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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Lightweight Multifunctional Planetary Probe for Extreme Environment Exploration and Locomotion

The demand to explore new worlds requires the development of advanced technologies that enable landed science on uncertain terrains or in hard to reach locations. As a result, contemporary Entry, Descent, Landing, (EDL) and additional locomotion (EDLL) profiles are becoming increasingly more complex, with the introduction of lifting/guided entries, hazard avoidance on descent, and a plethora of landing techniques including airbags and the skycrane maneuver. The inclusion of each of these subsystems into a mission profile is associated with a substantial mass penalty. This report explores the new all-in-one entry vehicle concept, TANDEM, a new combined EDLL concept, and compares it to the current state of the art EDL systems. The explored system is lightweight and collapsible and provides the capacity for lifting/guided entry, guided descent, hazard avoidance, omnidirectional impact protection and surface locomotion without the aid of any additional subsystems. This Phase I study explored: 1. The capabilities and feasibility of the TANDEM concept as an EDLL vehicle. 2. Extensive impact analysis to ensure mission success in unfavorable landing conditions, and safe landing in Tessera regions. 3. Development of a detailed design for a conceptual mission to Venus. As a result of our work it was shown that: 1. TANDEM provides additional benefits over the Adaptive, Deployable Entry Placement Technology (ADEPT) including guided descent and surface locomotion, while reducing the mass by 38% compared to the ADEPT-VITaL mission. 2. Demonstrated that the design of tensegrity structures, and TANDEM specifically, grows linearly with an increase in velocity, which was previously unknown. 3. Investigation of surface impact revealed a promising results that suggest a properly configured TANDEM vehicle can safely land and preform science in the Tessera regions, which was previously labeled by the Decadal Survey as, largely inaccessible despite its high scientific interest. This work has already resulted in a NASA TM and will be submitted to the Journal of Spacecraft and Rockets.

landing techniques↗
NASA NTRS2019

Pterodactyl: An Uncoupled Range Control Approach to Fully Numerical Predictor-Corrector Entry Guidance

Entry, descent, and landing (EDL) has been identified as a core area of investment in NASA's Strategic Technology Investment Plan (NASA STIP). STIP lists the space technologies needed to help achieve NASA's science, technology, and exploration goals across the agency. Within the EDL core area, deployable hypersonic decelerators, also known as deployable entry vehicles (DEVs), have been identified as an area of investment, due to its potential to revolutionize payload delivery methods to Earth and other planets. These vehicles, which can deploy their heat shields or alter their shape before entry, exploit an increased and more effective drag ratio by using less mass than traditional blunt body vehicles with rigid aeroshells. DEVs like Adaptive Deployable Entry and Placement Technology (ADEPT) and Hypersonic Inflatable Aerodynamic Decelerator (HIAD) have demonstrated the capability of transporting the equivalent science payloads of blunt body rigid aeroshells, while using a significantly smaller diameter when stowed within a launch vehicle. While DEVs' increased energy dissipation for less mass is an attractive feature, their ability to contract and expand would require advancements in the current state-of-the-art guidance and control (G&C) architectures used by traditional rigid vehicles. Pterodactyl, a project funded by NASA's Space Technology Mission Directorate (STMD), aims to provide feasible integrated G&C solutions for DEVs, complete with optimized vehicle designs and packaging analyses. Structural and aerodynamic analyses for the explored control systems suggested a need for a bank angle guidance algorithm, a heritage guidance approach that has been used in many entry precision targeting vehicles, as well as an additional need for the development of a non-bank angle guidance. For this reason, Pterodactyl will consider four different G&C configurations during its design phase: i) a reaction control system for bank (sigma) control, ii) a mass movement system for angle of attack (alpha) sideslip (beta) control, iii) flaps for alpha - beta control, and iv) flaps for sigma control. To increase the applicability of each proposed integrated G&C architecture, an 11 km/s lunar return demonstration mission is selected to stress the developed technology capability. The Lifting Nano-ADEPT (LNA) vehicle is chosen as the DEV to demonstrate the integrated solutions. This paper will detail the trajectory design for a lunar return mission, using the validated bank control guidance algorithm Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and a newly developed guidance algorithm: FNPEG Uncoupled Range Control (URC). FNPEG-URC diverges from traditional bank angle guidances by producing alpha and beta commands to thereby decouple downrange and crossrange control. This presentation will discuss the development and overall performance of FNPEG and FNPEG-URC for each of the four G&C configurations. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing site while abiding by trajectory constraints in the face of dispersions.

Johnson, Breanna↗
NASA NTRS2020

Pterodactyl: Control Architectures Development for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The need to return high mass payloads is driving the development of a new class of vehicles, Deployable Entry Vehicles (DEV) for which feasible and optimized control architectures have not been developed. The Pterodactyl project, seeks to advance the current state-of-the-art for entry vehicles by developing a design, test, and build capability for DEVs that can be applied to various entry vehicle configurations. This paper details the efforts on the NASA-funded Pterodactyl project to investigate multiple control techniques for the Lifting Nano-ADEPT (LNA) DEV. We design and implement multiple control architectures on the LNA and evaluate their performance in achieving varying guidance commands during entry.First we present an overview of DEVs and the Lifting Nano-ADEPT (LNA), along with the physical LNA configuration that influences the different control designs. Existing state-of-the-art for entry vehicle control is primarily propulsive as reaction control systems (RCS) are widely employed. In this work, we analyze the feasibility of using both propulsive control systems such as RCS to generate moments, and non-propulsive control systems such as aerodynamic control surfaces and internal moving mass actuations to shift the LNA center of gravity and generate moments. For these diverse control systems, we design different multi-input multi-output (MIMO) state-feedback integral controllers based on linear quadratic regulator (LQR) optimal control methods. The control variables calculated by the controllers vary, depending on the control system being utilized and the outputs to track for the controller are either the (i) bank angle or the (ii) angle of attack and sideslip angle as determined by the desired guidance trajectory. The LQR control design technique allows the relative allocation of the control variables through the choice of the weighting matrices in the cost index. Thus, it is easy to (i) specify which and how much of a control variable to use, and (ii) utilize one control design for different control architectures by simply modifying the choice of the weighting matrices.By providing a comparative analysis of multiple control systems, configurations, and performance, this paper and the Pterodactyl project as a whole will help entry vehicle system designers and control systems engineers determine suitable control architectures for integration with DEVs and other entry vehicle types.

Okolo, Wendy A.↗
NASA NTRS2020

Pterodactyl: Control System Demonstrator Development for Integrated Control Design of a Mechanically Deployed Entry Vehicle

The NASA-funded Pterodactyl project is a design, test, and build capability to (i) advance the current state of the art for Deployable Entry Vehicle (DEV) guidance and control (G&C), and (ii) determine the feasibility of control system integration for various entry vehicle types including those without aeroshells. This capability is currently being used to develop control systems for one such unconventional entry vehicle, the Lifting Nano-ADEPT (LNA) vehicle. ADEPT offers the possibility of integrating control systems directly onto the mechanically deployed structure and building hardware demonstrators will help assess integration and design challenges. Control systems based on aerodynamic control surfaces, mass movement, and reaction control systems (RCS) are currently being investigated for a down-select to the most suitable control architecture for the LNA.To that effect, in this submission, we detail the efforts of the Pterodactyl project to develop a series of hardware demonstrators for the different LNA control systems. Rapid prototypes, for a set of quarter- model or eighth-model vehicle segments, will be developed for all three architectures to validate mechanical design assumptions, and hardware-in-the-loop (HIWL) control approaches. A ground test control system demonstrator will be designed and built after the trade study is complete. The industrial-grade demonstrator will be designed so that it can be incorporated into a HWIL simulation to further validate the findings of the initial trade study. The HWIL simulation will leverage the iPAS environment developed at NASA's Johnson Space Center which facilitates integration testing to support technology maturation and risk reduction, necessary elements for the hardware demonstration development detailed in this paper.

Margolis, Benjamin W.↗
NASA NTRS2020

Enabling Entry Technologies for Ice Giant Missions

The highest priority science goals for Ice Giant missions are: 1) Interior structure of the Planet, and 2) Bulk composition that includes isotopes and noble gases. The interaction between the planetary interior and the atmosphere requires sustained global measurements. Noble gas and Isotope measurements require in situ measurement. Drag modulated aerocapture utilizing ADEPT offers more mass delivered to the Ice Giants than with propulsive orbit insertion. The Galileo Probe entered at a ‘hot’ spot which created interpretation challenges. Juno is providing valuable orbital measurements, but without in situ measurements the story is incomplete. Planetary scientists interested in Ice Giant missions should perform mission design studies with these new Entry System technologies to assess the feasibility within the context of the international collaboration framework. A mission architecture that includes probe(s) along with an orbiting spacecraft can deploy the probes at the desired location while taking simultaneous measurements from orbit to provide invaluable data that can correlate both global and local measurements. Entry System Technologies currently being developed by NASA are poised to enable missions that position the Orbiter & Probes through drag modulated aerocapture (ADEPT), and HEEET enables the Probes to survive the extreme environments encountered for entry into the atmospheric interior.

Venkatapathy, E.↗
NASA NTRS2020

Parametric Cost Estimates of Four 20 Ton Payload Mars EDL Vehicle Concepts

Cost is one of the biggest obstacles to sending humans to Mars. Many studies have examined various vehicles and/or technologies which could be used to send humans to Mars. However, nearly all of these studies have either ignored cost or have used the mass of the vehicles as a surrogate for cost. This work presents parametric cost estimates of four Mars Entry, Descent, and Landing vehicle concepts capable of landing 20 tons of payload on the surface of Mars. The concepts are the Co-Optimization Blunt-body Re-entry Analysis-Mid lift to drag ratio Rigid Vehicle (Cobra–MRV), Adaptive Deployable Entry and Placement Technology (ADEPT), Hypersonic Inflatable Aerodynamic Decelerator (HIAD), and Capsule concepts. Two variants of the HIAD concept are studied, one with a single HIAD heatshield and one with two HIADs. The study presents the development and production cost of each vehicle and the total cost to build five flight units and fifteen flight units. Five flight units is representative of a single mission, or a "Flags and Footprints" style campaign, whereas fifteen flight units is representative of multiple missions going to multiple sites on Mars. All costs presented in this work are normalized to the average of the first unit production cost of the lander concepts. There is a large amount of uncertainty both in the design of the vehicles and the cost of the vehicles and it is impossible to claim with certainty which vehicle will cost the least. However, it is likely that the total cost to produce five flight units will be in the following ranking from least costly to most costly, Single HIAD, Capsule, Dual HIAD, Cobra, ADEPT. The ranking for fifteen units is similar but with the positions of the Dual HIAD and Cobra reversed. This study only considers the cost of the entry vehicle and does not take into account the effect of the entry vehicle’s mass on the cost of the in-space propulsion stage or launch vehicle.

Paul D Friz↗
NASA NTRSDate not supplied

Validation and Sensitivity Analyses of Arc-Jet Performance of Woven Thermal Protection Entry Systems

Woven thermal protection materials for the Adaptable, Deployable, Entry and Placement Technology (ADEPT) entry system are simulated using a dual layer formalism in a finite volume implicit framework. The model developed and demonstrated here includes multi-dimensional and time-varying thermal response of the material to arc-jet test conditions. This work further demonstrates the sensitivities of the macro-scale thermal response to the through-thickness and in-plane conductivities of the carbon fabric, and to other experimental measurements such as cloth emissivity and thickness. The modeling can be extended to the ADEPT system that would encompass a single-piece woven heat shield configuration

Pratibha Raghunandan↗
NASA NTRS2013

Thermal and Structural Performance of Woven Carbon Cloth For Adaptive Deployable Entry and Placement Technology

Arcjet testing and analysis of a three-dimensional (3D) woven carbon fabric has shown that it can be used as a thermal protection system and as a load bearing structural component for a low ballistic coefficient hypersonic decelerator called ADEPT (Adaptive Deployable Entry and Placement Technology). Results of arcjet tests proved that the 3D woven carbon fabric can withstand flight-like heating while under flight-like biaxial mechanical loads representative of those encountered during shallow entry flight path angles into the atmosphere of Venus. Importantly, the arcjet test results have been used to extend a preliminary material thermal response model based on previous testing of the same 3D woven carbon fabric under uni-axial mechanical loading.

Carbon fabric↗
DOE OSTI2021

Instruction Roofline: An insightful visual performance model for GPUs

The Roofline performance model provides an intuitive approach to identify performance bottlenecks and guide performance optimization. However, the classic FLOP-centric approach is inappropriate for the emerging applications that perform more integer operations than floating point operations. In this article, we reintroduce our Instruction Roofline Model on NVIDIA GPUs and expand our evaluation of it. The Instruction Roofline incorporates instructions and memory transactions across all memory hierarchies together, and provides more performance insights than the FLOP-oriented Roofline Model, that is, instruction throughput, stride memory access patterns, bank conflicts, and thread predication. We use our Instruction Roofline methodology to analyze eight proxy applications: HPGMG from AMReX, Matrix Transpose benchmarks, ADEPT from MetaHipMer's sequence alignment phase, EXTENSION from MetaHipMer's local assembly phase, CUSP, cuSPARSE, cudaTensorCoreGemm, and cuBLAS. We demonstrate the ability of our methodology to understand various aspects of performance and performance bottlenecks on NVIDIA GPUs and motivate code optimizations.

Ding, N↗
DOE OSTI2024

Out-of-Distribution Detection and Radiological Data Monitoring Using Statistical Process Control

Abstract Machine learning (ML) models often fail with data that deviates from their training distribution. This is a significant concern for ML-enabled devices as data drift may lead to unexpected performance. This work introduces a new framework for out of distribution (OOD) detection and data drift monitoring that combines ML and geometric methods with statistical process control (SPC). We investigated different design choices, including methods for extracting feature representations and drift quantification for OOD detection in individual images and as an approach for input data monitoring. We evaluated the framework for both identifying OOD images and demonstrating the ability to detect shifts in data streams over time. We demonstrated a proof-of-concept via the following tasks: 1) differentiating axial vs. non-axial CT images, 2) differentiating CXR vs. other radiographic imaging modalities, and 3) differentiating adult CXR vs. pediatric CXR. For the identification of individual OOD images, our framework achieved high sensitivity in detecting OOD inputs: 0.980 in CT, 0.984 in CXR, and 0.854 in pediatric CXR. Our framework is also adept at monitoring data streams and identifying the time a drift occurred. In our simulations tracking drift over time, it effectively detected a shift from CXR to non-CXR instantly, a transition from axial to non-axial CT within few days, and a drift from adult to pediatric CXRs within a day—all while maintaining a low false positive rate. Through additional experiments, we demonstrate the framework is modality-agnostic and independent from the underlying model structure, making it highly customizable for specific applications and broadly applicable across different imaging modalities and deployed ML models.

Zamzmi, Ghada↗
DOE OSTI2014

A Pair Production Telescope for Medium-Energy Gamma-Ray Polarimetry

We describe the science motivation and development of a pair production telescope for medium-13 energy gamma-ray polarimetry. Our instrument concept, the Advanced Energetic Pair Telescope 14 (AdEPT), takes advantage of the Three-Dimensional Track Imager, a low-density gaseous time 15 projection chamber, to achieve angular resolution within a factor of two of the pair production 16 kinematics limit (~0.6° at 70 MeV), continuum sensitivity comparable with the Fermi-LAT front 17 detector (<3×10-6 MeV cm-2 s-1 at 70 MeV), and minimum detectable polarization less than 10% 18 for a 10 millicrab source in 106 seconds.

Hunter, Stanley D.↗
DOE OSTI2018

Engineering of Escherichia coli β-lactamase TEM-1 variants showing higher activity under acidic conditions than at the neutral pH

Highlights: • Genetic screening is useful for obtaining β-lactamases with altered pH dependency. • A few mutations each suppress the activity of a β-lactamase at pH 7.0. • The engineered β-lactamase variants are more active under the acidic conditions. • The relevant amino acid substitutions are located far from the catalytic site. Escherichia coli β-lactamase TEM-1 is potentially useful in the antibody-directed enzyme/prodrug therapy (ADEPT), converting nontoxic prodrugs to toxic agents. The produced toxin would kill cancer cells, when the enzyme is attached to a tumor-antigen-specific antibody. However, the off-site reaction possibly occurring in the blood or normal tissues raises safety concern. In the present study, we engineered TEM-1 variants preferentially active at pH 5.8–6.2, near the pH of the acidic microenvironment of tumor. A library of randomly mutagenized variants was screened for the ability to confer an antibiotic resistance on E. coli cells in acidic growth media and not in neutral media, to isolate a variant with a Thr-to-Ile substitution at position 160. An extensive mutagenesis study was then conducted in the proximity of this position, to show that a Leu162Glu mutation also causes the acid preference. Kinetic analyses indicated that the overall activity of the wild-type TEM-1 hardly changes over a pH range from 5.8 to 7.0, whereas TEM-1(T160I) is 1.5-times as active at pH 6.2 than pH 7.0, and TEM-1(T160I) is 3.1-fold as active at pH 5.8 than pH 7.0. A further mutagenesis study suggested that a change in the overall structure of the enzyme underlies the pH dependency of the variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Uncertainty quantification of graph convolution neural network models of evolving processes

The application of neural network models to scientific machine learning tasks has proliferated in recent years. In particular, neural networks have proved to be adept at modeling processes with spatial–temporal complexity. Nevertheless, these highly parameterized models have garnered skepticism in their ability to produce outputs with quantified error bounds over the regimes of interest. Hence there is a need to find uncertainty quantification methods that are suitable for neural networks. In this work we present comparisons of the parametric uncertainty quantification of neural networks modeling complex spatial–temporal processes with Hamiltonian Monte Carlo and Stein variational gradient descent and its projected variant. Specifically we apply these methods to graph convolutional neural network models of evolving systems modeled with recurrent neural network and neural ordinary differential equations architectures. We show that Stein variational inference is a viable alternative to Monte Carlo methods with some clear advantages for complex neural network models. For our exemplars, Stein variational interference gave similar pushed forward uncertainty profiles through time compared to Hamiltonian Monte Carlo, albeit with generally more generous variance. As a result, projected Stein variational gradient descent also produced similar uncertainty profiles to the non-projected counterpart, but large reductions in the active weight space were confounded by the stability of the neural network predictions and the convoluted likelihood landscape.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A mesoscale crystal plasticity model to predict room-temperature deformation and martensitic transformation of high-strength Quenching and Partitioning (Q&P) Steels and validation with synchrotron X-ray diffraction

Renowned for the superior mechanical properties and adeptness at cold-forming, Quenching and Partitioning (QP) steels have gained prominence as a promising candidate material in fabricating safety-critical components in various industries. The pertinent research on QP steels focus on the martensitic transformation of the Retained Austenite (RA) phase during cold-forming, a crucial mechanism that substantially influences the overall strength and ductility of QP steels. The austenite stability and transformation rate heavily rely on the local strain path and the initial microstructure, which is challenging for analytical prediction. In this paper, a mesoscale model is developed to capture the deformation and transformation kinetics of QP steels inside the microstructure. The model integrates the detailed explicit microstructure, acquired from characterization experiments, into a high-resolution finite element (FE) mesh. It distinctly model the deformation and interaction between the various phases and the effect on the transformation of RA. The model is validated with high energy X-ray diffraction (HEXRD) data, and shows excellent capability in predicting the asymmetric stress-strain behavior under uniaxial tension and compression, as well as the martensitic transformation rate. The model is used to investigate the strain and load partitioning effect of surrounding matrix to the transformation of RA, offering insights into the complex behavior of QP980 and facilitates further material development.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Fission yeast Duf89 and Duf8901 are cobalt/nickel-dependent phosphatase–pyrophosphatases that act via a covalent aspartyl–phosphate intermediate

Domain of Unknown Function 89 (DUF89) proteins are metal-dependent phosphohydrolases. Exemplary DUF89 enzymes differ in their metal and phosphosubstrate preferences. Here, we interrogated the activities and structures of two DUF89 paralogs from fission yeast—Duf89 and Duf8901. We find that Duf89 and Duf8901 are cobalt/nickel-dependent phosphohydrolases adept at hydrolyzing p-nitrophenylphosphate and PP i . Crystal structures of metal-free Duf89 and Co 2+ -bound Duf8901 disclosed two enzyme conformations that differed with respect to the position of a three-helix module, which is either oriented away from the active site in Duf89 or forms a lid over the active site in Duf8901. Lid closure results in a 16 Å movement of Duf8901 Asp195, vis-à-vis Asp199 in Duf89, that brings Asp195 into contact with an octahedrally coordinated cobalt. Reaction of Duf8901 with BeCl 2 and NaF in the presence of divalent cations Co 2+ , Ni 2+ , or Zn 2+ generated covalent Duf8901-(Asp248)–beryllium trifluoride (BeF 3 )•Co 2+ , Duf8901-(Asp248)–BeF 3 •Ni 2+ , or Duf8901-(Asp248)–BeF 3 •Zn 2+ adducts, the structures of which suggest a two-step catalytic mechanism via formation and hydrolysis of an enzyme-(aspartyl)–phosphate intermediate. Alanine mutations of Duf8901 Asp248, Asn249, Lys401, Asp286, and Asp195 that interact with BeF 3 •Co 2+ squelched p-nitrophenylphosphatase activity. A 1.8 Å structure of a Duf8901-(Asp248)–AlF 4 –OH 2 •Co 2+ transition-state mimetic suggests an associative mechanism in which Asp195 and Asp363 orient and activate the water nucleophile. Whereas deletion of the duf89 gene elicited a phenotype in which expression of phosphate homeostasis gene pho1 was derepressed, deleting duf8901 did not, thereby hinting that the DUF89 paralogs have distinct functional repertoires in vivo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Object detection with deep learning for rare event search in the GADGET II TPC

In the pursuit of identifying rare two-particle events within the GADGET II Time Projection Chamber (TPC), this paper presents a comprehensive approach for leveraging Convolutional Neural Networks (CNNs) and various data processing methods. To address the inherent complexities of 3D TPC track reconstructions, the data is expressed in 2D projections and 1D quantities. This approach capitalizes on the diverse data modalities of the TPC, allowing for the efficient representation of the distinct features of the 3D events, with no loss in topology uniqueness. Additionally, it leverages the computational efficiency of 2D CNNs and benefits from the extensive availability of pre-trained models. Given the scarcity of real training data for the rare events of interest, simulated events are used to train the models to detect real events. To account for potential distribution shifts when predominantly depending on simulations, significant perturbations are embedded within the simulations. This produces a broad parameter space that works to account for potential physics parameter and detector response variations and uncertainties. These parameter-varied simulations are used to train sensitive 2D CNN object detectors. When combined with 1D histogram peak detection algorithms, this multi-modal detection framework is highly adept at identifying rare, two-particle events in data taken during experiment 21072 at the Facility for Rare Isotope Beams (FRIB), demonstrating a 100% recall for events of interest. Here, we present the methods and outcomes of our investigation and discuss the potential future applications of these techniques.

Convolutional neural network↗
DOE OSTI2015

Metallothionein blocks oxidative DNA damage induced by acute inorganic arsenic exposure

We studied how protein metallothionein (MT) impacts arsenic-induced oxidative DNA damage (ODD) using cells that poorly express MT (MT-I/II double knockout embryonic cells; called MT-null cells) and wild-type (WT) MT competent cells. Arsenic (as NaAsO{sub 2}) was less cytolethal over 24 h in WT cells (LC{sub 50} = 11.0 ± 1.3 μM; mean ± SEM) than in MT-null cells (LC{sub 50} = 5.6 ± 1.2 μM). ODD was measured by the immuno-spin trapping method. Arsenic (1 or 5 μM; 24 h) induced much less ODD in WT cells (121% and 141% of control, respectively) than in MT-null cells (202% and 260%). In WT cells arsenic caused concentration-dependent increases in MT expression (transcript and protein), and in the metal-responsive transcription factor-1 (MTF-1), which is required to induce the MT gene. In contrast, basal MT levels were not detectable in MT-null cells and unaltered by arsenic exposure. Transfection of MT-I gene into the MT-null cells markedly reduced arsenic-induced ODD levels. The transport genes, Abcc1 and Abcc2 were increased by arsenic in WT cells but either showed no or very limited increases in MT-null cells. Arsenic caused increases in oxidant stress defense genes HO-1 and GSTα2 in both WT and MT-null cells, but to much higher levels in WT cells. WT cells appear more adept at activating metal transport systems and oxidant response genes, although the role of MT in these responses is unclear. Overall, MT protects against arsenic-induced ODD in MT competent cells by potential sequestration of scavenging oxidant radicals and/or arsenic. - Highlights: • Metallothionein blocks arsenic toxicity. • Metallothionein reduces arsenic-induced DNA damage. • Metallothionein may bind arsenic or radicals produced by arsenic.

60 APPLIED LIFE SCIENCES↗