Search NASA⌕ Search

SEARCH · Search NASA

Results for “correlation selection”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Ultraviolet Testing of Space Suit Materials for Mars

Human missions to Mars may require radical changes in the approach to extra-vehicular (EVA) suit design. A major challenge is the balance of building a suit robust enough to complete multiple EVAs under intense ultraviolet (UV) light exposure without losing mechanical strength or compromising the suit's mobility. To study how the materials degrade on Mars in-situ, the Jet Propulsion Laboratory (JPL) invited the Advanced Space Suit team at NASA's Johnson Space Center (JSC) to place space suit materials on the Scanning Habitable Environments with Raman & Luminescence for Organics and Chemicals (SHERLOC) instrument's calibration target of the Mars 2020 rover. In order to select materials for the rover and understand the effects from Mars equivalent UV exposure, JSC conducted ground testing on both current and new space suit materials when exposed to 2500 hours of Mars mission equivalent UV. To complete this testing, JSC partnered with NASA's Marshall Space Flight Center to utilize their UV vacuum chambers. Materials tested were Orthofabric, polycarbonate, Teflon, Dacron, Vectran, spectra, bladder, nGimat coated Teflon, and nGimat coated Orthofabric. All samples were measured for mass, tensile strength, and chemical composition before and after radiation. Mass loss was insignificant (less than 0.5%) among the materials. Most materials loss tensile strength after radiation and became more brittle with a loss of elongation. Changes in chemical composition were seen in all radiated materials through Spectral Analysis. Results from this testing helped select the materials that will fly on the Mars 2020 rover. In addition, JSC can use this data to create a correlation to the chemical changes after radiation-which is what the rover will send back while on Mars-to the mechanical changes, such as tensile strength.

Larson, Kristine↗
NASA NTRSDate not supplied

Modernization of Insulative Reusable Thermal Protection Systems (IRTPS)

Insulative thermal protection systems, such as Flexible Reusable Surface Insulation blankets and High Temperature Reusable Surface Insulation tiles, were developed for the Shuttle Orbiter to enable reuse of the vehicle for low-earth orbit missions. Since reusability is essential to many new industry launch and space vehicles, Shuttle-derived thermal protection materials (TPMs) are being sought for their flight proven performance. Alumina Enhanced Thermal Barrier (AETB) is the state-of-the-art tile material that was developed in the 90’s. AETB along with associated coatings, reaction cured glass (RCG) and Toughened Unipiece Fibrous Insulation (TUFI), are currently made by NASA using heritage raw materials derived from lifetime purchases. Finding viable replacements for raw materials that have changed in nature or are obsolete is important for continuation of these TPMs. In some cases, the use of modern raw materials has been shown to yield tile with reduced performance, most notably in mechanical properties. ​ In this work, the production of AETB will be discussed to better understand the process-structure-property relationships and for allowing use of these modern alternatives. A small-scale tile casting system was developed for rapid and efficient exploration of the manufacturing variables such raw material selection and pre-processing, casting process parameters, and billet firing protocols. An optical transmission defect characterization technique was implemented to correlate process variables to structure. Comparisons between TUFI/RCG coated AETB derived from heritage and modern raw materials will be shown including AHF arc jet test results completed under a collaboration with Stratolaunch.

thermal protection materials↗
NASA NTRS2009

Ground/Flight Correlation of Aerodynamic Loads with Structural Response

United States Air Force Research Laboratory (AFRL) ground tests at the NASA Transonic Dynamics Tunnel (TDT) and NASA flight tests provide a basis and methodology for in-flight characterization of the aeroelastic performance through the monitoring of the fluid-structure interaction using surface flow sensors. NASA NF-15B flight tests provided a unique opportunity to test the correlation of aerodynamic loads with sectional flow attachment/detachment points, also known as flow bifurcation points (FBPs), as observed in previous wind tunnel tests. The NF-15B tail was instrumented with hot-film sensors and strain gages for measuring root-bending strains. These data were gathered via selected sideslip maneuvers performed at level flight and subsonic speeds. The aerodynamic loads generated by the sideslip maneuver resulted in root-bending strains and hot-film sensor signals near the stagnation region that were highly correlated. For the TDT tests, a flexible wing section developed under the AFRL SensorCraft program was instrumented with strain gages, accelerometers, and hot-film sensors at multiple span stations. The TDT tests provided data showing a gradual phase change between the FBP and the structural mode occurred during a resonant condition as the wings structural modes were excited by the tunnel-generated gusts.

Mangalam, Arun S.↗
DOE OSTI2015

Automatic learning-based beam angle selection for thoracic IMRT

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume coverage and organ at risk sparing and were superior over plans produced with fixed sets of common beam angles. The great majority of the automatic plans (93%) were approved as clinically acceptable by three radiation therapy specialists. Conclusions: The results demonstrated the feasibility of utilizing a learning-based approach for automatic selection of beam angles in thoracic IMRT planning. The proposed method may assist in reducing the manual planning workload, while sustaining plan quality.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1994

ROSAT observations of z greater than 3 quasars

Successful pointed observations using the Roentgen Satellite (ROSAT) Position Sensitive Proportional Counter (PSPC) were made of seven z greater than 3 optically selected quasars from the Large Bright Quasar Survey (LBQS). Four detections and three 3 sigma upper limits resulted. Combining these data with the heterogeneous sample of Avni & Tananbaum (1986) confirms their conclusion that the ratio of x-ray to optical luminosity is correlated with optical luminosity and probably not correlated with redshift. This suggests that x-ray luminosity evolves more slowly than optical luminosity. These results are then used in conjunction with the LBQS database to estimate the contribution to the 2 keV x-ray background of bright, optically selected quasars with m(sub B(sub J)) less than 18.85; the result is about 5%.

Pickering, T. E.↗
DOE OSTI2023

Group Projected subspace pursuit for IDENTification of variable coefficient differential equations (GP-IDENT)

We propose an effective and robust algorithm for identifying partial differential equations (PDEs) with space-time varying coefficients from the noisy observation of a single solution trajectory. Identifying unknown differential equations from noisy data is a difficult task, and it is even more challenging with space and time varying coefficients in the PDE. The proposed algorithm, GP-IDENT, has three ingredients: (i) we use B-spline bases to express the unknown space and time varying coefficients, (ii) we propose Group Projected Subspace Pursuit (GPSP) to find a sequence of candidate PDEs with various levels of complexity, and (iii) we propose a new criterion for model selection using the Reduction in Residual (RR) to choose an optimal one among a pool of candidates. The new GPSP considers group projected subspaces which is more robust than existing methods in distinguishing correlated group features. We test GP-IDENT on a variety of PDEs and PDE systems, and compare it with the state-of-the-art parametric PDE identification algorithms under different settings to illustrate its outstanding performance. Furthermore, our experiments show that GP-IDENT is effective in identifying the correct terms from a large dictionary, and our model selection scheme is robust to noise.

Data-driven method↗
DOE OSTI2020

Machine learning substitutional defect formation energies in ABO 3 perovskites

Perovskite oxides are a promising material platform for use in a wide range of technological applications including electronics, sensors, fuel cells, and catalysis. This is owing to the extraordinary tunability of their physical and chemical properties via defect engineering. The feasibility and the stability of a defect, such as a substitutional dopant, in the host lattice is usually obtained via experiments and/or through detailed quantum mechanical calculations. Both of these conventional routes are expensive and time consuming. An alternative is a data-driven machine learning (ML)-based approach. In this work, we have applied ML techniques to identify the factors that influence defect formation energy, which is an important measure of the stability of the defects, in perovskite oxides. Using 13 elemental properties as features and random forest regression, we demonstrate a systematic approach to down-selecting from the larger set of features to those that are important, establishing a framework for accurate predictions of the defect formation energy. We quantitatively show that the most important factors that control the dopant stability are the dopant ionic size, heat of formation, effective tolerance factor, and oxidation state. Our work reveals previously unknown correlations, chemical trends, and the interplay between stability and underlying chemistries. Hence, these results showcase the efficacy of ML tools in identifying and quantifying different feature-dependencies and provide a promising route toward dopant selection in the perovskites. Herein, we have developed a framework that itself is general and can be potentially applied to other material classes.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Land use regression models for the oxidative potential of fine particles (PM2.5) in five European areas

Highlights: • OP moderately correlated (r ~.6) with PM{sub 2.5} mass, NO{sub 2}, and elemental constituents. • OP{sup AA} and OP{sup GSH} LUR models were developed and evaluated for five areas. • Three reasonably performing (R{sup 2}: .45–.58) OP{sup AA} LUR models in hold-out validation. • OP{sup GSH} models were not robust to new coefficients derived against sub-samples of sites. Oxidative potential (OP) of particulate matter (PM) is proposed as a biologically-relevant exposure metric for studies of air pollution and health. We aimed to evaluate the spatial variability of the OP of measured PM{sub 2.5} using ascorbate (AA) and (reduced) glutathione (GSH), and develop land use regression (LUR) models to explain this spatial variability. We estimated annual average values (m{sup −3}) of OP{sup AA} and OP{sup GSH} for five areas (Basel, CH; Catalonia, ES; London-Oxford, UK (no OP{sup GSH}); the Netherlands; and Turin, IT) using PM{sub 2.5} filters. OP{sup AA} and OP{sup GSH} LUR models were developed using all monitoring sites, separately for each area and combined-areas. The same variables were then used in repeated sub-sampling of monitoring sites to test sensitivity of variable selection; new variables were offered where variables were excluded (p > .1). On average, measurements of OP{sup AA} and OP{sup GSH} were moderately correlated (maximum Pearson's maximum Pearson's R = = .7) with PM{sub 2.5} and other metrics (PM{sub 2.5}absorbance, NO{sub 2}, Cu, Fe). HOV (hold-out validation) R{sup 2} for OP{sup AA} models was .21, .58, .45, .53, and .13 for Basel, Catalonia, London-Oxford, the Netherlands and Turin respectively. For OP{sup GSH}, the only model achieving at least moderate performance was for the Netherlands (R{sup 2} = .31). Combined models for OP{sup AA} and OP{sup GSH} were largely explained by study area with weak local predictors of intra-area contrasts; we therefore do not endorse them for use in epidemiologic studies. Given the moderate correlation of OP{sup AA} with other pollutants, the three reasonably performing LUR models for OP{sup AA} could be used independently of other pollutant metrics in epidemiological studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

THE LOCAL GROUP IN THE COSMIC WEB

We explore the characteristics of the cosmic web around Local-Group (LG)-like pairs using a cosmological simulation in the ΛCDM cosmology. We use the Hessian of the gravitational potential to classify regions on scales of ∼2 Mpc as a peak, sheet, filament, or void. The sample of LG counterparts is represented by two samples of halo pairs. The first is a general sample composed of pairs with similar masses and isolation criteria as observed for the LG. The second is a subset with additional observed kinematic constraints such as relative pair velocity and separation. We find that the pairs in the LG sample with all constraints are: (1) preferentially located in filaments and sheets, (2) located in a narrow range of local overdensity 0 < δ < 2, web ellipticity 0.1 < e < 1.0, and prolateness –0.4 < p < 0.4, (3) strongly aligned with the cosmic web. The alignments are such that the pair orbital angular momentum tends to be perpendicular to the smallest tidal eigenvector, e-hat {sub 3}, which lies along the filament direction or the sheet plane. A stronger alignment is present for the vector linking the two halos with the vector e-hat {sub 3}. Additionally, we fail to find a strong correlation between the spin of each halo in the pair with the cosmic web. All of these trends are expected to a great extent from the selection of LG total mass in the general sample. Applied to the observed LG, there is a potential conflict between the alignments of the different satellite planes and the numerical evidence for satellite accretion along filaments; the direction defined by e-hat {sub 3}. This highlights the relevance of achieving a precise characterization for the location of the LG in the cosmic web in the cosmological context provided by ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Fluorescence Color by Data-Driven Design of Genomic Silver Clusters

DNA nucleobase sequence controls the size of DNA-stabilized silver clusters, leading to their well-known yet little understood sequence-tuned colors. The enormous space of possible DNA sequences for templating clusters has challenged the understanding of how sequence selects cluster properties and has limited the design of applications that employ these clusters. Here, we investigate the genomic role of DNA sequence for fluorescent silver clusters using a data-driven approach. Employing rapid parallel silver cluster synthesis and fluorimetry, we determine the fluorescence spectra of silver cluster products stabilized by 1432 distinct DNA oligomers. By applying pattern recognition algorithms to this large experimental data set, we discover certain DNA base patterns, or “motifs,” that correlate to silver clusters with similar fluorescence spectra. These motifs are employed in machine learning classifiers to predictively design DNA template sequences for specific fluorescence color bands. Our method improves selectivity of templates by 330% for silver clusters with peak emission wavelengths beyond 660 nm. The discovered base motifs also provide physical insights into how DNA sequence controls silver cluster size and color. Finally, this predictive design approach for color of DNA-stabilized silver clusters exhibits the potential of machine learning and data mining to increase the precision and efficiency of nanomaterials design, even for a soft-matter-inorganic hybrid system characterized by an extremely large parameter space.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

Among many agricultural practices proposed to cut carbon emissions in the next 30 years is the deposition of carbon in soils as plant matter. Adding rooting traits as part of a sequestration strategy would result in significantly increased carbon sequestration. Integrating these traits into production agriculture requires a belowground phenotyping method compatible with high-throughput breeding (i.e., rapid, inexpensive, reliable, and non-destructive). However, methods that fulfill these criteria currently do not exist. We hypothesized that ground-penetrating radar (GPR) could fill this need as a phenotypic selection tool. In this study, we employed a prototype GPR antenna array to scan and discriminate the root and rhizome mass of the perennial sorghum hybrid PSH09TX15. B-scan level time/discrete frequency analyses using continuous wavelet transform were utilized to extract features of interest that could be correlated to the biomass of the subsurface roots and rhizome. Time frequency analysis yielded strong correlations between radar features and belowground biomass (max R −0.91 for roots and −0.78 rhizomes, respectively) These results demonstrate that continued refinement of GPR data analysis workflows should yield an applicable phenotyping tool for breeding efforts in contexts where selection is otherwise impractical.

Wolfe, Matthew↗
DOE OSTI2017

Blue Supergiant X-Ray Binaries in the Nearby Dwarf Galaxy IC 10

In young starburst galaxies, the X-ray population is expected to be dominated by the relics of the most massive and short-lived stars, black hole and neutron-star high-mass X-ray binaries (XRBs). In the closest such galaxy, IC 10, we have made a multi-wavelength census of these objects. Employing a novel statistical correlation technique, we have matched our list of 110 X-ray point sources, derived from a decade of Chandra observations, against published photometric data. We report an 8σ correlation between the celestial coordinates of the two catalogs, with 42 X-ray sources having an optical counterpart. Applying an optical color–magnitude selection to isolate blue supergiant (SG) stars in IC 10, we find 16 matches. Both cases show a statistically significant overabundance versus the expectation value for chance alignments. The blue objects also exhibit systematically higher f{sub x}/f{sub v} ratios than other stars in the same magnitude range. Blue SG-XRBs include a major class of progenitors of double-degenerate binaries, hence their numbers are an important factor in modeling the rate of gravitational-wave sources. We suggest that the anomalous features of the IC 10 stellar population are explained if the age of the IC 10 starburst is close to the time of the peak of interaction for massive binaries.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Towards an Optimal Noise Versus Resolution Trade-Off in Wind Scatterometry

A scatterometer is a radar that measures the normalized radar cross section sigma(sup 0) of the Earth's surface. Over the ocean this signal is related to the wind via the geophysical model function (GMF). The objective of wind scatterometry is to estimate the wind vector field from sigma(sup 0) measurements; however, there are many subtleties that complicate this problem-making it difficult to obtain a unique wind field estimate. Conventionally, wind estimation is split into two stages: a wind retrieval stage in which several ambiguous solutions are obtained, and an ambiguity removal stage in which ambiguities are chosen to produce an appropriate wind vector field estimate. The most common approach to wind field estimation is to grid the scatterometer swath into wind vector cells and estimate wind vector ambiguities independently for each cell. Then, field wise structure is imposed on the solution by an ambiguity selection routine. Although this approach is simple and practical, it neglects field wise structure in the retrieval step and does not account for the spatial correlation imposed by the sampling. This makes it difficult to develop a theoretically appropriate noise versus resolution trade-off using pointwise retrieval. Fieldwise structure may be imposed in the retrieval step using a model-based approach. However, this approach is generally only practical if a low order wind field model is applied, which may discard more information than is desired. Furthermore, model-based approaches do not account for the structure imposed by the sampling. A more general fieldwise approach is to estimate all the wind vectors for all the WVCs simultaneously from all the measurements. This approach can account for structure of the wind field as well as structure imposed by the sampling in the wind retrieval step. Williams and Long in 2010 developed a fieldwise retrieval method based on maximum a posteriori estimation (MAP). This MAP approach can be extended to perform a noise versus resolution trade-off, and deal with ambiguity selection. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed. This paper extends the fieldwise MAP estimation approach and investigates both the noise versus resolution trade-off as well as ambiguity removal in the fieldwise wind retrieval step. The method is then applied to the Sea Winds scatterometer and the results are analyzed.

soil moisture↗
DOE OSTI2017

Cluster Mass Calibration at High Redshift: HST Weak Lensing Analysis of 13 Distant Galaxy Clusters from the South Pole Telescope Sunyaev-Zel’dovich Survey

We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (z(median) = 0.88) galaxy clusters discovered in the South Pole Telescope (SPT) Sunyaev-Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass-observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V - I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration-mass relation using simulations. In combination with temperature estimates from Chandra we constrain the normalization of the mass-temperature scaling relation ln (E(z) M-500c/10(14)M(circle dot)) = A + 1.5ln (kT/7.2 keV) to A = 1.81(-0.14)(+0.24)(stat.)+/- 0.09(sys.), consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to c(200c) = 5.6(-1.8)(+3.7).

cosmology: observations↗
NASA NTRS1980

Gravity and magnetic anomaly modeling and correlation using the SPHERE program and Magsat data

The spherical Earth inversion, modeling, and contouring software were tested and modified for processing data in the Southern Hemisphere. Preliminary geologic/tectonic maps and selected cross sections for South and Central America and the Caribbean region are being compiled and as well as gravity and magnetic models for the major geological features of the area. A preliminary gravity model of the Andeas Beniff Zone was constructed so that the density columns east and west of the subducted plates are in approximate isostatic equilibrium. The magnetic anomaly for the corresponding magnetic model of the zone is being computed with the SPHERE program. A test tape containing global magnetic measurements was converted to a tape compatible with Purdue's CDC system. NOO data were screened for periods of high diurnal activity and reduced to anomaly form using the IGS-75 model. Magnetic intensity anomaly profiles were plotted on the conterminous U.S. map using the track lines as the anomaly base level. The transcontinental magnetic high seen in POGO and MAGSAT data is also represented in the NOO data.

Braile, L. W.↗
DOE OSTI2018

Spectroscopic Studies on the Metal-Insulator Transition Mechanism in Correlated Materials

Here, the metal–insulator transition (MIT) in correlated materials is a novel phenomenon that accompanies a large change in resistivity, often many orders of magnitude. It is important in its own right but its switching behavior in resistivity can be useful for device applications. From the material physics point of view, the starting point of the research on the MIT should be to understand the microscopic mechanism. Here, an overview of recent efforts to unravel the microscopic mechanisms for various types of MITs in correlated materials is provided. Research has focused on transition metal oxides (TMOs), but transition metal chalcogenides have also been studied. Along the way, a new class of MIT materials is discovered, the so–called relativistic Mott insulators in 5d TMOs. Distortions in the MO 6 (M = transition metal) octahedron are found to have a large and peculiar effect on the band structure in an orbital dependent way, possibly paving a way to the orbital selective Mott transition. In the final section, the character of the materials suitable for applications is summarized, followed by a brief discussion of some of the efforts to control MITs in correlated materials, including a dynamical approach using light.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Specific Ion Effects in Lanthanide–Amphiphile Structures at the Air–Water Interface and Their Implications for Selective Separation

The use of surfactants to attract dissolved ions to water surfaces and interfaces is an essential step in both solvent-based and solvent-free separation processes. Here, we have studied the interactions of lanthanide ions in the aqueous subphase with monolayers of dihexadecyl phosphate at air–water interfaces. With heavier lanthanides (atomic number Z ≥ 65) in the subphase, the floating layer can be compressed to an area/molecule of about half the molecular cross section, indicating bilayer formation. X-ray fluorescence and reflectivity data support this conclusion. In the presence of lighter lanthanides (Z < 65), only monolayers are observed. Subphase-concentration-dependent studies using Er 3+ (heavier) and Nd 3+ (lighter) lanthanides show a stepwise progression, with ions attaching to the monolayer only when the solution concentration is >3 × 10 –7 M. Above ~10 –5 M, bilayers form but only in the presence of the heavier lanthanide. Grazing incidence X-ray diffraction shows evidence of lateral ion–ion correlations in the bilayer structure but not in monolayers. Explicit solvent all-atom molecular dynamics simulations confirm the elevated ion–ion correlation in the bilayer system. This bilayer structure isolates heavier lanthanides but not lighter lanthanides from an aqueous solution and is therefore a potential mechanism for the selective separation of heavier lanthanides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Effect of Diets, Familial History, and Alternative Therapies on Genomic Instability of Breast Cancer Patients

This study evaluates a correlation between family history, micronutrients intake, and alternative therapies with genetic instability, before and during breast cancer treatment. For this study, a total of 150 women were selected. Among those, 50 women were breast cancer patients on chemotherapy, while 50 breast cancer patients were on radiotherapy, and 50 were healthy females. All the participants signed the informed consent form and answered the public health questionnaire. Samples of buccal epithelial and peripheral blood cells were collected and analyzed through micronucleus and comet assays. The cells were evaluated for apoptosis and DNA damage. Results showed the association of patients’ family history with an increase in toxicogenetic damage before and during cancer therapy. On the other hand, patients with late-onset cancer also presented genetic instability before and during therapy, along with those who did not take sufficient vegetables and alternative therapies. A positive correlation was observed between the genetic instability and alternative therapies, while inverse correlation was recorded with the vegetable consumption. Results clearly explain that the nutritional aspects and alternative therapies influence the genetic instability before and during cancer therapies especially in radiotherapy treated patients. Our data could be used for the monitoring therapies and management of breast cancer patients.

60 APPLIED LIFE SCIENCES↗