Search NASA⌕ Search

SEARCH · Search NASA

Results for “Health care”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Implementation of rapid diagnostics assays for detection of histoplasmosis and cryptococcosis in central american people living with HIV

Abstract Objectives Histoplasmosis and cryptococcosis are important public health problems in people living with HIV (PLHIV) in Central America. Conventional laboratory assays, based on microscopy and culture, are not optimal for the diagnosis of either disease. However, antigen (Ag) assays are rapid and highly accurate for the diagnosis of these infections. Methods Laboratory surveillance of PLHIV was carried out in four hospitals in Panama, Honduras and Nicaragua, between 2015 and 2019. Detection of Histoplasma antigens in urine was performed by enzyme immunoassay (EIA), and Cryptococcus antigen detection in sera and cerebrospinal fluid specimens was performed by lateral flow assay (LFA). Results A total of 4,453 PLHIV with clinical suspicion of histoplasmosis ( n = 1,343) or cryptococcosis ( n = 3,110; 2,721 sera and 389 CSF) were tested. Of 1,343 patients suspected of having histoplasmosis, 269 (20%) were Histoplasma Ag positive. Of 3,110 patients tested using the Cryptococcus Ag assay, 329 (11%) were positive. Honduras reported the highest positivity rates (32% for Histoplasma Ag, and 16% for Cryptococcus Ag); Panama reported the largest number of patients testing positive using the Histoplasma Ag assay ( n = 201); and Nicaragua reported the largest number of patients testing positive using the Cryptococcus Ag assay ( n = 170). Conclusion Here, we show how the implementation of rapid diagnostics assays impacted case detection and was useful for the care of people with advanced HIV. Rapid and accurate diagnosis could reduce mortality associated with histoplasmosis and cryptococcosis in PLHIV.

Caceres, Diego H.↗
DOE OSTI2024

Evaluating the impact of anatomical and physiological variability on human equivalent doses using PBPK models

Abstract Addressing human anatomical and physiological variability is a crucial component of human health risk assessment of chemicals. Experts have recommended probabilistic chemical risk assessment paradigms in which distributional adjustment factors are used to account for various sources of uncertainty and variability, including variability in the pharmacokinetic behavior of a given substance in different humans. In practice, convenient assumptions about the distribution forms of adjustment factors and human equivalent doses (HEDs) are often used. Parameters such as tissue volumes and blood flows are likewise often assumed to be lognormally or normally distributed without evaluating empirical data for consistency with these forms. In this work, we performed dosimetric extrapolations using physiologically based pharmacokinetic (PBPK) models for dichloromethane (DCM) and chloroform that incorporate uncertainty and variability to determine if the HEDs associated with such extrapolations are approximately lognormal and how they depend on the underlying distribution shapes chosen to represent model parameters. We accounted for uncertainty and variability in PBPK model parameters by randomly drawing their values from a variety of distribution types. We then performed reverse dosimetry to calculate HEDs based on animal points of departure for each set of sampled parameters. Corresponding samples of HEDs were tested to determine the impact of input parameter distributions on their central tendencies, extreme percentiles, and degree of conformance to lognormality. This work demonstrates that the measurable attributes of human variability should be considered more carefully and that generalized assumptions about parameter distribution shapes may lead to inaccurate estimates of extreme percentiles of HEDs.

Toxicology↗
DOE OSTI2023

Gut microbiome dynamics and associations with mortality in critically ill patients

Abstract Background Critical illness and care within the intensive care unit (ICU) leads to profound changes in the composition of the gut microbiome. The impact of such changes on the patients and their subsequent disease course remains uncertain. We hypothesized that specific changes in the gut microbiome would be more harmful than others, leading to increased mortality in critically ill patients. Methods This was a prospective cohort study of critically ill adults in the ICU. We obtained rectal swabs from 52 patients and assessed the composition the gut microbiome using 16 S rRNA gene sequencing. We followed patients throughout their ICU course and evaluated their mortality rate at 28 days following admission to the ICU. We used selbal, a machine learning method, to identify the balance of microbial taxa most closely associated with 28-day mortality. Results We found that a proportional ratio of four taxa could be used to distinguish patients with a higher risk of mortality from patients with a lower risk of mortality (p = .02). We named this binarized ratio our microbiome mortality index (MMI). Patients with a high MMI had a higher 28-day mortality compared to those with a low MMI (hazard ratio, 2.2, 95% confidence interval 1.1–4.3), and remained significant after adjustment for other ICU mortality predictors, including the presence of the acute respiratory distress syndrome (ARDS) and the Acute Physiology and Chronic Health Evaluation (APACHE II) score (hazard ratio, 2.5, 95% confidence interval 1.4–4.7). High mortality was driven by taxa from theAnaerococcus(genus) andEnterobacteriaceae(family), while lower mortality was driven byParasutterellaandCampylobacter(genera). Conclusions Dysbiosis in the gut of critically ill patients is an independent risk factor for increased mortality at 28 days after adjustment for clinically significant confounders. Gut dysbiosis may represent a potential therapeutic target for future ICU interventions.

Gastroenterology & Hepatology↗
DOE OSTI2021

Nucleic Acid-Based Sensing Techniques for Diagnostics and Surveillance of Influenza

Influenza virus poses a threat to global health by causing seasonal outbreaks as well as three pandemics in the 20th century. In humans, disease is primarily caused by influenza A and B viruses, while influenza C virus causes mild disease mostly in children. Influenza D is an emerging virus found in cattle and pigs. To mitigate the morbidity and mortality associated with influenza, rapid and accurate diagnostic tests need to be deployed. However, the high genetic diversity displayed by influenza viruses presents a challenge to the development of a robust diagnostic test. Nucleic acid-based tests are more accurate than rapid antigen tests for influenza and are therefore better candidates to be used in both diagnostic and surveillance applications. We review various nucleic acid-based techniques that have been applied towards the detection of influenza viruses in order to evaluate their utility as both diagnostic and surveillance tools. We discuss both traditional as well as novel methods to detect influenza viruses by covering techniques that require nucleic acid amplification or direct detection of viral RNA as well as comparing advantages and limitations for each method. There has been substantial progress in the development of nucleic acid-based sensing techniques for the detection of influenza virus. However, there is still an urgent need for a rapid and reliable influenza diagnostic test that can be used at point-of-care in order to enhance responsiveness to both seasonal and pandemic influenza outbreaks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Toxicity of hydraulic fracturing wastewater from black shale natural-gas wells influenced by well maturity and chemical additives

Hydraulic fracturing of deep shale formations generates large volumes of wastewater that must be managed through treatment, reuse, or disposal. Produced wastewater liberates formation-derived radionuclides and contains previously uncharacterized organohalides thought to be generated within the shale well, both posing unknown toxicity to human and ecological health. Here, we assess the toxicity of 42 input media and produced fluid samples collected from four wells in the Utica formation and Marcellus Shale using two distinct endpoint screening assays. Broad spectrum acute toxicity was assessed using a bioluminescence inhibition assay employing the halotolerant bacterium Aliivibrio fischeri, while predictive mammalian cytotoxicity was evaluated using a N-acetylcysteine (NAC) thiol reactivity assay. The acute toxicity and thiol reactivity of early-stage flowback was higher than later produced fluids, with levels diminishing through time as the natural gas wells matured. Acute toxicity of early stage flowback and drilling muds were on par with the positive control, 3,5-dichlorophenol (6.8 mg L -1 ). Differences in both acute toxicity and thiol reactivity between paired natural gas well samples were associated with specific chemical additives. Samples from wells containing a larger diversity and concentration of organic additives resulted in higher acute toxicity, while samples from a well applying a higher composition of ammonium persulfate, a strong oxidizer, showed greater thiol reactivity, predictive of higher mammalian toxicity. Both acute toxicity and thiol reactivity are consistently detected in produced waters, in some cases present up to nine months after hydraulic fracturing. These results support that specific chemical additives, the reactions generated by the additives, or the constituents liberated from the formation by the additives contribute to the toxicity of hydraulic fracturing produced waters and reinforces the need for careful consideration of early produced fluid management.

03 NATURAL GAS↗
DOE OSTI2025

Announcing the Biomedical Data Translator: Initial Public Release

ABSTRACT The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open‐source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. We announce here Translator's initial public release and provide an overview of its architecture, standards, user interface, and core features. Translator employs a scalable, federated, knowledge graph framework for the integration of clinical, genomic, pharmacological, and other biomedical knowledge sources, enabling query retrieval, inference, and hypothesis generation. Translator's user interface is designed to support the exploration of knowledge relationships and the generation of insights, without requiring deep technical expertise and gradually revealing more detailed evidence, provenance, and confidence information, as needed by a given user. To demonstrate Translator's application and impact, we highlight features of the user interface in the context of three real‐world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism. We discuss strengths and limitations of reasoning within a largely federated system and the need for rich concept modeling and deep provenance tracking. Finally, we outline future directions for enhancing Translator's functionality and expanding its data sources. Translator represents a significant step forward in making complex biomedical knowledge more accessible and actionable, aiming to accelerate translational research and improve patient care.

Research & Experimental Medicine↗
DOE OSTI2021

National Virtual Biotechnology Laboratory: Report on Rapid R&D Solutions to the COVID-19 Crisis

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply short ages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. Within months, NVBL teams produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment (PPE), creating nearly 1,000 new jobs. They used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported U.S. Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and U.S. Department of Defense (DoD) efforts to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. NVBL teams also studied how to control indoor virus movement to minimize uptake and protect human health. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development (R&D) solutions. As the fight against COVID continues, sustained efforts are needed to confront this pandemic as well as future threats. Examples include: 1) Establishing “supply chains on demand” to meet emergency production needs by leveraging the materials and manufacturing expertise of DOE national laboratories and developing advances in electronics, sensing, robotics, and automation capabilities; 2) Improving the speed and robustness of drug discovery by integrating experimental platforms with DOE’s computational and experimental user facilities, which provide unique resources to support the discovery of high-potential therapeutic agents; 3) Protecting public, environmental, and animal health by developing new testing protocols and instrumentation adaptable to diverse sample types (both physiological and environmental) to quickly detect a wide range of pathogens and monitor other biorisks; 4) Supporting near-real-time data needs of decision-makers at the local, regional, state, and national levels by advancing data curation, analysis, and modeling using artificial intelligence and new data science tools for managing and evaluating large diverse datasets; 5) Harnessing DOE’s expertise in environmental modeling to design rooms and air handling for offices, classrooms, restaurants, and other structures to minimize biorisk transmissions. Going forward, NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, the Office of Science will continue to be an integral component of agency wide efforts to prepare for and respond to biorisks and other crises.

42 ENGINEERING↗
DOE OSTI2021

Tunable, Bacterio-Instructive Scaffolds Made from Functional Graphenic Materials

The balance of bacterial populations in the human body is critical for human health. Researchers have aimed to control bacterial populations using antibiotic substrates. However, antibiotic materials that non-selectively kill bacteria can compromise health by eliminating beneficial bacteria, which leaves the body vulnerable to colonization by harmful pathogens. Due to their chemical tunablity and unique surface properties, graphene oxide (GO)-based materials – termed “functional graphenic materials” (FGMs) – have been previously designed to be antibacterial but have the capacity to actively adhere and instruct probiotics to maintain human health. Numerous studies have demonstrated that negatively and positively charged surfaces influence bacterial adhesion through electrostatic interactions with the negatively charged bacterial surface. We found that tuning the surface charge of FGMs provides an avenue to control bacterial attachment without compromising vitality. Using E. coli as a model organism for gram-negative bacteria, we demonstrate that negatively charged Claisen graphene (CG), a reduced and carboxylated FGM, is bacterio-repellent through electrostatic repulsion with the bacterial surface. Though positively charged poly-L-lysine (PLL) is antibacterial when free in solution by inserting into the bacterial cell wall, here, we found that covalent conjugation of PLL to CG (giving PLLn-G) masks the antimicrobial activity of PLL by restricting polypeptide mobility. This allows the immobilized positive charge of the PLLn-Gs to be leveraged for E. coli adhesion through electrostatic attraction. We identified the magnitude of positive charge of the PLLn-G conjugates, which is modulated by the length of the PLL peptide, as an important parameter to tune the balance between the opposing forces of bacterial adhesion and proliferation. We also tested adhesion of gram-positive B. subtilis to these FGMs and found that the effect of FGM charge is less pronounced. B. subtilis adheres nondiscriminatory to all FGMs, regardless of charge, but adhesion is scarce and localized. Overall, this work demonstrates that FGMs can be tuned to selectively control bacterial response, paving the way for future development of FGM-based biomaterials as bacterio-instructive scaffolds through careful design of FGM surface chemistry.

Eckhart, Karoline E.↗
DOE OSTI2020

Risk to Ecological Resources on Burial Waste Sites on the Hanford Site, Washington - 20248

The US and other nations have a large nuclear and chemical waste remediation task remaining from World War II, the Cold War, and industrial activities. The US Department of Energy (DOE) has the largest task in the U.S., with Hanford (Washington State) being the most contaminated site, with the longest and most costly cleanup program projected to extend to the end of the century. One of the greatest remediation problems at Hanford are the burial waste facilities, some of which are inside the 200 Areas on the Central Plateau, while others are outside the 200 Areas. These areas are associated with waste sites, pipes, and contaminated trenches, posing technical cleanup challenges to meet DoE's remediation goals, including protection of human health and the environment commensurate with Tri- Party Agreement and current regulatory requirements. In this paper we select one of the legacy waste sites (the BC Cribs and Trenches) as a case study to explore how risk to ecological resources varies during and as a consequence of remediation on sites primarily considered legacy waste sites. We used the risk methodology developed by the Consortium for Risk Evaluation with Stakeholder Participation (CRESP) during the Hanford Site-wide Risk Review. The CRESP methodology included evaluating the risk to receptors, including human health, the Columbia River, groundwater, and ecological and cultural resources. The risk evaluation process for ecological receptors included defining the boundaries of each evaluation unit (EU) to be remediated, definition of a suitable buffer area that might be affected, and consideration of the known resource value based on field work. This information, coupled with known remediation options or strategies, allowed us to develop a risk rating for ecological resources. Site risks were evaluated on a scale of 'not discernible' to 'very high' risk. Consideration of the risks at the buried waste sites was complicated by uncertainties in remediation methods and the degree of restoration that would occur as part of the remediation process. We use the BC Cribs and Trenches as a case study to explore why the risks are low currently but increase during remediation. The current 'not discernible to low' risk rating is due to the lack of high quality ecological resources on the BC Cribs and Trenches EU, except for edge areas (with some state-listed species). During remediation the risks increase to 'medium', mainly due to high quality resources on adjacent buffer lands, which could be disrupted during active remediation. Medium and high quality resources on the edge of the site are continuous with higher quality native shrub-steppe habitat on the buffer. Ecological resources on some of the areas surrounding the 200 East and West Areas are some of the highest quality shrub-steppe areas on the Hanford Site, and risk to these resources could be prevented by planning before and during remediation to minimize disruption. For example, lay down areas for the BC Cribs and Trenches can be minimized by careful planning. Heavy truck and other vehicular traffic can be minimized. Spread of the noxious weeds now on some of the site can be prevented, and the spread of invasive species into the site (particularly near undisturbed shrub-steppe habitat) can be reduced. Further, the areas around and between the 200 East and West Areas have been largely undisturbed and can serve as a source of seeds and propagules for any revegetation that occurs as part of the remediation process. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Next-Generation, High-temperature, High-frequency, High-efficiency, High-power-density Traction System

To meet performance and reliability requirements necessary for broader adoption of electric drive vehicles, the Electrical and Electronics Technical Team of the U.S. Drive partnership has established aggressive design goals for next-generation electric vehicle drivetrains. Specifically, the 2025 roadmap stipulates a 100 kW/L power density target and a $\$$2.7/kW cost target for power electronics, in addition to high-voltage operation (i.e., greater than 800 VDC). The additional targets for traction motor and the overall system performance impose further challenges on the power electronics design. For example, many high specific power machines have reduced iron content, and therefore reduced intrinsic filtering, thus requiring the inverter to supply a low-distortion drive current. These machines also typically have a high pole count, thus requiring drive current at a higher electrical frequency. Other motors, such as brush-less dc and switch reluctance machines, require a carefully-shaped, non-sinusoidal drive current (Yang, Shang, Brown, & Krishnamurthy, 2015), (Zhang, Bowman, O'Connel, & Haran, 2018), (Anderson, et al., 2018). Two- and three-level inverter topologies are the conventional framework for the power electronics design of the drivetrain, and some demonstrations have shown recent progress towards addressing cost, power density and efficiency goals (Gurpinar & Ozpineci, 2018), (Zhu, Kim, Chen, Erickson, & Maksimović, 2018), (Deshpande, Chen, Narayanasamy, Sathyanarayanan, & Luo, 2018), (Alizadeh, et al., 2019). However, an unconventional approach may be necessary to take the dramatic leap in power density necessitated by the roadmap—while simultaneously addressing the other system needs. Therefore, this project leverages the flying capacitor multilevel (FCML) topology, together with a scalable, modular approach, to address these needs. This type of hybrid converter has several advantages: lower voltage (i.e., less than 300 V) transistors can be used, energy-dense capacitors process most of the power, and the output current waveform is multilevel and exhibits a frequency multiplying effect—in other words, the output has reduced dv/dt and filtering requirements for the same high voltage dc bus. For example, in an electric vehicle with an 800 V bus, a 10-level FCML could leverage 100 V, commercially available GaN devices switching at 115 kHz to produce a ~1 MHz switching waveform (modulated according to the motor drive requirements) with one ninth of the dv/dt of a two-level converter. Prior work has already demonstrated promising performance and gravimetric power density figures for more electric aircraft applications (Pallo, Foulkes, Modeer, Coday, & Pilawa-Podgurski, 2018). This project leverages lessons learned to achieve the volumetric power density of 100 kW/L by employing advanced liquid cooling, address the 300,000 mile reliability challenge with redundant design, topology failure studies and online health monitoring, and reduce costs to $\$$2.7/kW through the use of low-cost GaN devices, modular converter assemblies, and modest modifications to traditional manufacturing methods. The project involved several hardware designs, each achieving increasing performance. At the conclusion of the project, a volumetric power density of 380 kW/L was achieved, in a 800V dc-ac converter, greatly surpassing even the aggressive target goal.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

U.S. Department of Energy: National Virtual Biotechnology Laboratory (Technical Report)

With funding from the CARES Act, the U.S Department of Energy (DOE) established the National Virtual Biotechnology Laboratory (NVBL) in March 2020 to address key challenges associated with the COVID-19 crisis. The NVBL brought together the broad scientific and technical expertise and resources of DOE’s 17 national laboratories to help tackle medical supply shortages, discover potential drugs to fight the virus, develop and validate COVID-19 testing methods, model disease spread and impact across the nation, and understand virus transport in buildings and the environment. National laboratory resources leveraged for this effort include a suite of world-leading user facilities broadly available to the research community, such as light and neutron sources, nanoscale science research centers, sequencing and biocharacterization facilities, and high-performance computing facilities. As part of the NVBL framework, DOE rapidly assembled five project teams to (1) identify new targets for medical therapeutics; (2) develop innovations in testing capabilities; (3) provide epidemiological and logistical support; (4) understand viral fate and transport in the environment; and (5) address supply chain bottlenecks by harnessing extensive additive manufacturing capabilities. Each research team was charged with defining high-impact projects that could be completed in a 6-month sprint while coordinating their developments with academia, other government agencies, and the private sector. Within months, NVBL teams used DOE’s high-performance computers and light and neutron sources to identify promising candidates for antibodies and antivirals that universities and drug companies are now evaluating. NVBL researchers also developed new diagnostic targets and sample collection approaches, and supported efforts by the U.S. Food and Drug Administration, Centers for Disease Control and Prevention, and U.S. Department of Defense to establish national guidelines used in administering millions of tests. Researchers used artificial intelligence and high-performance computing to produce near-real-time data analysis to forecast disease transmission, stress on public health infrastructure, and economic impact, which supported decision-makers at the local, state, and national levels. To minimize virus uptake and protect human health, NVBL teams studied how to control indoor virus movement. Researchers also produced innovations in materials and advanced manufacturing that mitigated shortages in test kits and personal protective equipment, creating nearly 1,000 new jobs. Through its NVBL framework, DOE has contributed significantly to the nation’s COVID response, demonstrating in only a few months the critical impact of its national laboratories. NVBL’s accomplishments demonstrate not only the powerful resource represented by DOE’s national laboratories working together to meet national needs, but also the effectiveness of the integrated NVBL framework for rapidly responding to emergencies with research and development solutions. Going forward, the NVBL is poised to apply the unique capabilities and expertise of the national laboratory complex to future national and international emergencies, both natural and engineered. Through this framework, DOE will continue to be an integral component of agency-wide efforts to prepare for and respond to biorisks and other crises. This technical report describes the goals, progress, and results of NVBL’s five project teams—Molecular Design for COVID-19 Therapeutics, COVID-19 Testing, Epidemiological Modeling, Viral Fate and Transport, and Materials and Manufacturing of Critical Supplies—and lists each team’s publications and research output.

42 ENGINEERING↗
DOE OSTI2022

Evaluation of Oak Ridge National Laboratory Health Physics Research Reactor Operation Data for Critical Benchmark Creation

The Oak Ridge National Laboratory (ORNL) Health Physics Research Reactor (HPRR) was a research reactor designed and built at ORNL in 1961. The critical assembly used a highly enriched uranium and molybdenum alloy as the fuel and could be operated in steady-state or burst modes. The HPRR has recently been the object of an investigation to create a criticality benchmark. Such benchmarks are very important, as they are used primarily to show the accuracy of newly developed modeling codes and to help experimental validation and reactor licensing. The evaluated experiments considered in this paper were carried out between 1974 and 1986 from various HPRR activities such as steady-state subcritical, steady-state critical, and burst prompt super-critical operations of the reactor for dosimetry, irradiation, or training purposes. By using the HPRR experimental logbook information and the as-built drawings of the critical assembly, a highly detailed model of the HPRR was created with SCALE 6.2.4/KENO-VI, and a first version of a critical benchmark of the HPRR was developed following the International Criticality Safety Benchmark Evaluation Project (ICSBEP) guidelines for thorough description and uncertainty/sensitivity quantification. Unfortunately, in most of the evaluated experiments, the obtained difference between calculated and experimental k eff is around 1,000 pcm, corresponding to a relative error of approximately 1%, beyond the quality standards of the ICSBEP recommending a relative error below 0.1%. Moreover, the derived experimental uncertainty is high, around 4% relative, mainly due to the U-Mo fuel density uncertainty, but also from numerous other factors. For these reasons, the creation of a valuable critical benchmark from HPRR operation data is thus far compromised. In this paper, the different steps of the experiments’ evaluation are summarized, and the reasons for the experimental/calculation discrepancies and potential ways to solve them are explored. This paper also aims to remind us always to exercise considerable care when performing experimental work, and to record all the data possible for potential future uses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Incidence and predictors of loss to follow-up among adult patients receiving antiretroviral therapy in Central Ethiopia: a multi-center retrospective cohort study

Background: Globally, loss to follow-up (LTFU) remains a significant public health concern despite the rapid expansion of antiretroviral medication programs. It is a significant cause of treatment failure and threatens the enhancement of HIV treatment outcomes among patients on antiretroviral therapy (ART). However, there is a paucity of evidence on its incidence and predictors in Ethiopia. Thus, this study aimed to examine the incidence and predictors of LTFU among adult HIV patients receiving ART at hospitals in Central Ethiopia. Methods: A multi-centered facility-based retrospective cohort study was conducted among 432 randomly selected adult patients who received antiretroviral therapy. Data were entered into EpiData version 3.1 and exported to Stata version 14 for analysis. The Kaplan–Meier failure function was employed to determine the overall failure estimates, and the log-rank test was used to compare the probability of failure among the different categories of variables. The Cox proportional hazard model was used to identify independent predictors of LTFU. Results: Overall, 172 (39.8%) study participants were lost to follow-up over the 10-year follow-up period with an incidence rate of 8.12 (95% CI: 7.11, 9.09) per 1,000 person-months. Undisclosed HIV status (AHR: 1.96, 95% CI: 1.14, 3.36), not able to work (AHR: 1.84, 95% CI: 1.13, 2.22), opportunistic infections (AHR: 3.13, 95% CI: 2.17, 4.52), CD4 < 200 cell/mL (AHR: 1.95, 95% CI: 1.18, 3.21), not receiving isoniazid preventive therapy (IPT) (AHR: 2.57, 95% CI: 1.62, 4.06), not participating in clubs (AHR: 1.68, 95% CI: 1.10, 2.22), side effects of drugs (AHR: 1.44, 95% CI: 1.02, 2.04), and high viral load (AHR: 3.15, 95% CI: 1.81, 5.47) were identified as significant predictors of loss to follow-up. Conclusion: In this study, the incidence of LTFU was high. The focus should be on creating awareness and prevention programs that aim to reduce loss to follow-up by continuing counseling, especially on the negative effects of loss to follow-up and the benefits of ART care.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Allopregnanolone as an Adjunct Therapy to Midazolam is More Effective Than Midazolam Alone in Suppressing Soman‐Induced Status Epilepticus in Male Rats

ABSTRACT Aims Humans and animals acutely intoxicated with the organophosphate soman can develop sustained status epilepticus (SE) that rapidly becomes refractory to benzodiazepines. We compared the antiseizure efficacy of midazolam, a current standard of care treatment for OP‐induced SE, versus combined therapy with midazolam and allopregnanolone (ALLO) in a rat model of soman‐induced SE. Methods Soman‐intoxicated male rats with robust seizure behavior and high‐amplitude electroencephalographic (EEG) activity were administered midazolam (0.65 mg, i.m.) 20 min after seizure initiation and 10 min later either a second dose of midazolam or ALLO (12 or 24 mg/kg, i.m.). Seizure behavior and EEG were monitored for 4 h after treatment. Brains were collected at the end of the monitoring period for histological analyses. Results Animals receiving 2 doses of midazolam exhibited persistent SE. Sequential dosing with midazolam followed by ALLO suppressed electrographic seizure activity. The combination therapy also significantly reduced soman‐induced neurodegeneration and neuroinflammation compared to 2 doses of midazolam. High but not low dose ALLO was associated with transitory and reversible respiratory compromise during the 1 h period after dosing. Conclusions Treatment with midazolam followed by ALLO was more effective than 2 doses of midazolam in suppressing benzodiazepine‐refractory, soman‐induced SE, and in mitigating its acute neuropathological consequences.

Andrew, Peter M. [Department of Molecular Bioscien↗
DOE OSTI2020

Initial Atmospheric Transport of Particles

A new version of the Initial Atmospheric Transport (IAT) model has been developed. This report fully characterizes the new model. IAT is designed to model heat release into the atmosphere that contains contaminated particles. The heat release forms a buoyant puff or plume. Buoyancy is quickly dissipated in 10's to 100's of seconds through drag and entrainment of ambient air. The final location of contaminant particles in the atmosphere after dissipation of abnormal heat is an important input to long term transportation codes such as the National Oceanic and Atmospheric Administration's (NOAA) Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) code. Ultimately the settling of contaminants after long term transport provides a basis for estimating health consequences. In comparison to the old version, the new model includes explicit simulation of particles, newly formulated equations of motion for a rising puff, and a new plume model. The plume model releases many instances of a single puff along a single trajectory in a way that balances energy released over a longer period than would be appropriate for a single puff. The puff model has additions for vorticity, turbulence, virtual mass, drag, and entrainment. The particle model leads to direct interfacing between IAT and the long-term transport code HYSPLIT. Previously, particle locations were given a pattern based on IAT's puff trajectory with no particle simulation. Now, particles are explicitly simulated, and 3-D spatial distributions of particles are output based on final positions. Ballistic particles are thrown outward at high velocity from explosive events and tend to hit the ground before the end of the simulation. Non-ballistic particles tend to get pulled into the rising puff s ring of vorticity with some escaping to ambient conditions as buoyant energy dissipates. A new model verification and validation effort was made for the new plume model. The Wallops Island Solid Rocket Propellant (SRP) fire plume was extracted to a 3-D transient dataset. After calibration, the model performs better than previous single puff attempts. Even so, error levels in the process used to estimate location and ambient weather conditions approach 30%. This leads to the conclusion that unplanned photogrammetry evaluations of the IAT model are useful but not sufficiently accurate to quantify model parameters. Like previous attempts, the vertical motion entrainment parameters come out much too high in comparison to values for other studies in the literature. It is suspected that a new model of shear entrainment would alleviate this problem. Unfortunately, IAT already has more calibration parameters than the data comparisons thus far can resolve with statistical certainty. This underscores the need to verify and validate the IAT model using detailed CFD studies that allow ideal statistical comparison with the IAT model for hundreds of cases. Even so, validation by comparison to carefully planned experiments (i.e. with acceptable error levels) is also necessary because the dynamics of entrainment are at a sub-grid level for CFD. Though better validation and verification are most important, many new enhancements are still envisioned for future IAT development. These include particle rain out due to condensation and agglomeration of water, direct connection to the North American Mesoscale (NAM) weather dataset, dynamic weather conditions, including ambient particle entrainment into the puff, and detrainment at the puff to ambient mixing interface. In general, including detailed aerosol dynamics is the greatest coming challenge which will require an entire new sub-model in IAT. This is very important if contaminant particles change in such a way that they increase or decrease in their potential harm to the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Leveraging Large Language Models for Real-World Data Evidence: A Framework for Automated Treatment Extraction and Data Harmonization

Background: The ability to comprehensively collect treatment information from cancer patient medical records would enable studies to evaluate real-world benefits and risks tied to specific treatments. Currently, it is difficult to system- atically collect high-quality treatment information because it is often stored in unstructured text. Manually extracting and standardizing drug and regimen data is time-intensive. Recent advances in large language models (LLMs) offer a potential solution for automated extraction of structured treatment information from clinical text. Objective: This study systematically evaluates the utility of four LLMs from the Llama family for automated extraction of oncology treatment information from clinical text. This information can guide researchers using cancer registry data to provide insights into cancer care and outcomes beyond clinical trials. Methods: Four instruction-tuned Llama models with varying parameter counts (1B, 3B, 8B, and 70B) were evaluated for their ability to extract treatment information from clinical documents. A unified oncology knowledge base integrating seven major public data sources was developed to standardize and normalize extracted entities—a critical step for harmonizing data from diverse sources. Extracted treatment data were compared against expert-annotated ground truth. Model performance was assessed using accuracy metrics (Precision, Recall, F1-Score) and opera- tional feasibility metrics, including processing speed and structural compliance of the output. Results: A strong positive correlation was observed between model size and extraction accuracy. F1-score improved from 0.609 for the 1B model to 0.710 (3B), 0.807 (8B), and 0.828 (70B). While larger models demonstrated superior accuracy and compliance, they incurred higher computational costs. The modest performance difference between 8B and 70B suggests diminishing returns with increasing model size. Conclusions: LLMs represent a viable technology for automating oncology treatment extraction. The 8B-parameter model emerged as a highly effective option, balancing high accuracy and computational efficiency. Selecting an appropriate LLM for deployment in cancer registries involves a trade-off between desired accuracy and available operational resources. Harmonizing extracted entities with the oncology knowledge base facilitates standardized integration into common data models, enhancing data quality for real-world evidence analyses.

artificial intelligence↗
DOE OSTI2023

Health Hazards of Exposures to Radioiodine

Iodine is a chemical element with atomic number 53. Iodine-127 is stable (non-radioactive) and commonly found in nature. Elemental iodine is a purple-colored solid at room temperature and pressure, but spontaneously sublimates (turns into vapor). Iodine is an essential element for life, and is required for proper functioning of the thyroid. Iodine is present in many foods, and is readily absorbed by the body and concentrated in the thyroid gland. A fraction of iodine ingested or inhaled is rapidly removed by the kidneys. The rest of the inhaled or ingested iodine is absorbed the by thyroid and retained for many months. Iodine has a biological half-life of approximately 120 days in health individuals. The biological half-life can be shorter in individuals with hyperthyroidism, and longer in individuals with hypothyroidism. Iodine has a number of radioactive isotopes, most of which have relatively short half-lives (days or weeks). Short half-life iodine isotopes are useful for a variety of medical applications, including imaging and cancer therapy. For example, Iodine-123 (half-life 13 hours) is commonly used for medical imaging of the thyroid, while iodine-131 (half-life 8 days) is used for suppressing thyroid function in individuals with hyperthyroidism or ablating (killing) thyroid cells to treat thyroid cancer. Iodine-125 (half-life 59 days) is produced in nuclear reactors, and has medical uses. Although iodine-125 can be used for thyroid imaging, Iodine-123 is more commonly used for that purpose because of its shorter half-life and higher-energy emissions. Iodine-125 is more commonly used for cancer treatment, and can be processed into small metal pellets (seeds) inserted directly into a tumor. Iodine-125 emits low-energy x-rays which can kill tumor cells and generally cannot escape the tumor, sparing other tissues. Medical iodine for imaging or treatment is typically administered orally in the form a pill or liquid solution. A typical adult thyroid scan using iodine-123 involves having the patient swallow between one and four 0.1 millicuries pills, with the exact dose dependent on the patient’s weight. This results in a whole-body committed effective dose of 80 – 320 mrem, and a thyroid equivalent dose of 1443 – 5772 mrem. Note that the whole-body effective dose relates to the overall cancer risk, while the larger equivalent dose to the thyroid only indicates that most of this risk is the result of exposure to the thyroid. These doses are considered safe, although the procedure is not recommended for pregnant or breastfeeding women. In contrast, the quantities of iodine-131 used for treatment of hyperthyroidism and thyroid cancers are much higher. For treatment of hyperthyroidism, 4 – 10 millicuries are administered, while for thyroid cancer the administration can range from 50 – 150 millicuries of I-131. In addition to medical exposures, large populations were exposed to radioiodine as result of the atomic bombings of Hiroshima and Nagasaki in Japan, and the Chernobyl nuclear accident. These populations have been carefully followed for many years to assess the effect of their radiation exposures on cancer risk. As a result, a great deal is known about the cancer risks associated with radioiodine exposure. Because iodine is concentrated in the thyroid, the principal risk of exposure to radioiodine is thyroid cancer. Children have the highest risk of thyroid cancer after exposure to radioactive iodine. According to a large study of Japanese atomic bomb survivors, an effective dose of one Sievert (100,000 mrem) has been observed to increase the risk of thyroid cancer by a factor of 9.5 in children aged zero to nine years old, by a factor of 3 in children aged 10 to 19 years old, and by barely detectable amounts in adults. Another way of quantifying the risk from radioiodine exposure is from risk coefficients, which provide the risk per unit intake of radionuclides in terms of both morbidity (any cancer) and mortality (death). Both morbidity (risk of cancer) and mortality (death) risks are shown in the table below. Note that because thyroid cancer is almost never fatal, the morbidity coefficients are much larger than the mortality coefficients.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Evaluation of Serial Testing After Exposure to COVID-19 in Early Care and Education Facilities, Illinois, March–May 2022

Objective: To understand SARS-CoV-2 transmission in early care and education (ECE) settings, we implemented a Test to Stay (TTS) strategy, which allowed children and staff who were close contacts to COVID-19 to remain in person if they agreed to test twice after exposure. We describe SARS-CoV-2 transmission, testing preferences, and the number of in-person days saved among participating ECE facilities. Methods: From March 21 through May 27, 2022, 32 ECE facilities in Illinois implemented TTS. Unvaccinated children and staff who were not up to date with COVID-19 vaccination could participate if exposed to COVID-19. Participants received 2 tests within 7 days after exposure and were given the option to test at home or at the ECE facility. Results: During the study period, 331 TTS participants were exposed to index cases (defined as people attending the ECE facility with a positive SARS-CoV-2 test result during the infectious period); 14 participants tested positive, resulting in a secondary attack rate of 4.2%. No tertiary cases (defined as a person with a positive SARS-CoV-2 test result within 10 days after exposure to a secondary case) occurred in the ECE facilities. Most participants (366 of 383; 95.6%) chose to test at home. Remaining in-person after an exposure to COVID-19 saved approximately 1915 in-person days among children and staff and approximately 1870 parent workdays. Conclusion: SARS-CoV-2 transmission rates were low in ECE facilities during the study period. Serial testing after COVID-19 exposure among children and staff at ECE facilities is a valuable strategy to allow children to remain in person and parents to avoid missing workdays.

Public, Environmental & Occupational Health↗