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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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24 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cystine-knot peptide inhibitors of HTRA1 bind to a cryptic pocket within the active site region

Cystine-knot peptides (CKPs) are naturally occurring peptides that exhibit exceptional chemical and proteolytic stability. We leveraged the CKP carboxypeptidase A1 inhibitor as a scaffold to construct phage-displayed CKP libraries and subsequently screened these collections against HTRA1, a trimeric serine protease implicated in age-related macular degeneration and osteoarthritis. The initial hits were optimized by using affinity maturation strategies to yield highly selective and potent picomolar inhibitors of HTRA1. Crystal structures, coupled with biochemical studies, reveal that the CKPs do not interact in a substrate-like manner but bind to a cryptic pocket at the S1’ site region of HTRA1 and abolish catalysis by stabilizing a non-competent active site conformation. The opening and closing of this cryptic pocket is controlled by the gatekeeper residue V221, and its movement is facilitated by the absence of a constraining disulfide bond that is typically present in trypsin fold serine proteases, thereby explaining the remarkable selectivity of the CKPs. Our findings reveal an intriguing mechanism for modulating the activity of HTRA1, and highlight the utility of CKP-based phage display platforms in uncovering potent and selective inhibitors against challenging therapeutic targets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Insight into the assembly of lipid-hyaluronan complexes in osteoarthritic conditions

Interactions between molecules in the synovial fluid and the cartilage surface may play a vital role in the formation of adsorbed films that contribute to the low friction of cartilage boundary lubrication. Osteoarthritis (OA) is the most common degenerative joint disease. Previous studies have shown that in OA-diseased joints, hyaluronan (HA) not only breaks down resulting in a much lower molecular weight (MW), but also its concentration is reduced ten times. Here, we have investigated the structural changes of lipid-HA complexes as a function of HA concentration and MW to simulate the physiologically relevant conditions that exist in healthy and diseased joints. Small angle neutron scattering and dynamic light scattering were used to determine the structure of HA-lipid vesicles in bulk solution, while a combination of atomic force microscopy and quartz crystal microbalance was applied to study their assembly on a gold surface. We infer a significant influence of both MW and HA concentrations on the structure of HA-lipid complexes in bulk and assembled on a gold surface. Our results suggest that low MW HA cannot form an amorphous layer on the gold surface, which is expected to negatively impact the mechanical integrity and longevity of the boundary layer and could contribute to the increased wear of the cartilage that has been reported in joints diseased with OA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Early Diagnosis of Fibromyalgia Using Surface-Enhanced Raman Spectroscopy Combined with Chemometrics

Fibromyalgia (FM) is a chronic muscle pain disorder that shares several clinical features with other related rheumatologic disorders. This study investigates the feasibility of using surface-enhanced Raman spectroscopy (SERS) with gold nanoparticles (AuNPs) as a fingerprinting approach to diagnose FM and other rheumatic diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), osteoarthritis (OA), and chronic low back pain (CLBP). Blood samples were obtained on protein saver cards from FM (n = 83), non-FM (n = 54), and healthy (NC, n = 9) subjects. A semi-permeable membrane filtration method was used to obtain low-molecular-weight fraction (LMF) serum of the blood samples. SERS measurement conditions were standardized to enhance the LMF signal. An OPLS-DA algorithm created using the spectral region 750 to 1720 cm -1 enabled the classification of the spectra into their corresponding FM and non-FM classes (Rcv > 0.99) with 100% accuracy, sensitivity, and specificity. The OPLS-DA regression plot indicated that spectral regions associated with amino acids were responsible for discrimination patterns and can be potentially used as spectral biomarkers to differentiate FM and other rheumatic diseases. This exploratory work suggests that the AuNP SERS method in combination with OPLS-DA analysis has great potential for the label-free diagnosis of FM.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Transcriptomic Changes in Peripheral Blood Mononuclear Cells of International Space Station Crewmembers

In space, living organisms are exposed to numerous stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmembers` immunobiology before, during, and after spaceflight. For this project, blood samples were collected from International Space Station (ISS) crewmembers at the following time points: i) at two pre-flight time points of 180 days (L180) and 45 days (L45) before launch. ii) During flight, blood was drawn at approximately the midpoint (mid-flight, MF) of the mission, and shortly before egress from the ISS (late-flight, LF). iii) Post-flight blood samples were collected within 24 hrs (R0), 30 days (R30) and 90 days (R90) after landing. For each crewmember, blood was also drawn from a matching test subject on the ground at the corresponding time point. For both the ISS crewmembers and the ground control subjects, total RNA was isolated from peripheral blood mononuclear cells (PBMC) and mRNA was analysed using next generation RNA-sequencing (NGS). Differentially expressed genes were determined by performing contrast analysis. Using the ground control subjects of all of the time points combined as a control, a number of dysregulated genes were identified in astronauts at MF, LF and R0, including downregulations of SMAD7 and CDKN1A at MF and LF. Some of the genes such as SERPINE1 and VEGFA were downregulated at MF and LF, but upregulated at R0, while others such as NKG7 were down regulated at all of the 3 time points. Pathway analysis of these differentially expressed genes indicated that the NF-κB pathway was chronically activated in space. Analysis of the consequent diseases suggested potential associations with not only immune dysfunction, but also other health risks including osteoarthritis, cardiac hypertrophy and neuroinflammation.

Maria Moreno-Villanueva↗
NASA NTRSDate not supplied

Transcriptomic Changes in Peripheral Blood Mononuclear Cells of International Space Station Crewmembers

In space, living organisms are exposed to numerous stress factors including microgravity and space radiation. For humans, these harmful environmental factors have been known to cause negative health impacts such as immune dysfunction. Understanding the mechanisms by which spaceflight impacts human health at the molecular level is critical not only for accurately assessing the risks associated with spaceflight, but also for developing effective countermeasures. This study is part of the Functional Immune Project, intended to determine alterations in crewmembers` immunobiology before, during, and after spaceflight. For this project, blood samples were collected from International Space Station (ISS) crewmembers at the following time points: i) Blood was drawn at two pre-flight time points of 180 days (L180) and 45 days (L45) before launch. ii) During flight, blood was drawn at approximately the midpoint (mid-flight, MF) of the mission, and shortly before egress from the ISS (late-flight, LF). iii) Post-flight blood samples were collected within 36 hours (R0), 30 days (R30) and 90 days (R90) after landing. For each crewmember, blood was also drawn from a matching test subject on the ground at the corresponding time point. For both the ISS crewmembers and the ground control subjects, total RNA was isolated from peripheral blood mononuclear cells (PBMC) and mRNA was analysed using next generation RNA-sequencing (NGS). Differentially expressed genes were determined by performing contrast analysis. Using the ground control subjects of all time points combined as a control, a number of dysregulated genes were identified in astronauts at MF, LF and R0, including downregulations of SMAD7 and CDKN1A at MF and LF. Some of the genes such as SERPINE1 and VEGFA were downregulated at MF and LF, but upregulated at R0, while others such as NKG7 were down regulated at all 3 time points. Pathway analysis of these differentially expressed genes indicated that the NF-κB pathway was chronically activated in space. Analysis of the consequent diseases suggested potential associations with not only immune dysfunction, but also other health risks including osteoarthritis, cardiac hypertrophy and neuroinflammation.

Maria Moreno-Villanueva↗