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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Conceptual Model to Identify Intent to Use Chemical-Biological Weapons

This paper describes a conceptual model to identify and interrelate indicators of intent of non-state actors to use chemical or biological weapons. The model expands on earlier efforts to understand intent to use weapons of mass destruction by building upon well-researched theories of intent and behavior and focusing on a sub-set of weapons of mass destruction (WMD) to account for the distinct challenges of employing different types of WMD in violent acts. The conceptual model is presented as a first, critical step in developing a computational model for assessing the potential for groups to use chemical or biological weapons.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2016

Chapter 32: A Global Survey of Stakeholder Views and Experiences for Systems Needed to Effectively and Efficiently Govern Sustainability of Bioenergy

The increased international trade led to growing concerns over sustainability of biofuels and a variety of governance systems has emerged to regulate the bioenergy sector for maximization of the benefits and minimization of the possible negative impacts. The general concept of governance is used in different ways. But in this chapter it is used in the broad sense of governance processes undertaken by governments, market actors, voluntary organizations or networks. This concept of governance recognizes the interdependence of the public, market-based and voluntary governing processes, and the relationships that may exist between them. A survey was designed with the objective of analyzing stakeholders' views, experiences, and ideas in relation to the governance challenges. The survey revealed a broad support for existing and new co-regulation among stakeholders, but also that low share of certified land is seen as a challenge for both forestry and agriculture.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Strategic supply system design – a holistic evaluation of operational and production cost for a biorefinery supply chain

Abstract Pioneer cellulosic biorefineries across the United States rely on a conventional feedstock supply system based on one‐year contracts with local growers, who harvest, locally store, and deliver feedstock in low‐density format to the conversion facility. While the conventional system is designed for high biomass yield areas, pilot scale operations have experienced feedstock supply shortages and price volatilities due to reduced harvests and competition from other industries. Regional supply dependency and the inability to actively manage feedstock stability and quality, provide operational risks to the biorefinery, which translate into higher investment risk. The advanced feedstock supply system based on a network of depots can mitigate many of these risks and enable wider supply system benefits. This paper compares the two concepts from a system‐level perspective beyond mere logistic costs. It shows that while processing operations at the depot increase feedstock supply costs initially, they enable wider system benefits including supply risk reduction (leading to lower interest rates on loans), industry scale‐up, conversion yield improvements, and reduced handling equipment and storage costs at the biorefinery. When translating these benefits into cost reductions per liter of gasoline equivalent ( LGE ), we find that total cost reductions between –$0.46 to –$0.21 per LGE for biochemical and –$0.32 to –$0.12 per LGE for thermochemical conversion pathways are possible. Naturally, these system level benefits will differ between individual actors along the feedstock supply chain. Further research is required with respect to depot sizing, location, and ownership structures. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefining published by Society of Industrial Chemistry and John Wiley & Sons Ltd.

09 BIOMASS FUELS↗
DOE OSTI2017

Cities and “budget-based” management of the energy-water-climate nexus: Case studies in transportation policy, infrastructure systems, and urban utility risk management

This article reviews city case studies to inform a framework for developing urban infrastructure design standards and policy instruments that together aim to pursue energy efficiency and greenhouse gas mitigation through city carbon budgets and water use efficiency and climate risk adaptation through city water budgets. Here, this article also proposes combining carbon and water budgeting at the city-scale for achieving successful coupled city carbon and water budget (CCCWB) programs. Under a CCCWB program, key actors including local governments, infrastructure designers/operators, and households would be assigned a GHG emissions and water 'budget' and be required by state or federal levels to keep within this budget through the use of flexibility mechanisms, incentive programs, and sanctions. Multiple incentives and cross-scale governance arrangements would be tied to energy-water systems integration, resource-efficient transportation and infrastructure development, and effective monitoring and management of energy use, emissions, climate risks to, and security of energy-water-transport-food and other critical systems. As a first step to promote strategies for CCCWB development, we systematically review approaches of and shortcomings to existing budget-based programs in the UK and US, and suggest improvements in three areas: measurement, modeling effectiveness of interventions for staying within a budget, and governance. To date, the majority of climate action or sustainability plans by cities, while mentioning climate impacts as a premise for the plan, do not address these impacts in the plan. They focus primarily on GHG mitigation while ignoring resource depletion challenges and energy-climate-water linkages, whereby water supplies can begin to limit energy production and energy shifts to mitigate climate change can limit water availability. Coupled carbon-water budget plans, programs, and policies - described in this study- may address these concerns as well as the emerging trends that will exacerbate these problems - e.g., including population growth, climatic changes, and emerging policy choices that are not coordinated. Cities and 'Budget-Based' Management of the Energy-Water-Climate Nexus: Case Studies to Inform Strategy for Integrated Performance- and Incentive-Based Design and Policy Instruments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2011

Technosocial Predictive Analytics for Illicit Nuclear Trafficking

Illicit nuclear trafficking networks are a national security threat. These networks can directly lead to nuclear proliferation, as state or non-state actors attempt to identify and acquire nuclear weapons-related expertise, technologies, components, and materials. The ability to characterize and anticipate the key nodes, transit routes, and exchange mechanisms associated with these networks is essential to influence, disrupt, interdict or destroy the function of the networks and their processes. The complexities inherent to the characterization and anticipation of illicit nuclear trafficking networks requires that a variety of modeling and knowledge technologies be jointly harnessed to construct an effective analytical and decision making workflow in which specific case studies can be built in reasonable time and with realistic effort. In this paper, we explore a solution to this challenge that integrates evidentiary and dynamic modeling with knowledge management and analytical gaming, and demonstrate its application to a geopolitical region at risk.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2018

Transforming Dermatologic Imaging for the Digital Era: Metadata and Standards

Imaging is increasingly being used in dermatology for documentation, diagnosis, and management of cutaneous disease. The lack of standards for dermatologic imaging is an impediment to clinical uptake. Standardization can occur in image acquisition, terminology, interoperability, and metadata. This paper presents the International Skin Imaging Collaboration position on standardization of metadata for dermatologic imaging. Metadata is essential to ensure that dermatologic images are properly managed and interpreted. There are two standards-based approaches to recording and storing metadata in dermatologic imaging. The first uses standard consumer image file formats, and the second is the file format and metadata model developed for the Digital Imaging and Communication in Medicine (DICOM) standard. DICOM would appear to provide an advantage over using consumer image file formats for metadata as it includes all the patient, study, and technical metadata necessary to use images clinically. Whereas, consumer image file formats only include technical metadata and need to be used in conjunction with another actor—for example, an electronic medical record—to supply the patient and study metadata. The use of DICOM may have some ancillary benefits in dermatologic imaging including leveraging DICOM network and workflow services, interoperability of images and metadata, leveraging existing enterprise imaging infrastructure, greater patient safety, and better compliance to legislative requirements for image retention.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Coordinative Entities: Forms of Organizing in Data Intensive Science

Scientific collaboration is a long-standing subject of CSCW scholarship that typically focuses on the development and use of computing systems to facilitate research. The research presented in this article investigates the sociality of science by identifying and describing particular, common forms of organizing that researchers in four different scientific realms employ to conduct work in both local contexts and as part of distributed, global projects. This paper introduces five prototypical forms of organizing we categorize as coordinative entities: the Principal Group, Intermittent Exchange, Sustained Aggregation, Federation, and Facility Organization. Coordinative entities as a categorization help specify, articulate, compare, and trace overlapping and evolving arrangements scientists use to facilitate data intensive research. We use this typology to unpack complexities of data intensive scientific collaboration in four cases, showing how scientists invoke different coordinative entities across three types of research activities: data collection, processing, and analysis. Finally, our contribution scrutinizes the sociality of scientific work to illustrate how these actors engage in relational work within and among diverse, dispersed forms of organizing across project, funding, and disciplinary boundaries.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2026

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗
DOE OSTI2022

Aggregation in bottom-up vulnerability assessments and equity implications: The case of Jordanian households’ water supply

Bottom-up methods for water resources modeling rely on acceptability thresholds to find, through a response surface, which deeply uncertain futures lead to system failure. They commonly treat water users as aggregate actors, which may preclude analysis of the equity impacts of interventions. This paper explores how aggregation choices for large groups of water users lead to different policy recommendations in response surface assessments. Herein, two aggregation methods with varying parameters are considered: percentile satisfaction targets and generalized mean. A 2-dimensional stress-test assessment across groundwater availability and population is applied to household water supply in Jordan. The study compares six different policies covering supply enhancement and rebalancing, using a country-wide multi-agent model that characterizes households across socioeconomic strata. For different aggregation levels, policies are ordered by their associated robustness index. Results show that aggregation choices may modify response surfaces as much as policy changes and strongly determine policy preference. Modifying allocation rules can substantially reduce the disparity in household vulnerability. Preferences defined by aggregation intervals provide a finer understanding of trade-offs among water users and may improve deliberation over equity under deep uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Programmable intrusion detection for distributed energy resources in cyber–physical networked microgrids

We present a programmable intrusion detection method is presented to identify the malicious attacks to distributed energy resources (DERs) in the cyber-physical networked microgrids. The proposed method injects small programmable signals into the system and uses the response to identify abnormal conditions. Because of the low or even zero inertia induced by integrations of DER power-electronic-interfaces, microgrids have very limited resilience capability; and thus, being sensitive to attacks. One microgrid's malfunction caused by attacks can easily propagate to its neighboring systems when several microgrids are connected, leading to catastrophic electricity supply failures. Through the presented method, malicious intrusions can be effectively detected, located, and defended for securing microgrids. Theoretical derivations are provided to define the programmable detection rules. The detection rule is easy and flexible to update, making it difficult for attack actors to gain the knowledge of the detection rules, in order to avoid being detected. Numerical results on a cyber-physical networked microgrids system show that the proposed method is effective and efficient in precisely locating intrusion attacks to the microgrids system.

42 ENGINEERING↗
DOE OSTI2022

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗
DOE OSTI2023

Online transfer learning strategy for enhancing the scalability and deployment of deep reinforcement learning control in smart buildings

In recent years, advanced control strategies based on Deep Reinforcement Learning (DRL) proved to be effective in optimizing the management of integrated energy systems in buildings, reducing energy costs and improving indoor comfort conditions when compared to traditional reactive controllers. However, the scalability and implementation of DRL controllers are still limited since they require a considerable amount of time before converging to a near-optimal solution. This issue is currently addressed in literature through the offline pre-training of the DRL agent. However this solution results in two main critical issues: (1) the need to develop a building surrogate model to perform the training task, and (2) the need to perform a fine-tuning process over several training episodes to obtain a near-optimal control policy. In this context, this paper introduces an Online Transfer Learning (OTL) strategy that exploits two knowledge-sharing techniques, weight-initialization and imitation learning, to transfer a DRL control policy from a source office building to various target buildings in a simulation environment coupling EnergyPlus and Python. A DRL controller based on discrete Soft Actor–Critic (SAC) is trained on the source building to manage the operation of a cooling system consisting of a chiller and a thermal storage. Several target buildings are defined to benchmark the performance of the OTL strategy with that of a Rule-Based Controller (RBC) and two DRL-based control strategies, deployed in offline and online fashion. The strategy adopted for OTL emulates the real world implementation with a simulation process by implementing the transferred DRL agent for a single episode in the target buildings. Target buildings have the same geometrical features and are served by the same energy system as the source building, but differ in terms of weather conditions, electricity price schedules, occupancy patterns, and building envelope efficiency levels. The results show that the OTL strategy can reduce the cumulated sum of temperature violations on average by 50% and 80% respectively when compared to RBC and online DRL while enhancing the energy system operation with electricity cost savings ranging between 20% and 40%. Furthermore, the OTL agent performs slightly worse than the offline DRL controller but it does not require any modeling effort and can be implemented directly on target buildings emulating a real-world implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Designing reinforcement learning algorithms for building HVAC control: From experimental observation to simulation comparisons

Advanced supervisory-level control with reinforcement learning (RL) is regarded as a promising solution for HVAC systems to minimize energy consumption while maintaining thermal comfort and indoor air quality. However, most RL applications were conducted in the simulation environment rather than real-world HVAC systems. This paper developed a value-based RL controller termed Deep Q-Network (DQN) for a typical central HVAC system and evaluated its performance in a building test facility. By comparing DQN with a rule-based controller, the study not only demonstrated the cases where DQN could properly maintain indoor comfort but also discussed possible reasons why DQN failed in some other situations. Recognizing the limitations of value-based RL algorithms from the experimental tests, a simulation study was conducted to compare DQN with an alternative RL approach, an actor–critic algorithm termed Deep Deterministic Policy Gradient (DDPG). In scenarios with a relatively large action space, DDPG outperformed DQN by requiring fewer computational resources and achieving better thermal comfort, lower energy consumption, and more stable control actions. The findings suggest that the ability of DDPG to handle continuous control variables more effectively allows for faster convergence in training and more precise control in practice, which enhances the overall efficiency and reliability of the HVAC system.

Guo, Fangzhou↗
DOE OSTI2012

ET-1 deletion from endothelial cells protects the kidney during the extension phase of ischemia/reperfusion injury

Highlights: Black-Right-Pointing-Pointer Ischemia/reperfusion injury (IRI) induced increased endothelin-1 (ET-1) expression. Black-Right-Pointing-Pointer IRI was accompanied by tubular injury and remodeling of renal arteries. Black-Right-Pointing-Pointer IRI increased oxidative stress and inflammation. Black-Right-Pointing-Pointer Genetic suppression of ET-1 in endothelial cells attenuates IRI in the kidney. Black-Right-Pointing-Pointer The mechanisms include the inhibition of oxidative stress and inflammation. -- Abstract: Background: The prognosis of patients after acute kidney injury (AKI) is poor and treatment is limited. AKI is mainly caused by renal ischemia/reperfusion injury (IRI). During the extension phase of IRI, endothelial damage may participate in ischemia and inflammation. Endothelin-1 (ET-1) which is mostly secreted by endothelial cells is an important actor of IRI, particularly through its strong vasoconstrictive properties. We aimed to analyze the specific role of ET-1 from the endothelial cells in AKI. Methods: We used mice lacking ET-1 in the vascular endothelial cells (VEETKO). We induced IRI in VEETKO mice and wild type controls by clamping both kidneys for 30 min. Sham operated mice were used as controls. Mice were sacrificed one day after IRI in order to investigate the extension phase of IRI. Kidney function was assessed based on serum creatinine concentration. Levels of expression of ET-1, its receptor ET{sub A}, protein kinase C, eNOS, E-Cadherin and inflammation markers were evaluated by real time PCR or western blot. Tubular injury was scored on periodic acid Schiff stained kidney preparations. Lumen and wall area of small intrarenal arteries were measured on kidney slices stained for alpha smooth muscle cell actin. Oxidative stress, macrophage infiltration and cell proliferation was evaluated on slices stained for 8-hydroxy-2 Prime -deoxyguanosine, F4/80 and PCNA, respectively. Results: IRI induced kidney failure and increased ET-1 and ET{sub A} receptor expression. This was accompanied by tubular injury, wall thickening and reduction of lumen area/wall area ratio of small renal arteries, increased oxidative stress and inflammation. These parameters were attenuated in VEETKO mice. Conclusion: Our results suggest that suppression of ET-1 from the endothelial cells attenuates IRI kidney injury. Blocking ET-1 effects may represent a therapeutic strategy in the management of AKI.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Induction of mitochondrial biogenesis and respiration is associated with mTOR regulation in hepatocytes of rats treated with the pan-PPAR activator tetradecylthioacetic acid (TTA)

Highlights: Black-Right-Pointing-Pointer We investigated mechanisms of mitochondrial regulation in rat hepatocytes. Black-Right-Pointing-Pointer Tetradecylthioacetic acid (TTA) was employed to activate mitochondrial oxidation. Black-Right-Pointing-Pointer Mitochondrial biogenesis and respiration were induced. Black-Right-Pointing-Pointer It was confirmed that PPAR target genes were induced. Black-Right-Pointing-Pointer The mechanism involved activation mTOR. -- Abstract: The hypolipidemic effect of peroxisome proliferator-activated receptor (PPAR) activators has been explained by increasing mitochondrial fatty acid oxidation, as observed in livers of rats treated with the pan-PPAR activator tetradecylthioacetic acid (TTA). PPAR-activation does, however, not fully explain the metabolic adaptations observed in hepatocytes after treatment with TTA. We therefore characterized the mitochondrial effects, and linked this to signalling by the metabolic sensor, the mammalian target of rapamycin (mTOR). In hepatocytes isolated from TTA-treated rats, the changes in cellular content and morphology were consistent with hypertrophy. This was associated with induction of multiple mitochondrial biomarkers, including mitochondrial DNA, citrate synthase and mRNAs of mitochondrial proteins. Transcription analysis further confirmed activation of PPAR{alpha}-associated genes, in addition to genes related to mitochondrial biogenesis and function. Analysis of mitochondrial respiration revealed that the capacity of both electron transport and oxidative phosphorylation were increased. These effects coincided with activation of the stress related factor, ERK1/2, and mTOR. The protein level and phosphorylation of the downstream mTOR actors eIF4G and 4E-BP1 were induced. In summary, TTA increases mitochondrial respiration by inducing hypertrophy and mitochondrial biogenesis in rat hepatocytes, via adaptive regulation of PPARs as well as mTOR.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

DNA binding of the p21 repressor ZBTB2 is inhibited by cytosine hydroxymethylation

Highlights: • 5-hmC epigenetic modification is measurable in HeLa, SH-SY5Y and UT7-MPL cell lines. • ZBTB2 binds to DNA probes containing 5-mC but not to sequences containing 5-hmC. • This differential binding is verified with DNA sequences involved in p21 regulation. - Abstract: Recent studies have demonstrated that the modified base 5-hydroxymethylcytosine (5-hmC) is detectable at various rates in DNA extracted from human tissues. This oxidative product of 5-methylcytosine (5-mC) constitutes a new and important actor of epigenetic mechanisms. We designed a DNA pull down assay to trap and identify nuclear proteins bound to 5-hmC and/or 5-mC. We applied this strategy to three cancerous cell lines (HeLa, SH-SY5Y and UT7-MPL) in which we also measured 5-mC and 5-hmC levels by HPLC-MS/MS. We found that the putative oncoprotein Zinc finger and BTB domain-containing protein 2 (ZBTB2) is associated with methylated DNA sequences and that this interaction is inhibited by the presence of 5-hmC replacing 5-mC. As published data mention ZBTB2 recognition of p21 regulating sequences, we verified that this sequence specific binding was also alleviated by 5-hmC. ZBTB2 being considered as a multifunctional cell proliferation activator, notably through p21 repression, this work points out new epigenetic processes potentially involved in carcinogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Nuclear AMPK regulated CARM1 stabilization impacts autophagy in aged heart

Senescence-associated autophagy downregulation leads to cardiomyocyte dysfunction. Coactivator-associated arginine methyltransferase 1 (CARM1) participates in many cellular processes, including autophagy in mammals. However, the effect of CARM1 in aging-related cardiac autophagy decline remains undefined. Moreover, AMP-activated protein kinase (AMPK) is a key regulator in metabolism and autophagy, however, the role of nuclear AMPK in autophagy outcome in aged hearts still unclear. Hers we identify the correlation between nuclear AMPK and CARM1 in aging heart. We found that fasting could promote autophagy in young hearts but not in aged hearts. The CARM1 stabilization is markedly decrease in aged hearts, which impaired nucleus TFEB-CARM1 complex and autophagy flux. Further, S-phase kinase-associated protein 2(SKP2), responsible for CARM1 degradation, was increased in aged hearts. We further validated that AMPK dependent FoxO3 phosphorylation was markedly reduced in nucleus, the decreased nuclear AMPK-FoxO3 activity fails to suppress SKP2-E3 ubiquitin ligase. This loss of repression leads to The CARM1 level and autophagy in aged hearts could be restored through AMPK activation. Taken together, AMPK deficiency results in nuclear CARM1 decrease mediated in part by SKP2, contributing to autophagy dysfunction in aged hearts. Our results identified nuclear AMPK controlled CARM1 stabilization as a new actor that regulates cardiac autophagy. - Highlights: • AMPK-dependent CARM1 stabilization is an important nuclear mechanism in cardiac autophagy. • AMPK deficiency lead to SKP2-mediated decrease in CARM1. • AMPK–SKP2–CARM1 in the regulation of autophagy dysfunction in aged heart.

60 APPLIED LIFE SCIENCES↗