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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Detecting thermal discrepancies in vessel walls

An infrared, heat-sensing catheter particularly useful for identifying potentially fatal arterial plaques in patients with disease of the coronary or other arteries and its use are detailed. In one embodiment, an infrared fiberoptic system (with or without ultrasound) is employed at the tip of the catheter to locate inflamed, heat-producing, atherosclerotic plaque, which is at greater risk for rupture, fissure, or ulceration, and consequent thrombosis and occlusion of the artery. In another embodiment, a catheter with an infrared detector (with or without ultrasound) employed at its tip will likewise locate inflamed heat-producing atherosclerotic plaque. The devices and methods of the invention may be used to detect abscesses, infection, and cancerous regions by the heat such regions differentially display over the ambient temperature of immediately adjacent tissues. The methods and devices of the invention may also be used to detect regions of cooler than ambient tissue in a vessel or organ which indicate cell death, thrombosis, cell death, hemorrhage, calcium or cholesterol accumulations, or foreign materials.

Casscells, S. Ward↗
DOE OSTI2021

Too Good to Be True? Evaluation of Colonoscopy Sensitivity Assumptions Used in Policy Models

Background: Models can help guide colorectal cancer screening policy. Although models are carefully calibrated and validated, there is less scrutiny of assumptions about test performance. Methods: We examined the validity of the CRC-SPIN model and colonoscopy sensitivity assumptions. Standard sensitivity assumptions, consistent with published decision analyses, assume sensitivity equal to 0.75 for diminutive adenomas (<6 mm), 0.85 for small adenomas (6–10 mm), 0.95 for large adenomas (≥10 mm), and 0.95 for preclinical cancer. We also selected adenoma sensitivity that resulted in more accurate predictions. Targets were drawn from the Wheat Bran Fiber study. In the study, we examined how well the model predicted outcomes measured over a three-year follow-up period, including the number of adenomas detected, the size of the largest adenoma detected, and incident colorectal cancer. Results: Using standard sensitivity assumptions, the model predicted adenoma prevalence that was too low (42.5% versus 48.9% observed, with 95% confidence interval 45.3%–50.7%) and detection of too few large adenomas (5.1% versus 14.% observed, with 95% confidence interval 11.8%–17.4%). Predictions were close to targets when we set sensitivities to 0.20 for diminutive adenomas, 0.60 for small adenomas, 0.80 for 10- to 20-mm adenomas, and 0.98 for adenomas 20 mm and larger. Conclusions: Colonoscopy may be less accurate than currently assumed, especially for diminutive adenomas. Alternatively, the CRC-SPIN model may not accurately simulate onset and progression of adenomas in higher-risk populations. Impact: Misspecification of either colonoscopy sensitivity or disease progression in high-risk populations may affect the predicted effectiveness of colorectal cancer screening. When possible, decision analyses used to inform policy should address these uncertainties.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

TRIM16 overexpression inhibits the metastasis of colorectal cancer through mediating Snail degradation

Highlights: • TRIM16 does significantly inhibit CRC cell migration and metastasis. • TRIM16 negatively regulates CRC cells EMT. • TRIM16 directly interacts with Snail. • TRIM16 promotes degradation of Snail via ubiquition proteasome pathway. Tripartite motif containing 16 (TRIM16) is a member of the tripartite motif protein family and functions as a potential tumor suppressor in several cancers. However, the specific function and clinical significance of TRIM16 in colorectal cancer (CRC) remains unclear. In this study, we observed that low TRIM16 expression was detected frequently in primary colorectal cancer (CRC) tissues and was closely associated with a better prognosis. Functional studies demonstrate that TRIM16 overexpression notably inhibits the metastasis abilities of CRC in vivo and in vitro. Mechanistically, our results demonstrated that TRIM16 directly bound and ubiquitinated Snail family transcriptional repressor 1 (Snail), an important transcriptional factor of the epithelial-mesenchymal transition (EMT) process suppressing the EMT in CRC. Additionally, our data revealed that the inhibition effect of TRIM16 on cancer metastasis was dependent on Snail degradation. Collectively, our study is the first to report that TRIM16 plays a crucial anti-tumor role in CRC tumorigenesis. We also provided novel evidence that TRIM16 might act as a prognostic and therapeutic target to assess and inhibit CRC progression.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2012

Developing an Open Source, Reusable Platform for Distributed Collaborative Information Management in the Early Detection Research Network

For the past decade, the NASA Jet Propulsion Laboratory, in collaboration with Dartmouth University has served as the center for informatics for the Early Detection Research Network (EDRN). The EDRN is a multi-institution research effort funded by the U.S. National Cancer Institute (NCI) and tasked with identifying and validating biomarkers for the early detection of cancer. As the distributed network has grown, increasingly formal processes have been developed for the acquisition, curation, storage, and dissemination of heterogeneous research information assets, and an informatics infrastructure has emerged. In this paper we discuss the evolution of EDRN informatics, its success as a mechanism for distributed information integration, and the potential sustainability and reuse benefits of emerging efforts to make the platform components themselves open source. We describe our experience transitioning a large closed-source software system to a community driven, open source project at the Apache Software Foundation, and point to lessons learned that will guide our present efforts to promote the reuse of the EDRN informatics infrastructure by a broader community.

Early Detection Research Network (EDRN)↗
NASA NTRS1972

Advancements in medicine from aerospace research

A program designed to find second applications for space technology in the medical field is described. Illustrative examples and clinical test results are included for prosthetic urethral devices, ear oximeter for monitoring leukemia patients, devices for measuring low level CO effects on automobile drivers, radiation dosimeter probe for detecting radiation levels in cancerous areas, and electromyographic muscle trainer.

Wooten, F. T.↗
NASA NTRS1982

Compact Dual-Mode Microwave Antenna

Compact dual-mode antenna, 3.66 cm wide by 1.83 cm thick is used both for heating and thermographic detection of tumors in cancer research. Temperature sensor operates independently or simultaneously with heater. Antenna includes 1.6-GHz transmitter and 4.76-GHz receiver. Strip heater between antennas controls temperature of device. Maximum power output is 25 W.

Carr, K. L.↗
NASA NTRS2004

Hairlike Percutaneous Photochemical Sensors

Instrumentation systems based on hairlike fiber-optic photochemical sensors have been proposed as minimally invasive means of detecting biochemicals associated with cancer and other diseases. The fiber-optic sensors could be mass-produced as inexpensive, disposable components. The sensory tip of a fiber-optic sensor would be injected through the patient's skin into subcutaneous tissue. A biosensing material on the sensory tip would bind or otherwise react with the biochemical(s) of interest [the analyte(s)] to produce a change in optical properties that would be measured by use of an external photonic analyzer. After use, a fiber-optic sensor could be simply removed by plucking it out with tweezers. A fiber-optic sensor according to the proposal would be of the approximate size and shape of a human hair, and its sensory tip would resemble a follicle. Once inserted into a patient's subcutaneous tissue, the sensor would even more closely resemble a hair growing from a follicle (see Figure 1). The biosensing material on the sensory tip could consist of a chemical and/or cells cultured and modified for the purpose. The biosensing material would be contained within a membrane that would cover the tip. If the membrane were not permeable by an analyte, then it would be necessary to create pores in the membrane that would be large enough to allow analyte molecules to diffuse to the biosensing material, but not so large as to allow cells (if present as part of the biosensing material) to diffuse out. The end of the fiber-optic sensor opposite the sensory tip would be inserted in a fiberoptic socket in the photonic analyzer.

George, Thomas↗
NASA NTRS2004

Microelectronic DNA assay for the detection of BRCA1 gene mutations

Mutations in BRCA1 are characterized by predisposition to breast cancer, ovarian cancer and prostate cancer as well as colon cancer. Prognosis for this cancer survival depends upon the stage at which cancer is diagnosed. Reliable and rapid mutation detection is crucial for the early diagnosis and treatment. We developed an electronic assay for the detection of a representative single nucleotide polymorphism (SNP), deletion and insertion in BRCA1 gene by the microelectronics microarray instrumentation. The assay is rapid, and it takes 30 minutes for the immobilization of target DNA samples, hybridization, washing and readout. The assay is multiplexing since it is carried out at the same temperature and buffer conditions for each step. The assay is also highly specific, as the signal-to-noise ratio is much larger than recommended value (72.86 to 321.05 vs. 5) for homozygotes genotyping, and signal ratio close to the perfect value 1 for heterozygotes genotyping (1.04).

Validation Studies↗
DOE OSTI2021

MIER3 induces epithelial-mesenchymal transition and promotes breast cancer cell aggressiveness via forming a co-repressor complex with HDAC1/HDAC2/Snail

Highlights: • The expression of MIER3 was correlated with poor outcome of breast cancer patients. • MIER3 induced EMT and promoted cell migration. • MIER3 interacted with HDAC1/HDAC2 and Snail to form a repressive complex. • The repressive complex bound to E-cadherin promoter and reduced its acetylation. Breast cancer is one of the most frequently diagnosed cancers and the leading cause of cancer death in women. MIER3 (Mesoderm induction early response 1, family member3) is considered as a potential oncogene for breast cancer. However, the role of MIER3 in breast cancer remain largely unknown. The expression of MIER3 was detected and the relationship between its expression and clinicopathological characteristics was also analyzed. The effect of MIER3 on proliferation and migration of breast cancer cells was detected in vitro and in vivo. Western blot, IF, and Co-IP were employed to detect the relationship between MIER3, HDAC1, HDAC2, and Snail. ChIP assay was performed to determine the binding of MIER3/HDAC1/HDAC2/Snail complex to the promoter of E-cadherin. In this study, we found that MIER3 was upregulated in breast cancer tissue and closely associated with poor prognosis of patients. MIER3 could promote the proliferation, migration, and epithelial-mesenchymal transition (EMT) of breast cancer cells. Further studies showed that MIER3 interacted with HDAC1/HDAC2 and Snail to form a repressive complex which could bind to E-cadherin promoter and was related to its deacetylation. Our study concluded that MIER3 was involved in forming a co-repressor complex with HDAC1/HDAC2/Snail to promote EMT by silencing E-cadherin.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Ad-apoptin inhibits glycolysis, migration and invasion in lung cancer cells targeting AMPK/mTOR signaling pathway

Ad-apoptin is a recombinant oncolytic adenovirus constructed by our laboratory that can express apoptin. It can selectively kill tumor cells without damaging normal cells. This study investigated the effects of Ad-apoptin on glycolysis, migration and invasion of non-small cell lung cancer. Cell viability and apoptosis were detected by CCK-8 and flow cytometry, respectively. Glycolysis was investigated by glucose consumption, lactic acid production and glycolytic key enzyme protein levels. Migration and invasion were evaluated via wound healing, transwell assays and epithelial-mesenchymal transition (EMT) protein levels. The interaction between apoptin and AMPK was detected by Co-IP. A nude mice tumor model was established to investigate the anti-cancer role of Ad-apoptin in vivo. The results showed that Ad-apoptin inhibits cell viability and induces apoptosis of A549 and NCI–H23 cells. Ad-apoptin can reduce the glucose uptake and lactic production in lung cancer cells, and reduce the expression of related glycolysis-limiting enzymes. At the same time, Ad-apoptin inhibited the migration and invasion of lung cancer. Immunoprecipitation showed that apoptin and AMPK could interact directly. Moreover, knockdown of AMPK significantly attenuated the inhibitory effect of Ad-apoptin on glycolysis, migration and invasion of A549 and NCI–H23 cells. Ad-apoptin can inhibit the growth of tumors in nude mice. Compared with the control group, Ad-apoptin had a significant inhibitory effect on AMPK knockdown tumors. The immunohistochemical results of tumor tissues were consistent with those in vitro. Collectively, Ad-apoptin targets AMPK and inhibits glycolysis, migration and invasion of lung cancer cells through the AMPK/mTOR signaling pathway. This suggests that Ad-apoptin may have therapeutic potential for lung cancer by targeting AMPK activation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

In search of autophagy biomarkers in breast cancer: Receptor status and drug agnostic transcriptional changes during autophagy flux in cell lines

Autophagy drives drug resistance and drug-induced cancer cell cytotoxicity. Targeting the autophagy process could greatly improve chemotherapy outcomes. The discovery of specific inhibitors or activators has been hindered by challenges with reliably measuring autophagy levels in a clinical setting. We investigated drug-induced autophagy in breast cancer cell lines with differing ER/PR/Her2 receptor status by exposing them to known but divergent autophagy inducers each with a unique molecular target, tamoxifen, trastuzumab, bortezomib or rapamycin. Differential gene expression analysis from total RNA extracted during the earliest sign of autophagy flux showed both cell- and drug-specific changes. We analyzed the list of differentially expressed genes to find a common, cell- and drug-agnostic autophagy signature. Twelve mRNAs were significantly modulated by all the drugs and 11 were orthogonally verified with Q-RT-PCR (Klhl24, Hbp1, Crebrf, Ypel2, Fbxo32, Gdf15, Cdc25a, Ddit4, Psat1, Cd22, Ypel3). The drug agnostic mRNA signature was similarly induced by a mitochondrially targeted agent, MitoQ. In-silico analysis on the KM-plotter cancer database showed that the levels of these mRNAs are detectable in human samples and associated with breast cancer prognosis outcomes of Relapse-Free Survival in all patients (RSF), Overall Survival in all patients (OS), and Relapse-Free Survival in ER + Patients (RSF ER + ). High levels of Klhl24, Hbp1, Crebrf, Ypel2, CD22 and Ypel3 were correlated with better outcomes, whereas lower levels of Gdf15, Cdc25a, Ddit4 and Psat1 were associated with better prognosis in breast cancer patients. This gene signature uncovers candidate autophagy biomarkers that could be tested during preclinical and clinical studies to monitor the autophagy process.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2002

Pathology effects at radiation doses below those causing increased mortality

Mortality data from experiments conducted at the Argonne National Laboratory (ANL) on the long-term effects of external whole-body irradiation on B6CF(1) mice were used to investigate radiation-induced effects at intermediate doses of (60)Co gamma rays or fission-spectrum neutrons either delivered as a single exposure or protracted over 60 once-weekly exposures. Kaplan-Meier analyses were used to identify the lowest dose in the ANL data (within radiation quality, pattern of exposure, and sex) at which radiation-induced mortality caused by primary tumors could be detected (approximately 1-2 Gy for gamma rays and 10-15 cGy for neutrons). Doses at and below these levels were then examined for radiation-induced shifts in the spectrum of pathology detected at death. To do this, specific pathology events were pooled into larger assemblages based on whether they were cancer, cardiovascular disease or non-neoplastic diseases detected within the lungs and pleura, liver and biliary tract, reproductive organs, or urinary tract. Cancer and cardiovascular disease were further subdivided into categories based on whether they caused death, contributed to death, or were simply observed at death. Counts of how often events falling within each of these combined pathology categories occurred within a mouse were then used as predictor variables in logistic regression to determine whether irradiated mice could be distinguished from control mice. Increased pathology burdens were detected in irradiated mice at doses lower than those causing detectable shifts in mortality-22 cGy for gamma rays and 2 cGy for neutrons. These findings suggest that (1) models based on mortality data alone may underestimate radiation effects, (2) radiation may have adverse health consequences (i.e. elevated health risks) even when mortality risks are not detected, and (3) radiation-induced pathologies other than cancer do occur, and they involve multiple organ systems.

Non-NASA Center↗
DOE OSTI2025

Large-scale deep learning for metastasis detection in pathology reports

Objectives No existing algorithm can reliably identify metastasis from pathology reports across multiple cancer types and the entire US population. In this study, we develop a deep learning model that automatically detects patients with metastatic cancer by using pathology reports from many laboratories and of multiple cancer types. Materials and Methods We use 60 471 unstructured pathology reports from 4 Surveillance, Epidemiology, and End Results (SEER) registries. The reports were coded into 1 of 3 labels: metastasis negative, metastases positive, or metastasis undetermined. We utilize a task-specific deep neural network trained from scratch and compare its performance with a widely used large language model (LLM). Results Our deep learning architecture trained on task-specific data outperforms a general-purpose LLM, with a recall of 0.894 compared to 0.824. We quantified model uncertainty and used it to defer reports for human review. We found that retaining 72.9% of reports increased recall from 0.894 to 0.969. Discussion A smaller deep learning architecture trained on task-specific data outperforms a general LLM. Equally critical to model performance is the incorporation of uncertainty quantification, achieved here through an abstention mechanism. Conclusions This study’s finding demonstrate the feasibility of developing algorithms to automatically identify metastatic cancer cases from unstructured pathology reports.

machine learning↗
DOE OSTI2021

Smartphone-Based Device for Colorimetric Detection of MicroRNA Biomarkers Using Nanoparticle-Based Assay

The detection of microRNAs (miRNAs) is emerging as a clinically important tool for the non-invasive detection of a wide variety of diseases ranging from cancers and cardiovascular illnesses to infectious diseases. Over the years, miRNA detection schemes have become accessible to clinicians, but they still require sophisticated and bulky laboratory equipment and trained personnel to operate. The exceptional computing ability and ease of use of modern smartphones coupled with fieldable optical detection technologies can provide a useful and portable alternative to these laboratory systems. Herein, we present the development of a smartphone-based device called Krometriks, which is capable of simple and rapid colorimetric detection of microRNA (miRNAs) using a nanoparticle-based assay. The device consists of a smartphone, a 3D printed accessory, and a custom-built dedicated mobile app. We illustrate the utility of Krometriks for the detection of an important miRNA disease biomarker, miR-21, using a nanoplasmonics-based assay developed by our group. We show that Krometriks can detect miRNA down to nanomolar concentrations with detection results comparable to a laboratory-based benchtop spectrophotometer. With slight changes to the accessory design, Krometriks can be made compatible with different types of smartphone models and specifications. Thus, the Krometriks device offers a practical colorimetric platform that has the potential to provide accessible and affordable miRNA diagnostics for point-of-care and field applications in low-resource settings.

Krishnan, Tushar (ORCID:0000000342610336)↗
DOE OSTI2022

Enzymatic Laser-Induced Graphene Biosensor for Electrochemical Sensing of the Herbicide Glyphosate

Glyphosate is a globally applied herbicide yet it has been relatively undetectable in-field samples outside of gold-standard techniques. Its presumed nontoxicity toward humans has been contested by the International Agency for Research on Cancer, while it has been detected in farmers’ urine, surface waters and crop residues. Rapid, on-site detection of glyphosate is hindered by lack of field-deployable and easy-to-use sensors that circumvent sample transportation to limited laboratories that possess the equipment needed for detection. Herein, the flavoenzyme, glycine oxidase, immobilized on platinum-decorated laser-induced graphene (LIG) is used for selective detection of glyphosate as it is a substrate for GlyOx. The LIG platform provides a scaffold for enzyme attachment while maintaining the electronic and surface properties of graphene. The sensor exhibits a linear range of 10–260 µm, detection limit of 3.03 µm, and sensitivity of 0.991 nA µm -1 . The sensor shows minimal interference from the commonly used herbicides and insecticides: atrazine, 2,4-dichlorophenoxyacetic acid, dicamba, parathion-methyl, paraoxon-methyl, malathion, chlorpyrifos, thiamethoxam, clothianidin, and imidacloprid. Sensor function is further tested in complex river water and crop residue fluids, which validate this platform as a scalable, direct-write, and selective method of glyphosate detection for herbicide mapping and food analysis.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Accelerating Random Forest Classification on GPU and FPGA

Random Forests (RFs) are a commonly used machine learning method for classification and regression tasks spanning a variety of application domains, including bioinformatics, business analytics, and software optimization. While prior work has focused primarily on improving performance of the training of RFs, many applications, such as malware identification, cancer prediction, and banking fraud detection, require fast RF classification. In this work, we accelerate RF classification on GPU and FPGA. In order to provide efficient support for large datasets, we propose a hierarchical memory layout suitable to the GPU/FPGA memory hierarchy. We design three RF classification code variants based on that layout, and we investigate GPU- and FPGA-specific considerations for these kernels. Our experimental evaluation, performed on an Nvidia Xp GPU and on a Xilinx Alveo U250 FPGA accelerator card using publicly available datasets on the scale of millions of samples and tens of features, covers various aspects. First, we evaluate the performance benefits of our hierarchical data structure over the standard compressed sparse row (CSR) format. Second, we compare our GPU implementation with cuML, a machine learning library targeting Nvidia GPUs. Third, we explore the performance/accuracy tradeoff resulting from the use of different tree depths in the RF. Finally, we perform a comparative performance analysis of our GPU and FPGA implementations. Our evaluation shows that for high accuracy targets, our GPU implementation yields 5-9x speedup over CSR, and up to a 2x speedup over cuML.

FPGA, Xilinx FPGA, GPU, Random Forest classificati↗
NASA NTRS2011

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.↗
NASA NTRS2002

Detection of cystic structures using pulsed ultrasonically induced resonant cavitation

Apparatus and method for early detection of cystic structures indicative of ovarian and breast cancers uses ultrasonic wave energy at a unique resonance frequency for inducing cavitation in cystic fluid characteristic of cystic structures in the ovaries associated with ovarian cancer, and in cystic structures in the breast associated with breast cancer. Induced cavitation bubbles in the cystic fluid implode, creating implosion waves which are detected by ultrasonic receiving transducers attached to the abdomen of the patient. Triangulation of the ultrasonic receiving transducers enables the received signals to be processed and analyzed to identify the location and structure of the cyst.

Bar-Cohen, Yoseph↗