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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Co-orchestration of multiple instruments to uncover structure–property relationships in combinatorial libraries

The rapid growth of automated and autonomous instrumentation brings forth opportunities for the co-orchestration of multimodal tools that are equipped with multiple sequential detection methods or several characterization techniques to explore identical samples. This is exemplified by combinatorial libraries that can be explored in multiple locations via multiple tools simultaneously or downstream characterization in automated synthesis systems. In co-orchestration approaches, information gained in one modality should accelerate the discovery of other modalities. Correspondingly, an orchestrating agent should select the measurement modality based on the anticipated knowledge gain and measurement cost. Herein, we propose and implement a co-orchestration approach for conducting measurements with complex observables, such as spectra or images. The method relies on combining dimensionality reduction by variational autoencoders with representation learning for control over the latent space structure and integration into an iterative workflow via multi-task Gaussian Processes (GPs). This approach further allows for the native incorporation of the system's physics via a probabilistic model as a mean function of the GPs. We illustrate this method for different modes of piezoresponse force microscopy and micro-Raman spectroscopy on a combinatorial Sm-BiFeO3 library. However, the proposed framework is general and can be extended to multiple measurement modalities and arbitrary dimensionality of the measured signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Basic Energy Sciences Roundtable: Foundational Science to Accelerate Nuclear Energy Innovation

Energy security, availability, and reliability are among the greatest challenges facing the nation and the planet. An abundant potential source of energy resides in the fundamental atomic building blocks of the universe in the form of nuclear fission and fusion reactions. In fact, energy from nuclear fission currently provides the majority of the world’s zero-carbon electricity, and future fusion energy systems offer great promise; carbon-free nuclear energy technologies can be key to the world’s decarbonized energy future. Although contemporary fission systems use well-established technologies to supply safe and efficient baseload power, they could be more fuel efficient and less costly. Moving beyond massive light-water fission reactors to a variety of advanced nuclear systems—which will vary in size and operate in extremes of temperature, corrosivity, and other parameters—will place stringent conditions on materials and chemical systems. New demands will be placed on the coolants and solvents, the materials, and the monitoring tools used in these reactors. Fusion-based nuclear energy will require superior materials to withstand extremely high temperatures, plasma exposure, radiation damage, and implanted gases. The advantages associated with these new fission and fusion technologies will be realized only through continued advancements in the fundamental science underpinning our knowledge of the physics and chemistry of nuclear systems gained via improved experimental and computational methods. In July 2022, the U.S. Department of Energy’s Office of Basic Energy Sciences—in coordination with the Offices of Nuclear Energy, Fusion Energy Sciences, and Advanced Scientific Computing Research—held a virtual roundtable titled “Foundational Science to Accelerate Nuclear Energy Innovation” to discuss the scientific and technical barriers for advanced nuclear energy systems. Five priority research opportunities were identified to address these scientific and technical challenges and to accelerate progress toward the realization of next-generation fusion and fission energy systems. The foundational science gaps inhibiting the advancement of nuclear energy technologies are identified and tackled in five priority research opportunities. These opportunities pave the way to accelerate the development and ultimately the adoption of new nuclear energy systems. They include the fundamental aspects of ion-electron interactions; novel properties of next-generation coolants and solvents; interfacial dynamics, not only in solids, but in other aspects of nuclear reactors; novel operando and in situ monitoring and sensing; and artificial intelligence to accelerate condensed phases discovery. Building on the foundation established by previous Basic Energy Sciences workshops, these opportunities encompass recent advances in fundamental knowledge and focus on the experimental and computational methods needed to resolve major technical challenges for nuclear energy technologies. Through developing fundamental scientific insight as well as pushing the frontiers of modeling complex systems and probing the operation of materials and chemical systems in extreme environments, research motivated by the priorities identified here will further develop the promise, potential, and utilization of nuclear energy for a clean energy future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2003

Genesis Discovery Mission: Science Canister Processing at JSC

Genesis addresses questions about materials and processes involved in the origins of the solar system by providing precise knowledge of solar isotopic and elemental compositions. Solar wind ions are collected and returned to Earth for analyses. The spacecraft has two primary instruments to collect solar wind: a set of collector arrays each of which can deploy to sample different solar wind regimes, and a concentrator that is an electrostatic mirror to concentrate and focus low mass ions onto a 6 cm target. One of the key challenges to obtaining a good sample of solar wind, uncontaminated by terrestrial atoms, is to have clean collection surfaces in a clean sample canister and clean facilities to handle the samples for allocation and future reference. The Johnson Space Center (JSC) is responsible for contamination control for the mission, for ensuring the cleanliness of collection surfaces, and for providing a clean environment for handling of the samples. The level of cleanliness required is high; at the time of analysis (after sample return), the surface contamination by C, N, O must each be <10(exp 15) atoms/sq cm and for other elements the number of atoms/sq cm of each surface contaminant shall not exceed the estimated solar wind fluence of the species (varies by element between U at approx. 10(exp 4) atoms/sq cm to Fe, Si, Mg, and Ne at approx. 10(exp 12) atoms/sq cm).

Stansbery, E. K.↗
NASA NTRS1975

Mariner 9 - An instrument of dynamical science

We review and evaluate the contributions of Mariner 9 in improving our knowledge of the dynamical characteristics of Mars and its two satellites, Phobos and Deimos. Primary results include the discovery of the large gravitational and topographical bulge in the Tharsis region, the development of a detailed gravity model representable as coefficients in a spherical harmonic expansion, the development of a topographic model exhibiting a three kilometer displacement of the center of figure from the center of mass, and the determination of the size, shape and motion of Phobos and Deimos.

Jordan, J. F.↗
NASA NTRS2016

NASA's SPACE LAUNCH SYSTEM: Development and Progress

NASA is embarked on a new era of space exploration that will lead to new capabilities, new destinations, and new discoveries by both human and robotic explorers. Today, the International Space Station (ISS) and robotic probes are yielding knowledge that will help make this exploration possible. NASA is developing both the Orion crew vehicle and the Space Launch System (SLS) (Figure 1), that will carry out a series of increasingly challenging missions leading to human exploration of Mars. This paper will discuss the development and progress on the SLS. The SLS architecture was designed to be safe, affordable, and sustainable. The current configuration is the result of literally thousands of trade studies involving cost, performance, mission requirements, and other metrics. The initial configuration of SLS, designated Block 1, will launch a minimum of 70 metric tons (mT) (154,324 pounds) into low Earth orbit - significantly greater capability than any current launch vehicle. It is designed to evolve to a capability of 130 mT (286,601 pounds) through the use of upgraded main engines, advanced boosters, and a new upper stage. With more payload mass and volume capability than any existing rocket, SLS offers mission planners larger payloads, faster trip times, simpler design, shorter design cycles, and greater opportunity for mission success. Since the program was officially created in fall 2011, it has made significant progress toward launch readiness in 2018. Every major element of SLS continued to make significant progress in 2015. Engineers fired Qualification Motor 1 (QM-1) in March 2015 to test the 5-segment motor, including new insulation, joint, and propellant grain designs. More than 70 major components of test article and flight hardware for the Core Stage have been manufactured. Seven test firings have been completed with an RS-25 engine under SLS operating conditions. The test article for the Interim Cryogenic Propulsion Stage (ICPS) has also been completed. Major work continues in 2016 as the program continues both flight and development RS-25 engine testing, begins welding test article and flight core stage tanks, completes stage adapter manufacturing, and test fires the second booster qualification motor. This paper will discuss the program's key accomplishments to date and the challenging work ahead for what will be the world's most capable launch vehicle.

Honeycutt, John↗
NASA NTRS2022

Structural and chemical complexity of minerals: An update

The complexities of chemical composition and crystal structure are fundamental characteristics of minerals that have high relevance to the understanding of their stability, occurrence and evolution. This review summarises recent developments in the field of mineral complexity and outlines possible directions for its future elaboration. The database of structural and chemical complexity parameters of minerals is updated by H-correction of structures with unknown H positions and the inclusion of new data. The revised average complexity values (arithmetic means) for all minerals are 3.54(2) bits/atom and 345(10) bits/cell (based upon 4443 structure reports). The distributions of atomic information amounts, chemIG and strIG, versus the number of mineral species fit the normal modes, whereas the distributions of total complexities, chemIG,total and strIG,total, along with numbers of atoms per formula and per unit cell are log normal. The three most complex mineral species known today are ewingite, morrisonite and ilmajokite, all either discovered or structurally characterised within the last five years. The most important complexity-generating mechanisms in minerals are: (1) the presence of isolated large clusters; (2) the presence of large clusters linked together to form three-dimensional frameworks; (3) formation of complex three-dimensional modular frameworks; (4) formation of complex modular layers; (5) high hydration state in salts with complex heteropolyhedral units; and (6) formation of ordered superstructures of relatively simple structure types. The relations between symmetry and complexity are considered. The analysis of temporal dynamics of mineralogical discoveries since 1875 with the step of 25 years show the increasing chemical and structural complexities of human knowledge of the mineral kingdom in the history of mineralogy. In the Earth’s history, both diversity and complexity of minerals experience dramatic increases associated with the formation of Earth’s continental crust, initiation of plate tectonics and the Great Oxidation event.

complexity↗
NASA NTRS2010

Psychrophilic and Psychrotolerant Microbial Extremophiles in Polar Environments

The microbial extremophiles that inhabit the polar regions of our planet are of tremendous significance. The psychrophilic and psychrotolerant microorganisms, which inhabit all of the cold environments on Earth have important applications to Bioremediation, Medicine, Pharmaceuticals, and many other areas of Biotechnology. Until recently, most of the research on polar microorganisms was confined to studies of polar diatoms, yeast, fungi and cyanobacteria. However, within the past three decades, extensive studies have been conducted to understand the bacteria and archaea that inhabit the Arctic and Antarctic sea-ice, glaciers, ice sheets, permafrost and the cryptoendolithic, cryoconite and ice-bubble environments. These investigations have resulted in the discovery of many new genera and species of anaerobic and aerobic microbial extremophiles. Exotic enzymes, cold-shock proteins and pigments produced by some of the extremophiles from polar environments have the potential to be of great benefit to Mankind. Knowledge about microbial life in the polar regions is crucial to understanding the limitations and biodiversity of life on Earth and may provide valuable clues to the Origin of Life on Earth. The discovery of viable microorganisms in ancient ice from the Fox Tunnel, Alaska and the deep Vostok Ice has shown that microorganisms can remain alive while cryopreserved in ancient ice. The psychrophilic lithoautotrophic homoacetogen isolated from the deep anoxic trough of Lake Untersee is an ideal candidate for life that might inhabit comets or the polar caps of Mars. The spontaneous release of gas from within the Anuchin Glacier above Lake Untersee may provide clues to the ice geysers that erupt from the tiger stripe regions of Saturn s moon Enceladus. The methane productivity in the lower regimes of Lake Untersee may also provide insights into possible mechanisms for the recently discovered methane releases on Mars. Since most of the other water bearing bodies of our Solar system are frozen worlds, microbial extremophiles from the Polar Regions of Earth are of great importance to Astrobiology in understanding where and how to search for evidence of life elsewhere in the Cosmos.

Hoover, Richard B.↗
DOE OSTI2025

32 examples of LLM applications in materials science and chemistry: towards automation, assistants, agents, and accelerated scientific discovery

Abstract Large language models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientific automation, knowledge extraction, and more. Recent developments demonstrate that the latest class of models are able to integrate structured and unstructured data, assist in hypothesis generation, and streamline research workflows. To explore the frontier of LLM capabilities across the research lifecycle, we review applications of LLMs through 32 total projects developed during the second annual LLM hackathon for applications in materials science and chemistry, a global hybrid event. These projects spanned seven key research areas: (1) molecular and material property prediction, (2) molecular and material design, (3) automation and novel interfaces, (4) scientific communication and education, (5) research data management and automation, (6) hypothesis generation and evaluation, and (7) knowledge extraction and reasoning from the scientific literature. Collectively, these applications illustrate how LLMs serve as versatile predictive models, platforms for rapid prototyping of domain-specific tools, and much more. In particular, improvements in both open source and proprietary LLM performance through the addition of reasoning, additional training data, and new techniques have expanded effectiveness, particularly in low-data environments and interdisciplinary research. As LLMs continue to improve, their integration into scientific workflows presents both new opportunities and new challenges, requiring ongoing exploration, continued refinement, and further research to address reliability, interpretability, and reproducibility.

Computer Science↗
NASA NTRS1988

Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

Stclair, D. C.↗
DOE OSTI2024

Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges

Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long-term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large-ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy-related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno-economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO 2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO 2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large-ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large-ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Model-Based Approaches to Generate Knowledge from Data in a Plant Reliability Context

One challenge that nuclear power plant system engineers are facing is that the amount of equipment reliability (ER) data being continuously generated are extremely large. These data elements come in different forms: textual (e.g., condition reports) and numeric (e.g., generated by monitoring systems) and they provide system engineers with valuable insights and information regarding the discovery of anomalous behaviors or degradation trends, the identification of the possible causes behind such behaviors and trends, and the prediction of their direct consequences. This paper directly targets the generation of knowledge from ER data by putting “data into context”. Here, we employ model-based system engineering (MBSE) models of systems and assets to represent and capture their architecture and functional (i.e., cause-effect) relations. ER data elements are processed by identifying first which elements of the developed MBSE elements they are referring to. This task is much harder for textual data since the information contained in issue or maintenance reports needs to “be understood” by a computational tool. Here we called this process “knowledge extraction” where our methods to extract knowledge from textual data. Lastly, once numeric and textual ER data elements have been processed and “understood”, we discover possible cause-effect relations among them. This is performed by observing if a logical connection through the MBSE models exists, and if there is a temporal relation among them. The logic and temporal are the two main ingredients to perform “machine reasoning” from ER data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Proteome-wide characterization of PTMs reveals host cell responses to viral infection and identifies putative antiviral drug targets

Post-translational modifications (PTMs) are biochemical modifications that can significantly alter protein structure, function, stability, localization, and interactions with other molecules, thereby activating or inactivating intracellular processes. A growing body of research has begun to highlight the role of PTMs, including phosphorylation, ubiquitination, acetylation, and redox modifications, during virus-host interactions. Collectively, these PTMs regulate key steps in mounting the host immune response and control critical host pathways required for productive viral replication. This has led to the conception of antiviral therapeutics that focus on controlling host protein PTMs, potentially offering pathogen-agnostic treatment options and revolutionizing our capacity to prevent virus transmission. On the other hand, viruses can hijack the host cellular PTM machinery to modify viral proteins in promoting viral replication and evading immune surveillance. PTM regulation during virus-host interactions is complex and poorly mapped, and the development of effective PTM-targeted antiviral drugs will require a more comprehensive understanding of the cellular pathways essential for virus replication. In this review, we discuss the roles of PTMs in virus infection and how technological advances in mass spectrometry-based proteomics can capture systems-level PTM changes during viral infection. Additionally, we explore how such knowledge is leveraged to identify PTM-targeted candidates for developing antiviral drugs. Looking ahead, studies focusing on the discovery and functional elucidation of PTMs, either on the host or viral proteins, will not only deepen our understanding of molecular pathology but also pave the way for developing better drugs to fight emerging viruses.

Immunology↗
NASA NTRS1992

The planet Mars - From antiquity to the present

Telescopic observations of Mars, from those of Galileo in 1610 to the late 19th century, were summarized by Flammarion (1892, 1909). Major compilations of knowledge of Mars were produced by Antoniadi (1930) and de Vaucouleurs (1954). Polar cap composition was debated until the discovery by the Viking mission that the north and south perennial polar caps are composed of different materials. Spacecraft data indicate a rich and diverse geologic history as well as many unsolved puzzles. An annotated list of books about Mars is provided. Basic physical and chemical data on Mars are summarized in tabular form, and a guide to the Martian seasons is given.

Kieffer, Hugh H.↗
NASA NTRS2011

Saturn Neutron Exosphere as Source for Inner and Innermost Radiation Belts

Energetic proton and electron measurements by the ongoing Cassini orbiter mission are expanding our knowledge of the highest energy components of the Saturn magnetosphere in the inner radiation belt region after the initial discoveries of these belts by the Pioneer 11 and Voyager 2 missions. Saturn has a neutron exosphere that extends throughout the magnetosphere from the cosmic ray albedo neutron source at the planetary main rings and atmosphere. The neutrons emitted from these sources at energies respectively above 4 and 8 eV escape the Saturn system, while those at lower energies are gravitationally bound. The neutrons undergo beta decay in average times of about 1000 seconds to provide distributed sources of protons and electrons throughout Saturn's magnetosphere with highest injection rates close to the Saturn and ring sources. The competing radiation belt source for energetic electrons is rapid inward diffusion and acceleration of electrons from the middle magnetosphere and beyond. Minimal losses during diffusive transport across the moon orbits, e.g. of Mimas and Enceladus, and local time asymmetries in electron intensity, suggest that drift resonance effects preferentially boost the diffusion rates of electrons from both sources. Energy dependences of longitudinal gradient-curvature drift speeds relative to the icy moons are likely responsible for hemispheric differences (e.g., Mimas, Tethys) in composition and thermal properties as at least partly produced by radiolytic processes. A continuing mystery is the similar radial profiles of lower energy (<10 MeV) protons in the inner belt region. Either the source of these lower energy protons is also neutron decay, but perhaps alternatively from atmospheric albedo, or else all protons from diverse distributed sources are similarly affected by losses at the moon' orbits, e.g. because the proton diffusion rates are extremely low. Enceladus cryovolcanism, and radiolytic processing elsewhere on the icy moon and ring surfaces, are additional sources of protons via ionization and charge exchange from breakup of water molecules. But one must then account somehow for local acceleration to the observed keV-MeV energies, since moon sweeping and E-ring absorption would remove protons diffusing inward from the middle magnetosphere. Although the main rings block further inward diffusion from the inner radiation belts, the exospheric neutron-decay source, combined with much slower diffusion of protons relative to electrons, may produce an innermost radiation belt in the gap between the upper atmosphere and the D-ring. This innermost belt will first be explored in-situ during the final proximal orbits of the Cassini mission.

Cooper, John↗
DOE OSTI2026

Performance and Reliability Assessment of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Data Advisor (ADA)

The Atmospheric Radiation Measurement (ARM) User Facility provides one of the world's largest openly accessible repositories of atmospheric observations through the ARM Data Discovery platform. Although the repository contains more than three decades of measurements collected from permanent observatories, mobile facilities, aircraft campaigns, and field experiments, identifying appropriate datasets can be challenging, particularly for new users unfamiliar with ARM instrumentation and datastream organization. To improve data accessibility, the ARM Data Center developed the ARM Data Advisor (ADA), an artificial intelligence-powered assistant designed to facilitate scientific data discovery, dataset interpretation, and user guidance. This report evaluates ADA's performance as a domain-specific scientific assistant using realistic atmospheric science workflows. The evaluation examines five key capabilities: data retrieval and curation efficiency, hallucination resistance, scientific reasoning, response to ambiguous queries, and content retention and session continuity. Representative prompts were developed to simulate typical interactions between researchers and the ARM Data Discovery platform, and ADA's responses were assessed for retrieval completeness, scientific accuracy, consistency, and practical usefulness. In these representative tests, ADA reduced the complexity of discovering and accessing ARM datasets by recommending appropriate datastreams, explaining instrumentation, interpreting metadata, and assisting with data processing workflows. ADA also exhibits strong domain knowledge of atmospheric science terminology and generally resists hallucination by acknowledging unavailable datasets and requesting clarification when appropriate. Overall, the results indicate that ADA represents a promising advancement in scientific data discovery within the ARM User Facility and has considerable potential to improve researcher productivity, particularly for new users and interdisciplinary scientists seeking efficient access to ARM observations.

Salvador, Christian [ORNL] (ORCID:0000000283287777↗
DOE OSTI2024

Gene-Metabolite Association Prediction with Interactive Knowledge Transfer Enhanced Graph for Metabolite Production

Identifying gene targets for enhancing metabolite production in metabolic engineering is challenging due to the vast research literature and the approximation in genome-scale metabolic model (GEM) simulations. Here, to address this, we propose the Gene-Metabolite Association Prediction task, which automates gene discovery for given metabolite-gene pairs, accompanied by a benchmark dataset of 2474 metabolites and 1947 genes for Saccharomyces cerevisiae (SC) and Issatchenkia orientalis (IO). This task is complicated by incomplete metabolic graphs and metabolic heterogeneity. We introduce an Interactive Knowledge Transfer mechanism based on Metabolism Graphs (IKT4Meta) to enhance prediction accuracy by integrating cross-metabolism knowledge. Using Pretrained Language Models (PLMs) to generate inter-graph links mitigates heterogeneity issues, while intra-graph links are propagated via these anchors. Gene-metabolite predictions are then performed on the enriched graphs integrating multiple microorganisms’ knowledge. Experiments show that IKT4Meta outperforms baselines by up to 12.3% in link prediction.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2001

Time course of the MAPK and PI3-kinase response within 24 h of skeletal muscle overload

Knowledge of the molecular mechanisms by which skeletal muscle hypertrophies in response to increased mechanical loading may lead to the discovery of novel treatment strategies for muscle wasting and frailty. To gain insight into potential early signaling mechanisms associated with skeletal muscle hypertrophy, the temporal pattern of mitogen-activated protein kinase (MAPK) phosphorylation and phosphatidylinositol 3-kinase (PI3-kinase) activity during the first 24 h of muscle overload was determined in the rat slow-twitch soleus and fast-twitch plantaris muscles after ablation of the gastrocnemius muscle. p38alpha MAPK phosphorylation was elevated for the entire 24-h overload period in both muscles. In contrast, Erk 2 and p54 JNK phosphorylation were transiently increased by overload, returning to the levels of sham-operated controls by 24 h. PI3-kinase activity was increased by muscle overload only at 12 h of overload and only in the plantaris muscle. In summary, sustained elevation of p38alpha MAPK phosphorylation occurred early in response to muscle overload, identifying this pathway as a potential candidate for mediating early hypertrophic signals in response to skeletal muscle overload.

Non-NASA Center↗