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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Advanced urothelial cancer: a radiology update

The recent genomic characterization of urothelial carcinoma by the Cancer Genome Atlas Project, made possible by the introduction of high throughput, reduced cost, and sequence analysis, has shed new insights on the biology of advanced disease. In addition, studies on imaging of advanced urothelial carcinoma have widened the knowledge on disease presentation and on pattern of metastatic spread and their correlation with the underlying biology of urothelial carcinoma. The wide range of treatments for advanced urothelial cancer, including combined chemotherapy regimens and immune checkpoint inhibitors, each result in treatment class-specific patterns of response and adverse events. Results of studies point to the need for a reliable biomarker, perhaps with imaging, that predicts prognosis and treatment response to systemic treatment, and can be used to select the most effective treatment while minimizing toxicity. This review of advanced urothelial cancer introduces the latest advances in genetic profiling, the current role of imaging, the radiographic appearance of treatment response and their toxicities, and details potential future areas of imaging research.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Computed tomography (CT) in the evaluation of bladder and ureteral trauma: indications, technique, and diagnosis

Introduction: Trauma to the genitourinary system includes blunt and penetrating injuries to bladder and ureters. These are rare injuries and are overlooked as other abdominal and pelvic injuries often take priority. Delayed diagnosis can lead to significant morbidity and mortality. Computed tomography has taken a central role in the imaging of the ureters and bladder. Methods: This article reviews the anatomic relationships, mechanisms of injury, and clinical presentation to help physicians determine when bladder and ureteral injuries should be suspected and further imaging should be pursued. Radiologic evaluation of bladder and ureteral injury with CT cystography and CT urography, respectively, will be reviewed. Conclusion: CT cystography and CT urography are effective tools in identifying potentially serious injuries to the genitourinary system. Timely recognition of these injuries can be crucial for the overall management and prognosis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Preoperative imaging for locoregional staging of bladder cancer

Bladder cancer is the ninth most common cancer, expected to lead to an estimated 17,670 deaths in the United States in 2019. Clinical management and prognosis of bladder cancer mainly depend on the extent of locoregional disease, particularly whether bladder muscle is involved. Therefore, bladder cancer is often divided into superficial, non-muscle-invasive bladder cancer and muscle-invasive bladder cancer; the latter often prompts consideration for cystectomy. While precise staging prior to cystectomy is crucial, the optimal preoperative imaging modality used to stage the disease remains controversial. Transurethral resection of bladder tumor (TURBT) followed by computed tomography (CT) urography is the current recommended approach for staging bladder cancer but suffers from a high rate of understaging. We review the recent literature and compare different imaging modalities for assessing the presence of muscle invasion and lymph node involvement prior to cystectomy and highlight the advantages of each modality.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2023

Identifying crack tip position and stress intensity factors from displacement data

Fracture prognosis and characterization efforts require knowledge of crack tip position and the Stress Intensity Factors (SIFs) acting in the vicinity of the crack. Here, in this work, we present an efficient numerical approach to infer both of these characteristics under a consistent theoretical framework from noisy, unstructured displacement data. The novel approach utilizes the separability of the asymptotic linear elastic fracture mechanics fields to expedite the search for crack tip position and is particularly useful for noisy displacement data. The manuscript begins with an assessment of the importance of accurately locating crack tip position when quantifying the SIFs from displacement data. Next, the proposed separability approach for quickly inferring crack tip position is introduced. Comparing to the widely used displacement correlation approach, the performance of the separability approach is assessed. Cases involving both noisy data and systematic deviation from the asymptotic linear elastic fracture mechanics model are considered, e.g. inelastic material behavior and finite geometries. An open source python implementation of the proposed approach is available for use by those doing field and laboratory work involving digital image correlation and simulations, e.g. finite element, discrete element, molecular dynamics and peridynamics, where the crack tip position is not explicitly defined.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiscale Modeling Meets Machine Learning: What Can We Learn?

Machine learning is increasingly recognized as a promising technology in the biological, biomedical, and behavioral sciences. There can be no argument that this technique is incredibly successful in image recognition with immediate applications in diagnostics including electrophysiology, radiology, or pathology, where we have access to massive amounts of annotated data. However, machine learning often performs poorly in prognosis, especially when dealing with sparse data. This is a field where classical physics-based simulation seems to remain irreplaceable. In this review, we identify areas in the biomedical sciences where machine learning and multiscale modeling can mutually benefit from one another: Machine learning can integrate physics-based knowledge in the form of governing equations, boundary conditions, or constraints to manage ill-posted problems and robustly handle sparse and noisy data; multiscale modeling can integrate machine learn- ing to create surrogate models, identify system dynamics and parameters, analyze sensitivities, and quantify uncertainty to bridge the scales and understand the emergence of function. With a view towards applications in the life sciences, we discuss the state of the art of combining machine learning and multiscale modeling, identify applications and opportunities, raise open questions, and address potential challenges and limitations. We anticipate that it will stimulate discussion within the community of computational mechanics and reach out to other disciplines including mathematics, statistics, computer science, artificial intelligence, biomedicine, systems biology, and precision medicine to join forces towards creating robust and efficient models for biological systems.

machine learning, multiscale modeling, physics-bas↗
DOE OSTI2023

Friction Extrusion: Solid-State Metal Synthesis and Recycling in Sustainable Manufacturing

Friction extrusion (FE) is a novel solid-state process for synthesis and recycling of metals and alloys. The novelty of FE is that it utilizes the frictional heating and extensive plastic deformation intrinsic in the process to stir, mechanically alloy, consolidate, and convert powders, chips, and other recyclable feedstock metals into a usable product form of highly engineered materials. FE represents a potentially transformational sustainable manufacturing technology. Being a solid-state process, it eliminates the energy-intensive melting and solidification steps, which are necessary in the conventional metal recycle and synthesis processes. Therefore, FE is a highly energy-efficient, practically zero-emission, and economically competitive process. Here, in this work, the concept and configuration of FE are introduced, the energy-saving advantage of FE is analyzed, the feasibility of FE is demonstrated with synthesizing Al alloys, and the results of some metallographic and mechanical properties studies are presented. A prognosis of the friction extrusion technology is outlined.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Caffeine enhances the anti-tumor effect of 5-fluorouracil via increasing the production of reactive oxygen species in hepatocellular carcinoma

The development of drug resistance affecting the prognosis of patients with hepatocellular carcinoma (HCC) leads to low survival rate of HCC patients. Caffeine is reported to have a function of protecting the liver and anti-tumor activity. Therefore, caffeine may be an ideal enhancer for HCC chemotherapy regimens. Our study showed that the combination of caffeine and 5-FU significantly inhibited the proliferation of HCC cells in vivo and in vitro comparing with caffeine or 5-FU monotherapy. The CI values of caffeine (0.5 mM) combined with 5-FU (25, 50 μM) were all less than 1, confirming that the utilization of drug combination has a synergistic inhibitory effect on the proliferation of HCC cells. Meanwhile, results of Western blot and TUNEL assays demonstrated that the apoptotic level of HCC cells in the combined group was significantly increased. The protein expression level of cleaved PARP was up-regulated, while the protein level of Bcl-2 and Bcl-xL was down-regulated. In addition, we found that ROS levels were increased in the 1 mM caffeine and 25 μM 5-FU combination group comparing with the control or single drug group. Taken together, this is the first study to demonstrate that the combination of caffeine and 5-FU inhibits HCC cells proliferation and promotes cellular apoptosis by regulating intracellular ROS production. The present data provides a basis for the application of caffeine combined with 5-FU as a novel chemotherapy regimen for HCC.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Multiplexed Quantitative Proteomics in Prostate Cancer Biomarker Development

Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.

Prostate cancer, SRM, PRM, DIA, protein biomarker↗
DOE OSTI2020

Analysis of degradation in residential battery energy storage systems for rate-based use-cases

This article examines the impact of residential battery energy storage (BES) systems' operational modes on the life (i.e. usable energy capacity) of the battery under several climatic conditions and battery chemistries. The sharp increase in residential BES installations has been a result of decreasing costs of batteries, increase in rate structures motivated applications such as solar self-consumption and time-of-use energy management, and customers purchasing these systems for backup power. While these different modes of operations provide a combination of increased bill savings, reliability of supply, and energy sustainability to the customer, their operational characteristics vary significantly between use-cases. Functional life of BES systems is known to be strongly dependent on their operating conditions. In this article, we analyze the operation of residential BES systems under different rate-based use-cases, for different battery chemistries and cell designs, and under different environmental conditions. This is conducted by simulating the control of BES operations using rate-based cycling algorithms and analyzing the prognosis of multiple battery lifetime models that consider complex nonlinear dependencies of operational stress factors such as state-of-charge, depth-of-discharge, and temperature on degradation. Significant variations in battery life are observed owing to the differences in characteristics of the uses-cases coupled with environmental conditions and battery chemistries. Such differences lead to the conclusion that choice of residential BES technologies and chemistries should account for their intended use-cases.

25 ENERGY STORAGE↗
DOE OSTI2023

Effect of radiation exposure on survival after first solid cancer diagnosis in A-bomb survivors

Comparison of the estimated effect of atomic bomb radiation exposure on solid cancer incidence and solid cancer mortality in the RERF Life Span Study (LSS) reveals a difference in the magnitude and shape of the excess relative risk dose response. A possible contributing factor to this difference is pre-diagnosis radiation effect on post-diagnosis survival. Pre-diagnosis radiation exposure theoretically could influence post-diagnosis survival by affecting the genetic makeup and possibly aggressiveness of cancer, or by compromising tolerance for aggressive treatment for cancer. We analyze the radiation effect on post-diagnosis survival in 20,463 LSS subjects diagnosed with first-primary solid cancer between 1958 and 2009 with particular attention to whether death was caused by the first-primary cancer, other cancer, or non-cancer diseases. From multivariable Cox regression analysis of cause-specific survival, the excess hazard at 1 Gy (EH 1Gy ) for death from the first primary cancer was not significantly different from zero – p = 0.23, EH 1Gy = 0.038 (95 % CI: –0.023, 0.104). Death from other cancer and death from non-cancer diseases both were significantly associated with radiation dose: other cancer EH 1Gy = 0.38 (95 % CI: 0.24, 0.53); non-cancer EH 1Gy = 0.24 (95 % CI: 0.13, 0.36), both p < 0.001. There is no detectable large effect of pre-diagnosis radiation exposure on post-diagnosis death from the first primary cancer in A-bomb survivors. A direct effect of pre-diagnosis radiation exposure on cancer prognosis is ruled out as an explanation for the difference in incidence and mortality dose response in A-bomb survivors.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

CPTAC↗
DOE OSTI2022

Bayesian model updating with finite element vs surrogate models: Application to a miter gate structural system

Bayesian finite element (FE) model updating using direct model evaluations of large-scale high-fidelity FE models is extremely computationally expensive. Surrogate models can be used as fast emulators of FE models to accelerate the model calibration process. The physics/mechanics-based FE models are still the underpinning behind the surrogate models. Here, this paper evaluates the loss in accuracy and the gain in computational time while performing Bayesian model updating by using surrogate model evaluations compared to using direct FE model evaluations. This evaluation is crucial before entirely relying on surrogate models in model updating for structural health monitoring (SHM) and damage prognosis (DP) purposes. This paper also demonstrates Bayesian updating and surrogate model construction of large-scale high-fidelity FE models of infrastructure systems. In this regard, the miter gate structural system is considered as the testbed structure. Three predominant damage modes (loss of contact between gate and wall, loss of thickness due to corrosion, and loss of tension in the diagonal rods) are considered for model updating purposes. Bayesian model updating is performed using direct FE evaluations by leveraging parallel computing. Two types of surrogates, namely polynomial chaos expansion (PCE) and Gaussian process regression (GPR), are developed for the miter gate. Model updating is performed again using the trained surrogate models, and the updating results are compared with their counterparts obtained using the direct FE evaluation results. The posterior distribution of the FE model parameters obtained using the trained surrogates are sufficiently accurate with respect to the posterior obtained utilizing the direct FE evaluations. In addition, an approximate 4-fold decrease in the computational time was observed when using surrogate model evaluations instead of direct FE evaluations for model updating.

42 ENGINEERING↗
DOE OSTI2021

Modern Radiation Therapy for Extranodal Nasal-Type NK/T-cell Lymphoma: Risk-Adapted Therapy, Target Volume, and Dose Guidelines from the International Lymphoma Radiation Oncology Group

In the multidisciplinary management of early-stage extranodal natural killer/T-cell lymphoma, nasal type (ENKTCL), with curative intent, radiation therapy is the most efficacious modality and is an essential component of a combined-modality regimen. In the past decade, utilization of upfront radiation therapy and non–anthracycline-based chemotherapy has improved treatment and prognosis. This guideline mainly addresses the heterogeneity of clinical features, principles of risk-adapted therapy, and the role and appropriate design of radiation therapy. Radiation therapy methods (including target volume definition, dose and delivery methods) are crucial for optimizing cure for patients with early-stage ENKTCL. The application of the principles of involved site radiation therapy in this lymphoma entity often leads to a more extended clinical target volume (CTV) than in other lymphoma types because it usually presents with primary tumor invasion, multifocal lesions, or extensive submucosal infiltration beyond the macroscopic disease. The CTV varies across different primary sites and is classified mainly into nasal, nonnasal upper aerodigestive tract (UADT), and extra-UADT entities. This review is a consensus of the International Lymphoma Radiation Oncology Group regarding the approach to radiation therapy, target-volume definition, optimal dose, and dose constraints in ENKTCL treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Randomized Trial of Radiation Therapy With Weekly Cisplatin or Cetuximab in Low-Risk HPV-Associated Oropharyngeal Cancer (TROG 12.01) – A Trans-Tasman Radiation Oncology Group Study

The excellent prognosis of patients with low-risk human papillomavirus (HPV)- associated oropharyngeal squamous cell carcinoma has led to concerns about overtreatment and excessive toxicity with radiation therapy and cisplatin, leading to interest in de-intensification trials. We investigated whether cetuximab, an epidermal growth factor receptor targeting antibody, when combined with radiation therapy would result in a decrease in symptom burden and toxicity with similar efficacy compared with weekly cisplatin.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

A prognostic risk model for glioma patients by systematic evaluation of genomic variations

The overall survival rate of gliomas has not significantly improved despite new effective treatments, mainly due to tumor heterogeneity and drug delivery. Here, we perform an integrated clinic-genomic analysis of 1, 477 glioma patients from a Chinese cohort and a TCGA cohort and propose a potential prognostic model for gliomas. We identify that SBS11 and SBS23 mutational signatures are associated with glioma recurrence and indicate worse prognosis only in low-grade type of gliomas and IDH-Mut subtype. We also identify 42 genomic features associated with distinct clinical outcome and successfully used ten of these to develop a prognostic risk model of gliomas. The high-risk glioma patients with shortened survival were characterized by high level of frequent copy number alterations including PTEN, CDKN2A/B deletion, EGFR amplification, less IDH1 or CIC gene mutations, high infiltration levels of immunosuppressive cells and activation of G2M checkpoint and Oxidative phosphorylation oncogenic pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

NIRDye 812: A molecular platform tailored for multimodal bioimaging applications of targeted fluorescence- and photoacoustic-guided surgery

The primary treatment for malignant tumors remains to be surgical removal of the diseased tissue. The presence or absence of residual diseased tissue at the tumor margin is the strongest predictor of postoperative prognosis and recurrence. Accordingly, reliance on the ability of surgeons to visually distinguish diseased tissue from healthy tissue unambiguously in real time is crucial. Near infrared-I (NIRsingle bondI) fluorescence-emitting targeting biomolecular constructs such as anticancer antibody-fluorophore conjugates, namely cetuximab-IRDye® 800CW (CTB-IRDye® 800CW), are FDA-approved for clinical trial usage in the fluorescence-guided resection of diseased tissue due to affording improved direct visualization of tumor tissue when compared to the use of either the unaided eye under standard white light illumination (WLI) surgical techniques or non-targeting fluorophores. Unfortunately, though helpful, CTB-IRDye® 800CW affords limited (i) identification of diseased tissue and (ii) tumor margin delineation, because the immunoconjugate generates suboptimal tumor-to-background ratios (TBRs) as a result of its spectral/photophysical profiles poorly aligning with the fixed optical windows of pre-/clinical setups. As such, CTB-IRDye® 800CW is more prone to affording incomplete resection compared to if TBRs were higher due to otherwise. Here, to aid in accurately identifying deep-seated diseased tissue, photoacoustic (PA) tomography has been implemented alongside CTB-IRDye® 800CW to achieve PA signals that could result in higher TBRs. However, in clinical trial practice, using IRDye® 800CW for PA imaging also yields subpar TBRs due to it affording low PA signals. To overcome such limitations, we developed NIRDye 812, a structurally-modified topological equivalent of IRDye® 800CW, to confer it the capability to yield both higher TBRs and superior PA signal than that of the equivalent CTB-conjugate and fluorophore IRDye® 800CW itself, respectively. To do so, we substituted the oxygen atom at its meso-position with a sulfur atom. CTB-NIRDye 812 demonstrated a red-shifted absorption wavelength at 796 nm and a peak NIR-I fluorescence emission wavelength at 820 nm, which better dovetails with the fixed windows of preinstalled fixed emission filters within commercial pre-/clinical NIR-I fluorescence imaging instruments. Overall, CTB-NIRDye 812 provided a ~ 2-fold increase in TBRs compared to those of CTB-IRDye® 800CW in vivo. Also, NIRDye 812 displayed an ~60% higher PA signal than that of IRDye® 800CW. Collectively, we achieved our goal of improving upon the spectral/photophysical and PA properties of IRDye® 800CW via introducing a subtle modification to its electronic core such that its CTB immunoconjugate could potentially allow for fast track or breakthrough designation by the FDA due to its near-identical structure displaying considerably improved efficacy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

NaroNet: Discovery of tumor microenvironment elements from highly multiplexed images

Understanding the spatial interactions between the elements of the tumor microenvironment -i.e. tumor cells. fibroblasts, immune cells- and how these interactions relate to the diagnosis or prognosis of a tumor is one of the goals of computational pathology. We present NaroNet, a deep learning framework that models the multi-scale tumor microenvironment from multiplex-stained cancer tissue images and provides patient-level interpretable predictions using a seamless end-to-end learning pipeline. Trained only with multiplex-stained tissue images and their corresponding patient-level clinical labels, NaroNet unsupervisedly learns which cell phenotypes, cell neighborhoods, and neighborhood interactions have the highest influence to predict the correct label. To this end, NaroNet incorporates several novel and state-of-the-art deep learning techniques, such as patch-level contrastive learning, multi-level graph embeddings, a novel max-sum pooling operation, or a metric that quantifies the relevance that each microenvironment element has in the individual predictions. We validate NaroNet using synthetic data simulating multiplex-immunostained images where a patient label is artificially associated to the -adjustable- probabilistic incidence of different microenvironment elements. We then apply our model to two sets of images of human cancer tissues: 336 seven-color multiplex-immunostained images from 12 high-grade endometrial cancer patients; and 382 35-plex mass cytometry images from 215 breast cancer patients. In both synthetic and real datasets, NaroNet provides outstanding predictions of relevant clinical information while associating those predictions to the presence of specific microenvironment elements.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

Acute myeloid leukemia is a poor prognosis cancer commonly stratified by genetic aberrations, but these mutations are often heterogeneous and don’t always predict therapeutic response. Here we combine transcriptomic, proteomic, and phosphoproteomic datasets with ex vivo drug sensitivity data to help understand the underlying pathophysiology of AML beyond mutations. We measured the proteome and phosphoproteome of 210 patients and combined them with genomics and transcriptomic measurements to identify four proteogenomic subtypes that complemented existing genetic subtypes. We then built a predictor to classify samples into subtypes based on 147 molecular features and mapped them to a ‘landscape’. Each region of this landscape corresponded to specific drug response patterns. We then built a drug response prediction model to identify drugs that target distinct subtypes. We can ultimately use these models to predict drug treatment response and prioritize treatments. Finally, we extended our models and mapped a series of cell lines representing various stages of quizartinib resistance into our subtype landscape, predicting and experimentally validating a switch in sensitivity to venetoclax to panobinostat, two drugs with very different mechanisms than quizartinib. Our results show how multi-omics data together with drug sensitivity data can inform therapy stratification and drug combinations in AML.

59 BASIC BIOLOGICAL SCIENCES↗