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All sources NASA NTRS DOE OSTI

DOE OSTI2020

Field experimental evidence shows that self-interest attracts more sunlight

This study examines how messaging approaches in a prosocial intervention can influence not only the effectiveness of the intervention but also, contagion afterward. Our investigation focuses on leveraging two motivations for solar adoption: self-interest and prosocial. Using data from a natural field experiment in 29 municipalities containing 684,000 people, we find that self-interest messaging is twice as effective in inducing solar adoption both during and after the intervention. Adoptions under self-interest messaging have 10% higher net present value, but prosocial messaging increases the likelihood that adopters recommend solar to their friends and neighbors. Income moderates the effectiveness of self-interest messaging, performing much better in high-income communities than low- and moderate-income communities. There was no significant difference across income groups for prosocial messaging. These results provide guidance to policy makers aiming to encourage prosocial behavior across all income groups.

14 SOLAR ENERGY↗

DOE OSTI2025

Cognitive behavioural therapy targeting cardiac anxiety post-myocardial infarction: results from two sequential pilot studies

Abstract Aims Cardiac anxiety, which is cardiac-related fear and avoidance behaviours, is common following myocardial infarction (MI) and has been associated with increased risk for cardiovascular events. However, there are currently no treatments specifically designed to target cardiac anxiety. The aim of the two pilot studies was to evaluate an exposure-based cognitive behavioural therapy protocol (MI-CBT) targeting cardiac anxiety following MI, assessing feasibility, acceptability, and the intervention's potential for reducing cardiac anxiety and improving health-related quality of life (QoL). Methods and results A series of two sequential, uncontrolled pilot studies were conducted. In Pilot Study 1 (n = 15), MI-CBT was delivered via face-to-face videoconference, while Pilot Study 2 (n = 23) was delivered online. Patients with a history of MI (≥6 months before assessment, type 1 ST- or non-ST-segment elevation MI, and elevated cardiac anxiety as per clinical interview) were included. The interventions lasted 8 weeks and were therapist-led, with key components including exposure to cardiac-related symptoms and reduction of avoidance behaviours. Participants completed self-rated assessments, including the Cardiac Anxiety Questionnaire (CAQ) and the 12-Item Short Form Health Survey (SF-12), at baseline, post-treatment, and 6-month follow-up. Treatment adherence and satisfaction were high. Cognitive behavioural therapy led to a large reduction in cardiac anxiety, as measured by the CAQ (P < 0.001), and significant improvements in health-related QoL, as measured by the SF-12 (P < 0.001), in both pilot studies. Conclusion These studies suggest that exposure-based CBT is a feasible, acceptable, and promising approach to reduce cardiac anxiety and improve QoL following MI. A randomized controlled trial should be conducted to evaluate the efficacy of the intervention.

Johnsson, Amanda (ORCID:0009000862983934)↗

DOE OSTI2025

Ethical considerations in infectious disease modelling for public health policy: the case of school closures

Mathematical models of infectious diseases are frequently used as a tool to support public health policy and decisions around the implementation of interventions such as school closures. However, most publications on policy-relevant modelling lack an ethical framework and do not explicitly consider the ethical implications of the work. This creates a risk that the unintended consequences of interventions are overlooked or that models are used to justify decisions that are inconsistent with public health ethics. In this article, we focus on the case study of school closures as a commonly modelled intervention against pandemic influenza, COVID-19 and other infectious disease threats. We briefly review some of the key concepts in public health ethics and describe approaches to modelling the effects of school closures. We then identify a series of ethical considerations involved in modelling school closures. These include accounting for population heterogeneity and inequalities; including a diversity of viewpoints and expertise in model design; considering the distribution of benefits and harms; and model transparency and contextualization. Furthermore, we conclude with some recommendations to ensure that policy-relevant modelling is consistent with some key ethics values.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Social Learning and Solar Photovoltaic Adoption

Growing literature points to the effectiveness of leveraging social interactions and nudges to spur adoption of prosocial behaviors. This study investigates a large-scale behavioral intervention designed to actively leverage social learning and peer interactions to encourage adoption of residential solar photovoltaic systems. Municipalities choose a solar installer offering group pricing and undertake an informational campaign driven by volunteer ambassadors. We find a causal treatment effect of 37 installations per municipality from the campaigns and no evidence of harvesting or persistence. The intervention also lowers installation prices. Randomized controlled trials based on the intervention show that selection into the program is important, whereas group pricing is not. Our results suggest that the program provided economies of scale and lowered consumer acquisition costs, leading to low-cost emission reductions. This paper was accepted by Matthew Shum, marketing.

Business & Economics↗

DOE OSTI2021

Reopening California: Seeking robust, non-dominated COVID-19 exit strategies

The COVID-19 pandemic required significant public health interventions from local governments. Although nonpharmaceutical interventions often were implemented as decision rules, few studies evaluated the robustness of those reopening plans under a wide range of uncertainties. This paper uses the Robust Decision Making approach to stress-test 78 alternative reopening strategies, using California as an example. This study uniquely considers a wide range of uncertainties and demonstrates that seemingly sensible reopening plans can lead to both unnecessary COVID-19 deaths and days of interventions. We find that plans using fixed COVID-19 case thresholds might be less effective than strategies with time-varying reopening thresholds. While we use California as an example, our results are particularly relevant for jurisdictions where vaccination roll-out has been slower. The approach used in this paper could also prove useful for other public health policy problems in which policymakers need to make robust decisions in the face of deep uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Association of microbial dynamics with urinary estrogens and estrogen metabolites in patients with endometriosis

Endometriosis is an estrogen dependent gynecological disease associated with altered microbial phenotypes. The association among endogenous estrogen, estrogen metabolites, and microbial dynamics on disease pathogenesis has not been fully investigated. Here, we identified estrogen metabolites as well as microbial phenotypes in non-diseased patients (n = 9) and those with pathologically confirmed endometriosis (P-EOSIS, n = 20), on day of surgery (DOS) and ~1–3 weeks post-surgical intervention (PSI). Then, we examined the effects of surgical intervention with or without hormonal therapy (OCPs) on estrogen and microbial profiles of both study groups. For estrogen metabolism analysis, liquid chromatography/tandem mass spectrometry was used to quantify urinary estrogens. The microbiome data assessment was performed with Next generation sequencing to V4 region of 16S rRNA. Surgical intervention and hormonal therapy altered gastrointestinal (GI), urogenital (UG) microbiomes, urinary estrogen and estrogen metabolite levels in P-EOSIS. At DOS, 17β-estradiol was enhanced in P-EOSIS treated with OCPs. At PSI, 16-keto-17β-estradiol was increased in P-EOSIS not receiving OCPs while 2-hydroxyestradiol and 2-hydroxyestrone were decreased in P-EOSIS receiving OCPs. GI bacterial α-diversity was greater for controls and P-EOSIS that did not receive OCPs. P-EOSIS not utilizing OCPs exhibited a decrease in UG bacterial α-diversity and differences in dominant taxa, while P-EOSIS utilizing OCPs had an increase in UG bacterial α-diversity. P-EOSIS had a strong positive correlation between the GI/UG bacteria species and the concentrations of urinary estrogen and its metabolites. These results indicate an association between microbial dysbiosis and altered urinary estrogens in P-EOSIS, which may impact disease progression.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Cooperative Research and Development Agreement With Georgetown University Report: National Institutes of Health, National Center for Advancing Translational Sciences Clinical and Translational Science Award

Oak Ridge National Laboratory (ORNL) is participating with Georgetown University (GU) as a subrecipient in response to the National Institutes of Health (NIH), National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Award (CTSA) (U54 Clinical Trial Optional) funding opportunity announcement. This Cooperative Research and Development Agreement is put in to place to facilitate the development and implementation of clinical interventions that demonstrably improve human health is currently a complex, recursive, and inefficient process that leads to delays of years or decades before discoveries in biomedical research result in health benefits for patients and communities. NCATS conducts and supports research in the science of translation, to discover the mechanistic and operational principles of the intervention development and dissemination process, thereby providing the scientific foundation for improvements in translational efficiency that will accelerate the realization of interventions that improve human health. Under NCATS’ leadership, the CTSA Program supports a national network of medical research institutions called hubs. GU is the lead institution in one of the NIH hubs that was created as a result of a previous NIH CTSA. The missions of the GU have historically included the advancement of health through research in the clinical and biomedical sciences, the education of future leaders in medical and nursing practice and academia, and the provision of compassionate and scientifically competent patient care and service to the Washington, DC community and the nation. GU is the lead institution for the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS), a multi-institutional partnership of medical research institutions forged from a desire to promote clinical research and translational science. Through multiple collaborations among these institutions, GHUCCTS is transforming clinical research and translational science in order to bring new scientific advances to health care. Oak Ridge National Laboratory is the Department of Energy's (DOE) largest science and energy laboratory. Managed since April 2000 by a partnership of the University of Tennessee and Battelle, ORNL was established in 1943 as a part of the secret Manhattan Project to pioneer a method for producing and separating plutonium. During the 1950s and 1960s, ORNL became an international center for the study of nuclear energy and related research in the physical and life sciences. With the creation of DOE in the 1970s, ORNL's mission broadened to include a variety of energy technologies and strategies. Today the laboratory supports the nation with a peacetime science and technology mission that is just as important as, but very different from, its role during the Manhattan Project. ORNL is home to the world's premier center for high performance supercomputing to enable scientific discovery. ORNL has extensive expertise in various areas of computer science that are uniquely situated to support GU. Additionally, ORNL’s leading computational user facilities present a unique opportunity to leverage the largest scale machines for open science in support of the stated mission of the NCATS CTSA. ORNL's partnership with GU will offer unparalleled opportunity in data analytics, deep-learning, artificial intelligence, and urban dynamics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Agent-based Disease Surveillance and Transmission Model

The SARS-CoV-2 pandemic has driven a need for models that can predict transmission among populations and test the effectiveness of proposed interventions to control it such as testing, quarantining, vaccinations, and nonpharmaceutical interventions. Some questions of interest include:1. How rapidly will the virus spread if no action is taken? 2. How frequently should people be tested and quarantined if necessary? 3. Should unvaccinated persons be tested more frequently than the vaccinated? 4. If test results are delayed, how will that affect the spread? 5. How do test false negative rates affect the overall efficacy of testing programs? 6. How do constraints on testing resources impact the overall efficacy of testing programs? 7. How does the patient’s failure to recognize COVID symptoms and quarantine affect the spread? 8. What level of vaccination coverage is needed to suppress the epidemic? 9. What is the risk of a large outbreak (probability exceeding x infections)? 10. What is the cost effectiveness of interventions (dollars per avoided infection)? This report describes the structure of a discrete event simulation model that provides actionable information to address these questions. Parameter inputs and results of analyses have been reported in briefings provided to LLNL management and are not discussed here.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Glucuronidase Function in Clinical Samples

The purpose of this CRADA is to expand upon the work previously performed through CRADA No. PNNL/381. As explained in the previous CRADA, Glucuronidase enzymes are important for contributing to enterohepatic recycling of numerous therapeutic drug compounds, resulting in impaired or prolonged drug activity. Further, other pathways within the gut, such as bile acid metabolism through the action of bile salt hydrolase enzymes (BSH), have shown to impact both the development of colon cancers and impact recovery. Adapting the activity-based protein profiling (ABPP) technologies developed at PNNL to a microtiter plate-based chemical probe assay was the first step in demonstrating the clinical usability of the technology. With assay proof-of-concept complete through CRADA No. PNNL/381, clinical cohort testing using the developed assay is the next step towards commercialization of this technology. Some chemotherapeutic agents are mediated by gut-produced microbiota through enterohepatic circulation. For example, irinotecan, the first line treatment for many colon and other cancers, can be recycled into a patient’s system through gut microbiota produced glucuronidase enzymes. A significant percentage of patients subjected to irinotecan treatment experience dose-limiting diarrhea and gastric distress that limits treatment options and delays effective intervention. Relatedly, bile salt hydrolases modify ratios of bile acids in the gut, which alter nutrient and pharmaceutical uptake by the intestines and impact patient response to treatment. Coupled together these gut-mediated disorders can significantly decrease patient outcomes. In this project, we propose to investigate a clinical cohort of samples from colon cancer patients to better understand gut microbiome activities surrounding microbiota produced glucuronidases to aid clinician decisions and enhance therapeutic intervention. Our project will measure glucuronidase activity of individual patients and compare this activity to a variety of factors, including patient medical history, treatment response, and overall outcomes. Data will be compared with metagenomic, metabolomic, and proteomic analyses to fully defined the entire gut microbiome space and correlate results with the glucuronidase activity. Resultant analysis is expected to provide actionable information to direct decision making towards therapeutic intervention.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗

DOE OSTI2025

Case Report: Differential diagnosis of hematuria in the emergency department: emphasizing double J stent-inferior vena cava fistula

Introduction Hematuria, a common clinical indicator of genitourinary tract pathology, arises from diverse etiologies including calculi, infections, malignancies, trauma, and iatrogenic causes. Initial evaluation requires hemodynamic assessment, identification of underlying causes, and urinary drainage optimization. This report highlights a rare case of iatrogenic hematuria secondary to double-J stent migration into the inferior vena cava. Case presentation A Chinese male presented with acute left flank pain and gross hematuria persisting for 4 h. Diagnostic imaging revealed a left ureteral stone, prompting double-J stent placement at a local hospital. Despite intervention, hematuria worsened, necessitating abdominal CT. Imaging identified proximal migration of the left double-J stent into the inferior vena cava, with no evidence of vascular injury. Due to concerns regarding inadequate drainage and infection risk, conservative management without catheter clamping was initiated prior to referral. Definitive treatment involved ureteroscopic stent removal under direct visualization at our institution, resulting in rapid symptom resolution. Conclusion This case emphasizes three critical clinical insights: (1) Persistent postoperative hematuria warrants consideration of iatrogenic causes, particularly following urologic device placement. (2) Imaging modalities, especially CT, are indispensable for detecting atypical stent migration. (3) Comprehensive history-taking must include prior urologic interventions to guide differential diagnosis. While double-J stent migration into major vessels remains exceptionally rare, its recognition prevents delayed management of potentially life-threatening complications. Clinicians should maintain heightened vigilance for device-related hematuria in patients with refractory symptoms post-procedurally, ensuring prompt imaging evaluation and multidisciplinary intervention when indicated.

Qi, Wenqi↗

DOE OSTI2022

Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

CTRL-STEER: Closed-Loop Neuron Activation Control in Vision-Language-Action Models

Vision-Language-Action (VLA) models enable test-time behavioral steering via neuron-level interventions, but existing methods use fixed strengths and operate in open loop. This static modulation fails under evolving task dynamics, leading to overcorrection, oscillations, and reduced task success—especially for temporal attributes like speed. We propose CTRL-STEER, a control-theoretic framework that casts activation steering as closed-loop feedback with adaptive, time-varying interventions. Instead of assuming neurons encode temporal concepts, we steer along motion-aligned residual directions and regulate intervention magnitude via feedback. We instantiate this with both PID and reinforcement learning controllers that jointly optimize concept adherence and task success. Experiments on fine-tuned OpenVLA policies across four LIBERO suites show improved stability and a better steering–success trade-off over fixed-coefficient baselines, without retraining the base model.

Babu, Abhijith [Florida International University, ↗

DOE OSTI2024

Can we mitigate tropical cyclone formation using aerosols? A review of cyclogenesis and aerosol effects as a theoretical basis

Tropical cyclogenesis is a complex phenomenon, involving processes across multiple scales, with various theories proposed to explain its mechanisms. This paper provides an up-to-date summary of the established physical mechanisms and controlling factors of cyclogenesis. Understanding the nature of tropical cyclone formation is necessary to improve tropical cyclone forecasts and inform tropical cyclone mitigation strategies targeting early-stage intervention. Despite the disparities among theories, the critical role of persistent, intensified convection in tropical cyclone initiation is universally acknowledged. Therefore, our hypothesis is that interrupting convective development using aerosol injection is a potential strategy for mitigating tropical cyclone formation. Targetted injection of coarse and fine aerosols at the formation stage are two proposed potential approaches for mitigating tropical cyclones. These methods have completely different microphysical effects but each may ultimately interfere with the formation of the nascent cyclone. In conclusion, these potential interventions open new areas of further research, which are important and necessary to establish a solid scientific foundation for cyclogenesis mitigation.

Tropical cyclone formation↗

DOE OSTI2026

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗

DOE OSTI2020

Investigating the interconnectedness of active transportation and public transit usage as a primer for Mobility-as-a-Service adoption and deployment

With the advent of Mobility-as-a-Service packages to reduce car usage and (by extension) greenhouse gas emissions, it is crucial that researchers and practitioners consider mutual determinants and outcomes that link the adoption of multiple alternative modes. This study therefore investigates the joint usage of active travel (walking, cycling, bike-sharing) and public transit (bus, rail) modes with respect to personal and situational contexts. Online survey data (n = 826) were collected across six Midwestern U.S. states using Amazon MTurk. Respondents indicated their average weekly usage of eight travel modes across three trip purposes so that multimodality could be assessed. Several psychological constructs were extracted via (a) the stages of change framework, used to indicate willingness to adopt new behavior, and (b) confirmatory factor analysis conducted on Likert scales rooted in theories of community, identity, norms, personality, and well-being. A multiple-indicators multiple-causes structural equation model is then employed to investigate the process of adopting a modality style that incorporates active and transit modes. The model confirms that compatible physical and social contexts, as well as navigational skills and openness to learning, are key primers of multimodalism. However, a path juncture stemming from neighborhood support for mobility innovation illustrates a potential polarity in outcomes between individuals and communities. In addition, the stage of active mobility adoption is linked to identity and norm activation, offering further guidance on what influences readiness for change. The seamless integration of mobility services is critical to matching the convenience and comfort of the private vehicle; understanding potential pathways to sustainable mobility, though, requires analyses and interventions that are driven by well-being outcomes and grounded in rigorous psychological frameworks. Here, the research findings offer practical guidance for identifying intervention opportunities to be linked with MaaS enrollment while demonstrating the need to illuminate how mobility might relate to social cohesion, identity expression, and various sources of satisfaction.

42 ENGINEERING↗

DOE OSTI2024

Cost effectiveness of preemptive school closures to mitigate pandemic influenza outbreaks of differing severity in the United States

Background: Nonpharmaceutical interventions (NPIs) may be considered as part of national pandemic preparedness as a first line defense against influenza pandemics. Preemptive school closures (PSCs) are an NPI reserved for severe pandemics and are highly effective in slowing influenza spread but have unintended consequences. Methods: We used results of simulated PSC impacts for a 1957-like pandemic (i.e., an influenza pandemic with a high case fatality rate) to estimate population health impacts and quantify PSC costs at the national level using three geographical scales, four closure durations, and three dismissal decision criteria (i.e., the number of cases detected to trigger closures). At the Chicago regional level, we also used results from simulated 1957-like, 1968-like, and 2009-like pandemics. Our net estimated economic impacts resulted from educational productivity costs plus loss of income associated with providing childcare during closures after netting out productivity gains from averted influenza illness based on the number of cases and deaths for each mitigation strategy. Results: For the 1957-like, national-level model, estimated net PSC costs and averted cases ranged from $\$7.5$ billion (2016 USD) averting 14.5 million cases for two-week, community-level closures to $\$97$ billion averting 47 million cases for 12-week, county-level closures. We found that 2-week school-by-school PSCs had the lowest cost per discounted life-year gained compared to county-wide or school district–wide closures for both the national and Chicago regional-level analyses of all pandemics. The feasibility of spatiotemporally precise triggering is questionable for most locales. Theoretically, this would be an attractive early option to allow more time to assess transmissibility and severity of a novel influenza virus. However, we also found that county-wide PSCs of longer durations (8 to 12 weeks) could avert the most cases (31–47 million) and deaths (105,000–156,000); however, the net cost would be considerably greater ($\$88$-$\$103$ billion net of averted illness costs) for the national-level, 1957-like analysis. Conclusions: We found that the net costs per death averted ($\$180,000$-$\$4.2$ million) for the national-level, 1957-like scenarios were generally less than the range of values recommended for regulatory impact analyses ($\$4.6$ to 15.0 million). This suggests that the economic benefits of national-level PSC strategies could exceed the costs of these interventions during future pandemics with highly transmissible strains with high case fatality rates. In contrast, the PSC outcomes for regional models of the 1968-like and 2009-like pandemics were less likely to be cost effective; more targeted and shorter duration closures would be recommended for these pandemics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Ultra-Sharp Nanowire Arrays Natively Permeate, Record, and Stimulate Intracellular Activity in Neuronal and Cardiac Networks

Intracellular access with high spatiotemporal resolution can enhance the understanding of how neurons or cardiomyocytes regulate and orchestrate network activity and how this activity can be affected with pharmacology or other interventional modalities. Nanoscale devices often employ electroporation to transiently permeate the cell membrane and record intracellular potentials, which tend to decrease rapidly with time. Here, one reports innovative scalable, vertical, ultrasharp nanowire arrays that are individually addressable to enable long-term, native recordings of intracellular potentials. One reports electrophysiological recordings that are indicative of intracellular access from 3D tissue-like networks of neurons and cardiomyocytes across recording days and that do not decrease to extracellular amplitudes for the duration of the recording of several minutes. The findings are validated with cross-sectional microscopy, pharmacology, and electrical interventions. The experiments and simulations demonstrate that the individual electrical addressability of nanowires is necessary for high-fidelity intracellular electrophysiological recordings. This work advances the understanding of and control over high-quality multichannel intracellular recordings and paves the way toward predictive, high-throughput, and low-cost electrophysiological drug screening platforms.

36 MATERIALS SCIENCE↗