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DOE OSTI2025

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Cooperative Automated Cohort Driving on Connected Infrastructure, Arterial Roadways, and Highways: Final Project Demonstration and System-of-Systems Model Correlation

This project seeks to synergize vehicle automated driving and connectivity data to improve mobility and energy efficiency of groups of mixed vehicles operating in close proximity (vehicle cohort) on various infrastructure. A custom cellular communication network links vehicles operating as a cohort with infrastructure to a centralized system-of-systems digital twin with an AI-based optimal behavior planner. The data contained in this set are from final testing and technology demonstrations to U.S. Department of Energy staff at the American Center for Mobility. The data contain single-lane, single-light scenarios; multi-lane, multi-light arterial scenarios; and limited-access highway scenarios. All test cases were derived from simulations and replicated on the test track. The project employed two and four light-duty vehicles with connectivity and drive automation for the testing. The baseline scenario without connectivity was run under the control of the system-of-systems centralized planner but operating each vehicle with an intelligent driver model controlling the velocity, lane utilization, and vehicle gap. This was to ensure the highest compatibility with the simulation in terms of dynamic behavior. The connected cohort case utilized AI optimization to perform coordinated and cooperative control for energy, as well as safe, comfortable behavior for the cohort. The dataset is appropriately named with unconnected and connected designations, with comparisons sharing the same run index number. The included PowerPoint and PDF files describe the test setup and provide an overview of results from the project. ![image](de-EE0009209_March_2023_Data_Arterial_Scenario_Results.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

The POINTER Imaging baseline cohort: Associations between multimodal neuroimaging biomarkers, cardiovascular health, and cognition

Abstract INTRODUCTION The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is evaluating lifestyle interventions in older adults at risk for cognitive decline and dementia. Here we characterize the baseline data set of the POINTER Imaging ancillary study. METHODS Participants underwent health and cognitive assessments and neuroimaging with multimodal positron emission tomography (PET) (beta‐amyloid [Aβ] and tau) and magnetic resonance imaging (MRI). Framingham risk score (FRS) was used to quantify cardiovascular disease (CVD) risk. RESULTS A total of 1052 participants (31% from underrepresented ethnoracial groups) were enrolled. Compared to Aβ−, Aβ+ (29%) participants were older, had higher apolipoprotein E (APOE) ε4 carriage rate and white matter hyperintensity volume, and greater temporal tau. FRS was related to MRI measures, but not AD biomarkers. FRS and tau had independent effects on cognition. DISCUSSION In this heterogenous, at‐risk cohort, CVD risk was related to more abnormal brain structure and poorer cognition, representing a putative non‐AD (Alzheimer's disease) pathway to brain injury and cognitive decline. Highlights The U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) cohort is enriched for cardiovascular disease (CVD) and poor lifestyle POINTER Imaging collected multimodal neuroimaging data in this unique, at‐risk cohort Amyloid burden was related to age, apolipoprotein E (APOE) ε4 carriage, and measures of disease progression Associations between amyloid and tau, and tau and cognition, were relatively weak CVD risk and tau pathology were independently related to memory

Neurosciences & Neurology↗

DOE OSTI2026

Eight Ways Agrivoltaics Installations Can Impact Communities: Insights from the Energy to Communities Peer-Learning Cohort

From July to December of 2024, the National Laboratory of the Rockies partnered with World Resources Institute to run a peer-learning cohort for local governments and community-based organizations on "Implementing an Agrivoltaics Project." This cohort effort, funded by the U.S. Department of Energy's Energy to Communities program, provided 15 organizations with expert presentations, peer-learning opportunities, and technical assistance related to agrivoltaics project development. Pulling from cohort discussions, this document shares a summary of the benefits that agrivoltaics projects can provide to surrounding communities.

14 SOLAR ENERGY↗

DOE OSTI2026

E2C Cohorts: Overview of Project Procurement, Performance Monitoring, and O&M [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Successful Energy Project Implementation" will explore common challenges in implementing energy projects and learn strategies to turn project plans into reality. Each participant will focus on a local energy project or priority as a cornerstone for their learning throughout the series. This presentation is focused on project performance, monitoring, and O&M. This workshop is on May 27.

14 SOLAR ENERGY↗

DOE OSTI2024

Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids

The National Renewable Energy Laboratory (NREL), with support from World Resources Institute (WRI), designed and led a six-month peer-learning cohort from January through July 2024 on "Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids" as part of the U.S Department of Energy's Clean Energy to Communities (nrel.gov/c2c) (C2C) program. Representatives from 15 municipalities, municipal utilities, colleges, and Tribes from across the United States participated in monthly workshops covering best practices for planning and deploying local resilience projects. This document shares key takeaways, lessons learned, and resources from the cohort including considerations for planning, proposing, designing, procuring, and funding microgrid projects for resilience.

C2C↗

DOE OSTI2024

Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort Evaluating and Prioritizing Municipal Buildings for Energy Efficiency and Decarbonization Investment

buildings↗

DOE OSTI2024

Lessons Learned from the Clean Energy to Communities (C2C) Peer-Learning Cohort Incorporating Community Priorities into Electric Vehicle Plans and Projects

The National Renewable Energy Laboratory (NREL), with support from World Resources Institute (WRI), designed and led a six-month peer-learning cohort from January through July 2024 on "Enhancing Resilience at Critical Facilities through Solar, Storage, and Microgrids" as part of the U.S Department of Energy's Clean Energy to Communities (nrel.gov/c2c) (C2C) program. Representatives from 15 municipalities, municipal utilities, colleges, and Tribes from across the United States participated in monthly workshops covering best practices for planning and deploying local resilience projects. This document shares key takeaways, lessons learned, and resources from the cohort including key steps that can be taken to help entities design effective community engagement processes around clean mobility.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

DOE OSTI2026

Lessons Learned from the Energy to Communities (E2C) Peer-Learning Cohort on Engaging with Electric Utilities for Successful Local Partnerships

NLR designed and led a six-month peer-learning cohort from July through December 2025 on “Engaging With Electric Utilities for Successful Local Partnerships” as part of the U.S. Department of Energy’s Energy to Communities (E2C) program. Representatives from 15 local and regional governments from across the United States participated in monthly workshops covering best practices for engaging with their utilities to advance their own energy goals. This document shares key takeaways, lessons learned, and resources from the cohort that may be useful to local governments, regional governments, or Tribes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Cohort-based pan-cancer analysis and experimental studies reveal ISG15 gene as a novel biomarker for prognosis and immunotherapy efficacy prediction

Abstract ISG15, an interferon-stimulated ubiquitin-like protein, plays a multifaceted role in tumorigenesis and immune regulation. This study comprehensively evaluates ISG15 as a prognostic biomarker and predictor of immunotherapy response through pan-cancer bioinformatics analysis and experimental validation. By integrating multiomics data from TCGA, GEO, and clinical cohorts, we found that ISG15 is significantly overexpressed in multiple cancers and generally correlates with poor prognosis. Elevated ISG15 expression is associated with increased immune checkpoint gene expression, particularly PD-L1, and immune infiltration, notably M2-like tumor-associated macrophages. Immunohistochemistry and multiplexed immunofluorescence confirmed a strong positive correlation between ISG15, PD-L1, and M2-TAM infiltration in lung and gastric cancer samples. Functional analysis at the single-cell level revealed significant associations between ISG15 and tumor proliferation, angiogenesis, and immune suppression. Immunotherapy cohort analysis demonstrated that tumors with high ISG15 expression responded favorably to PD-L1 inhibitors but exhibited resistance to CTLA-4 blockade, findings further validated in lung cancer patients receiving anti-PD-1 therapy. These results suggest that ISG15 is a promising biomarker for prognosis and immunotherapy response prediction across cancers. Its integration into clinical decision-making may enhance personalized treatment strategies, improve immunotherapy outcomes, and provide new insights into the tumor immune microenvironment, cancer progression, and potential therapeutic targets for future drug development.

Immunology↗

DOE OSTI2025

Timing based clustering of childhood BMI trajectories reveals differential maturational patterns; Study in the Northern Finland Birth Cohorts 1966 and 1986

Children’s biological age does not always correspond to their chronological age. In the case of BMI trajectories, this can appear as phase variation, which can be seen as shift, stretch, or shrinking between trajectories. With maturation thought of as a process moving towards the final state - adult BMI, we assessed whether children can be divided into latent groups reflecting similar maturational age of BMI. The groups were characterised by early factors and time-related features of the trajectories. We used data from two general population birth cohort studies, Northern Finland Birth Cohorts 1966 and 1986 (NFBC1966 and NFBC1986). Height (n = 6329) and weight (n = 6568) measurements were interpolated in 34 shared time points using B-splines, and BMI values were calculated between 3 months to 16 years. Pairwise phase distances of 2999 females and 3163 males were used as a similarity measure in k-medoids clustering. We identified three clusters of trajectories in females and males (Type 1: females, n = 1566, males, n = 1669; Type 2: females, n = 1028, males, n = 973; Type 3: females, n = 405, males, n = 521). Similar distinct timing patterns were identified in males and females. The clusters did not differ by sex, or early growth determinants studied. Trajectory cluster Type 1 reflected to the shape of what is typically illustrated as the childhood BMI trajectory in literature. However, the other two have not been identified previously. Type 2 pattern was more common in the NFBC1966 suggesting a generational shift in BMI maturational patterns.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Risk of longer-term endocrine and metabolic conditions in the Deepwater Horizon Oil Spill Coast Guard cohort study – five years of follow-up

Abstract Introduction Long-term endocrine and metabolic health risks associated with oil spill cleanup exposures are largely unknown, despite the endocrine-disrupting potential of crude oil and oil dispersant constituents. We aimed to investigate risks of longer-term endocrine and metabolic conditions among U.S. Coast Guard (USCG) responders to the Deepwater Horizon (DWH) oil spill. Methods Our study population included all active duty DWH Oil Spill Coast Guard Cohort members ( N = 45,224). Self-reported spill exposures were ascertained from post-deployment surveys. Incident endocrine and metabolic outcomes were defined using International Classification of Diseases (9th Revision) diagnostic codes from military health encounter records up to 5.5 years post-DWH. Using Cox proportional hazards regression, we estimated adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for various incident endocrine and metabolic diagnoses (2010–2015, and separately during 2010–2012 and 2013–2015). Results The mean baseline age was 30 years (~ 77% white, ~ 86% male). Compared to non-responders ( n = 39,260), spill responders ( n = 5,964) had elevated risks for simple and unspecified goiter (aHR = 2.09, 95% CI: 1.29–3.38) and disorders of lipid metabolism (aHR = 1.09, 95% CI: 1.00–1.18), including its subcategory other and unspecified hyperlipidemia (aHR = 1.10, 95% CI: 1.01–1.21). The dysmetabolic syndrome X risk was elevated only during 2010–2012 (aHR = 2.07, 95% CI: 1.22–3.51). Responders reporting ever ( n = 1,068) vs. never ( n = 2,424) crude oil inhalation exposure had elevated risks for disorders of lipid metabolism (aHR = 1.24, 95% CI: 1.00–1.53), including its subcategory pure hypercholesterolemia (aHR = 1.71, 95% CI: 1.08–2.72), the overweight, obesity and other hyperalimentation subcategory of unspecified obesity (aHR = 1.52, 95% CI: 1.09–2.13), and abnormal weight gain (aHR = 2.60, 95% CI: 1.04–6.55). Risk estimates for endocrine/metabolic conditions were generally stronger among responders reporting exposure to both crude oil and dispersants (vs. neither) than among responders reporting only oil exposure (vs. neither). Conclusion In this large cohort of active duty USCG responders to the DWH disaster, oil spill cleanup exposures were associated with elevated risks for longer-term endocrine and metabolic conditions.

Denic-Roberts, Hristina↗

DOE OSTI2024

Clean Energy Cybersecurity Accelerator: Cohort 2 - Asimily Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator (TM) (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Data Center Cybersecurity, Supply Chain Risk Management, and Emerging Regulation Cohort Summary: Takeaways and Action Plans

This report summarizes the outcomes of the Data Center Cohort under the Department of Energy’s Technical Assistance for Digital Assurance (TADA) initiative, aimed at enhancing grid resilience through cybersecurity, supply chain risk management (SCRM), and Cyber-Informed Engineering (CIE). The cohort engaged 17 organizations across utilities, data center operators, vendors, and technology providers in three sessions combining presentations, discussions, and exercises. Key topics included AI-driven load behavior, cybersecurity vulnerabilities in UPS/BESS and cooling systems, governance gaps at utility–data center boundaries, and supply chain integrity. Five cross-cutting themes emerged: interconnection architecture vulnerabilities, fragmented governance, AI-driven stability risks, lack of regulatory frameworks, and long-term supply chain concerns. Actionable recommendations were developed, including implementing DMZ segmentation, formalizing vendor access agreements, designing AI workload limits, and advancing standards through NERC and state-level programs. These strategies aim to strengthen resilience, clarify responsibilities, and ensure secure integration of data centers into the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

E2C Cohort on Major Energy Disruptions in the Southeast: Trade-Offs and Feasibility of Energy Sector Investment for Community Resilience [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the tradeoffs and relative costs of different strategies to improve outcomes from these extreme events. The workshop is on May 21, 2026.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

E2C Successful Project Implementation Cohort: Overview of Solar, Microgrid and Resilience Project Development [Slides]

The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Successful Energy Project Implementation" will explore common challenges in implementing energy projects and learn strategies to turn project plans into reality. Each participant will focus on a local energy project or priority as a cornerstone for their learning throughout the series. This presentation overviews the basics of developing solar, microgrid and resilience projects with emphasis on understanding the project development process.

14 SOLAR ENERGY↗

DOE OSTI2026

E2C Cohorts: Implementation Funding Projects - Impact Summary [Slides]

From August 2024 to October 2025, 11 Clean Cities and Communities coalitions supported projects to advance transportation goals by gathering input from local stakeholders, and using the resulting insights to develop new plans and programs for local partners. This effort leveraged information and best practices shared during the 2024 E2C Cohort on Integrating Community Priorities into Electric Vehicle Plans and Projects. These coalitions supported partners across the country to develop plans for electric vehicle integration through one-on-one technical assistance and tailored local engagement. This deck summarizes the individual projects completed by coalitions, and the overall reach and impact of all of this program.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2026

Identification of drug repurposing candidates for amyotrophic lateral sclerosis using electronic health records: a retrospective cohort study

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with a life expectancy of only 3–5 years and few approved treatments. To identify drug repurposing candidates for the treatment of ALS, we analysed the electronic health records (EHRs) of a large cohort of military veterans with ALS. We analysed the EHRs of individuals in the US Veterans Health Administration (VHA) database who were diagnosed with ALS between Jan 1, 2009 and Dec 31, 2019 to assess medication effects. Individuals without recorded prescriptions after the date of diagnosis were excluded. Two sets of criteria were applied to ascertain exposure. Exposure criteria A were met if the dispense date or the end date of the medication was within 12 months of ALS diagnosis and the end date was at least 6 months after the dispense date. Exposure criteria B were met if there were at least two dispenses within 6 months before diagnosis and 12 months after diagnosis. Propensity score-matched control groups were generated on the basis of confounders included in the EHR, with methodology of potential outcomes used to infer treatment effects. The primary outcome was death. A standard Cox proportional hazards analysis was done to assess association with survival. Survival was defined as the time from diagnosis date recorded in the EHR to death reported in the Department for Veterans Affairs Vital Status File. Follow-up survival time was censored on Dec 31, 2020, for those alive on this date. Downstream protein targets of drugs with clinically significant effects were analysed using the protein–protein interaction networks-based algorithm PathFX. The EHRs of 11 003 individuals with ALS in the VHA database were appropriate for analysis. 162 medications with treatment groups of 30 or more individuals were identified. Among these 162 medications, 27 were associated with statistically significant changes (≥0·1) in the hazard ratio (HR) for death. 18 of the medications were associated with a reduced HR for death (prolonged survival), and nine were associated with an increased HR for death (reduced survival). Drugs associated with reduced HR included HMG-CoA reductase inhibitors (simvastatin, pravastatin, lovastatin, and atorvastatin), PDE5 inhibitors (vardenafil and sildenafil), and α-adrenergic antagonists (tamsulosin and terazosin). The medications associated with an increased HR were drugs used either in the management of clinical features of ALS associated with poor outcomes or in end-of-life care. PathFx analysis identified a complex of proteins interacting with several of the identified drugs. To our knowledge, this analysis is the largest EHR-based study for identifying drug repurposing candidates for ALS. We identified several drugs that warrant further assessment as therapeutic options in ALS, as well as a protein network complex that might serve as a therapeutic target for ALS.

Reimer, Richard J. [Stanford Univ., CA (United Sta↗