EMS response time is associated with a greater reduction in survival time in DACs compared to non-DACs. Factors, e.g., nighttime and interstate crashes, contribute to higher EMS response time, while pedestrian drugs, driver speeding, and hit-and-run behaviors are associated with a greater reduction in survival time in DACs than non-DACs. Finally, the implications of the findings are discussed in the paper.

60 APPLIED LIFE SCIENCES↗