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DOE OSTI2023

Bootstrapping outperforms community‐weighted approaches for estimating the shapes of phenotypic distributions

Abstract Estimating phenotypic distributions of populations and communities is central to many questions in ecology and evolution. These distributions can be characterized by their moments (mean, variance, skewness and kurtosis) or diversity metrics (e.g. functional richness). Typically, such moments and metrics are calculated using community‐weighted approaches (e.g. abundance‐weighted mean). We propose an alternative bootstrapping approach that allows flexibility in trait sampling and explicit incorporation of intraspecific variation, and show that this approach significantly improves estimation while allowing us to quantify uncertainty. We assess the performance of different approaches for estimating the moments of trait distributions across various sampling scenarios, taxa and datasets by comparing estimates derived from simulated samples with the true values calculated from full datasets. Simulations differ in sampling intensity (individuals per species), sampling biases (abundance, size), trait data source (local vs. global) and estimation method (two types of community‐weighting, two types of bootstrapping). We introduce the traitstrap R package, which contains a modular and extensible set of bootstrapping and weighted‐averaging functions that use community composition and trait data to estimate the moments of community trait distributions with their uncertainty. Importantly, the first function in the workflow, trait_fill , allows the user to specify hierarchical structures (e.g. plot within site, experiment vs. control, species within genus) to assign trait values to each taxon in each community sample. Across all taxa, simulations and metrics, bootstrapping approaches were more accurate and less biased than community‐weighted approaches. With bootstrapping, a sample size of 9 or more measurements per species per trait generally included the true mean within the 95% CI. It reduced average percent errors by 26%–74% relative to community‐weighting. Random sampling across all species outperformed both size‐ and abundance‐biased sampling. Our results suggest randomly sampling ~9 individuals per sampling unit and species, covering all species in the community and analysing the data using nonparametric bootstrapping generally enable reliable inference on trait distributions, including the central moments, of communities. By providing better estimates of community trait distributions, bootstrapping approaches can improve our ability to link traits to both the processes that generate them and their effects on ecosystems.

Maitner, Brian S.↗

DOE OSTI2018

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon–Cerrado border

Abstract. Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest–savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon–Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961–1990 and interannual climate variability for 1948–2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. Furthermore, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon–Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

P44/WDR77 restricts the sensitivity of proliferating cells to TGFβ signaling

Highlights: • P44/WDR77 causes proliferating cells to become non-responsive to TGFβ signaling. • P44/WDR77 down-regulates TβRII and TβR2 expression. • P44/WDR77 down-regulated TGFβ signaling correlates with lung tumorigenesis. - Abstract: We previously reported that a novel WD-40 domain-containing protein, p44/WDR77, drives quiescent epithelial cells to re-enter the cell cycle and plays an essential role for growth of lung and prostate cancer cells. Transforming growth factor beta (TGFβ) signaling is important in the maintenance of non-transformed cells in the quiescent or slowly cycling stage. However, both non-transformed proliferating cells and human cancer cells are non-responsive to endogenous TGFβ signaling. The mechanism by which proliferating cells become refractory to TGFβ inhibition is not well established. Here, we found that silencing p44/WDR77 increased cellular sensitivity to TGFβ signaling and that this was inversely correlated with decreased cell proliferation. Smad2 or 3 phosphorylation, TGFβ-mediated transcription, and TGFβ2 and TGFβ receptor type II (TβRII) expression were dramatically induced by silencing of p44/WDR77. These data support the hypothesis that p44/WDR77 down-regulates the expression of the TGFβ ligand and its receptor, thereby leading to a cellular non-response to TGFβ signaling. Finally, we found that p44/WDR77 expression was correlated with cell proliferation and decreased TGFβ signaling during lung tumorigenesis. Together, these results suggest that p44/WDR77 expression causes the non-sensitivity of proliferating cells to TGFβ signaling, thereby contributing to cellular proliferation during lung tumorigenesis.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

In Situ Characterization of Mesoporous Co/CeO 2 Catalysts for the High-Temperature Water-Gas Shift

Here, mesoporous Co/CeO 2 catalysts were found to exhibit significant activity for the high-temperature water-gas shift (WGS) reaction with cobalt loadings as low as 1 wt %. The catalysts feature a uniform dispersion of cobalt within the CeO 2 fluorite type lattice with no evidence of discrete cobalt phase segregation. In situ XANES and ambient pressure XPS experiments were used to elucidate the active state of the catalysts as partially reduced cerium oxide doped with oxidized cobalt atoms. In situ XRD and DRIFTS experiments suggest facile cerium reduction and oxygen vacancy formation, particularly with lower cobalt loadings. In situ DRIFTS analysis also revealed the presence of surface carbonate and bidentate formate species under reaction conditions, which may be associated with additional mechanistic pathways for the WGS reaction. Deactivation behavior was observed with higher cobalt loadings. XANES data suggest the formation of small metallic cobalt clusters at temperatures above 400 °C may be responsible. Notably, this deactivation was not observed for the 1% cobalt loaded catalyst, which exhibited the highest activity per unit of cobalt.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

The Dark Energy Survey supernova programme: modelling selection efficiency and observed core-collapse supernova contamination

ABSTRACT The analysis of current and future cosmological surveys of Type Ia supernovae (SNe Ia) at high redshift depends on the accurate photometric classification of the SN events detected. Generating realistic simulations of photometric SN surveys constitutes an essential step for training and testing photometric classification algorithms, and for correcting biases introduced by selection effects and contamination arising from core-collapse SNe in the photometric SN Ia samples. We use published SN time-series spectrophotometric templates, rates, luminosity functions, and empirical relationships between SNe and their host galaxies to construct a framework for simulating photometric SN surveys. We present this framework in the context of the Dark Energy Survey (DES) 5-yr photometric SN sample, comparing our simulations of DES with the observed DES transient populations. We demonstrate excellent agreement in many distributions, including Hubble residuals, between our simulations and data. We estimate the core collapse fraction expected in the DES SN sample after selection requirements are applied and before photometric classification. After testing different modelling choices and astrophysical assumptions underlying our simulation, we find that the predicted contamination varies from 7.2 to 11.7 per cent, with an average of 8.8 per cent and an r.m.s. of 1.1 per cent. Our simulations are the first to reproduce the observed photometric SN and host galaxy properties in high-redshift surveys without fine-tuning the input parameters. The simulation methods presented here will be a critical component of the cosmology analysis of the DES photometric SN Ia sample: correcting for biases arising from contamination, and evaluating the associated systematic uncertainty.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Smaller stellar disc scale lengths in rich environments

Abstract We investigate the dependence of stellar disc scale lengths on environment for a sample of Sloan Digital Sky Survey Data Release 7 galaxies with published photometric bulge-disc decompositions. We compare disc scale lengths at fixed bulge mass for galaxies in an isolated field environment to galaxies in X-ray rich and X-ray poor groups. At low bulge mass, stellar disc scale lengths in X-ray rich groups are smaller compared to discs in both X-ray poor groups and in isolated field environments. This decrease in disc scale length is largely independent of halo mass, though shows some dependence on group-centric distance. We also find that stellar disc scale lengths are smaller in X-ray rich environments for a subset of star-forming galaxies and for galaxies of different morphological types. We note that disc scale lengths of low mass galaxies are known to have large systematic uncertainties, however we focus on differences between samples with the same measurement biases. Our results show that stellar disc scale lengths depend on X-ray brightness, a tracer of IGM density, suggesting a role for hydrodynamic processes such as ram-pressure stripping and/or starvation.

Demers, Melanie L.↗

NASA NTRS2015

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth‐atmosphere system through scattering and absorption of shortwave radiation and the absorption and re‐emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud‐free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two‐channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight‐forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

LaFontaine Frank J.↗

DOE OSTI2016

Quantifying Transient Uncertainty in the BEAVRS Benchmark Using Time Series Analysis Methods

Advances in computation have brought about significant improvements in creating fast-running high-fidelity simulations of nuclear cores. The BEAVRS benchmark is a highly-detailed PWR specification with two cycles of measured operational data used to validate high-fidelity core analysis methods. This PWR depletion benchmark captures the fine details of the LWR fuel assemblies, burnable absorbers, in-core fission detectors, core loading and shuffling patterns. Specifically, 58 of the 193 assemblies contain in-core detectors with measurements taken over 61 axial positions every month. These detectors are U-235 fission chambers with slightly varying mass of U-235. The collected signals are normalized on a given assembly permitting full core comparisons. The fuel layout for cycle 1 and instrument tube locations for the reactor are given in figures 1 and 2 respectively. Through a series of data processing and comparisons, it was shown that axially integrated radial maps of reaction rates were in close agreement between provided detector data and calculated data. More recently, the focus of the BEAVRS project has been on quantifying uncertainty to further assess the validity of aforementioned results. A close investigation of sources of error shows that uncertainties from operational nuclear data arise primarily from data measurements and processing. While the errors in axial realignment and interpolation seem significant, these sources affect only a small subset of data points near grid spacers and do not persist throughout the entire core. Instead, measurement uncertainty from detector count rates and radial integration dominate the uncertainty in measured data are determined as the most significant sources of error. This uncertainty analysis treated each given burnup step as independent of comparable data at neighboring burnup steps. More recent work has been targeted at understanding how reaction rates vary over time, in order to determine whether calculated reaction rates follow any observable trends. This abstract hones in on transient uncertainty quantification, in order to compare observed data against models for transient behavior. The first section of the paper uses linear regression tools to fit operational data, while the latter portion of the paper explores more complex simulation tools to fit operational data. Ultimately, the BEAVRS benchmark aims to serve as a true non-proprietary international benchmark for the validation of high-fidelity tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

The Impact of Freeze‐Thaw History on Soil Carbon Response to Experimental Freeze‐Thaw Cycles

Abstract Freeze‐thaw is a disturbance process in cold regions where permafrost soils are becoming vulnerable to temperature fluctuations above 0°C. Freeze‐thaw alters soil physical and biogeochemical properties with implications for carbon persistence and emissions in Arctic landscapes. We examined whether different freeze‐thaw histories in two soil systems led to contrasting biogeochemical responses under a laboratory‐controlled freeze‐thaw incubation. We investigated controls on carbon composition through Fourier‐transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) to identify nominal carbon oxidation states and relative abundances of aliphatic‐type carbon molecules in both surface and subsurface soils. Soil cores (∼60 cm‐depth) were sampled from two sites in Alaskan permafrost landscapes with different in situ freeze‐thaw characteristics: Healy (>40 freeze‐thaw cycles annually) and Toolik (<15 freeze‐thaw cycles annually). FT‐ICR‐MS was coupled with in situ temperature data and soil properties (i.e., soil texture, mineralogy) to assess (a) differences in soil organic matter composition associated with previous freeze‐thaw history and (b) sensitivity to experimental freeze‐thaw in the extracted cores. Control (freeze‐only) samples showed greater carbon oxidation in Healy soils compared with Toolik, even in lower mineral horizons where freeze‐thaw history was comparable across both sites. Healy showed the most loss of carbon compounds following experimental freeze‐thaw in the lower mineral depths, including a decrease in aliphatics. Toolik soils responded more slowly to freeze‐thaw as shown by intermediary carbon oxidation distributed across multiple carbon compound classes. Variations in the response of permafrost carbon chemistry to freeze‐thaw is an important factor for predicting changes in soil function as permafrost thaws in high northern latitudes.

Rooney, Erin C.↗

DOE OSTI2023

Applications of physics informed neural operators

Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Time for a drought experiment: Do you know your plants’ water status?

Abstract Drought stress is an increasing concern because of climate change and increasing demands on water for agriculture. There are still many unknowns about how plants sense and respond to water limitation, including which genes and cellular mechanisms are impactful for ecology and crop improvement in drought-prone environments. A better understanding of plant drought resistance will require integration of several research disciplines. A common set of parameters to describe plant water status and quantify drought severity can enhance data interpretation and research integration across the research disciplines involved in understanding drought resistance and would be especially useful in integrating the flood of genomic data being generated in drought studies. Water potential (ψw) is a physical measure of the free energy status of water that, along with related physiological measurements, allows unambiguous description of plant water status that can apply across various soil types and environmental conditions. ψw and related physiological parameters can be measured with relatively modest investment in equipment and effort. Thus, we propose that increased use of ψw as a fundamental descriptor of plant water status can enhance the insight gained from many drought-related experiments and facilitate data integration and sharing across laboratories and research disciplines.

Juenger, Thomas E. (ORCID:0000000195509288)↗

DOE OSTI2013

The Decomposition of Hydrazine in the Gas Phase and over an Iridium Catalyst

Hydrazine is an important rocket fuel, used as both a monopropellant and a bipropellant. This paper presents theoretical results to complement the extensive experimental studies of the gas phase and Ir catalyzed decompositions involved in the monopropellant applications of hydrazine. Gas phase electronic structure theory calculations that include electron correlation predict that numerous molecular and free radical reactions occur within the same energy range as the basic free radical pathways: NN bond breaking around 65 kcal/mol and NH bond breaking around 81 kcal/mol. The data suggest that a revision to existing kinetics modeling is desirable, based on the energetics and the new elementary steps reported herein. A supported Ir-6 octahedron model for the Shell 405 Iridium catalyst used in thrusters was developed. Self-Consistent Field and electron correlation calculations (with core potentials and associated basis sets) find a rich chemistry for hydrazine on this catalyst model. The model catalyst provides dramatically lower NN and NH bond cleavage energies and an even smaller barrier to breaking the NH bond by NH2 abstractions. Thus, the low temperature decomposition over the catalyst is interpreted in terms of consecutive NH2 abstractions to produce ammonia and nitrogen. The higher temperature channel, which has hydrogen and nitrogen products, may be due to a mixture of two mechanisms. These two mechanisms are successive NH cleavages with surface H + H recombinations, and the same type of assisted H-2 eliminations found to occur in the gas phase part of this study.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Increasing the Pressure‐Free Stripping Capacity of the Lithium Metal Anode in Solid‐State‐Batteries by Carbon Nanotubes

Abstract Lithium metal is the key anode material for solid‐state‐batteries as its successful implementation will drastically increase their energy and power densities. However, anode contact loss during stripping leads to dendrites upon plating and subsequent cell failure. Design strategies to mitigate these issues are crucial to enable the use of lithium metal anodes. This paper reports the dissolution kinetics of composite anodes made of lithium metal and carbon nanotubes (CNTs) with a garnet‐type solid electrolyte (SE). In addition to an enhancement of the effective diffusion within the anode, its dissolution is fundamentally changed from being 2D to 3D. By maintaining contact with the SE, the CNTs facilitate lithium transport to the interface, which yields more than 20 mAh cm −2 discharge capacity at 100 µ A cm −2 without the application of external stack pressure ( > 1 MPa). Conclusions drawn from electrochemical data on the anode microstructure are validated using cryo‐focused‐ion‐beam scanning electron microscopy and correlated with the mechanical properties. Micro‐indentation, acoustic analysis, and stress–strain testing show that mechanical properties of the anode, like yield strength and hardness, are adjustable. Overall, it is shown that the mechanical and electrochemical properties of Li–CNT composite electrodes can be tailored to suit the requirements of a practical cell.

Fuchs, Till↗

DOE OSTI2014

Implications of caspase-dependent proteolytic cleavage of cyclin A1 in DNA damage-induced cell death

Highlights: • Caspase-1 mediates doxorubicin-induced downregulation of cyclin A1. • Active caspase-1 effectively cleaved cyclin A1 at D165. • Cyclin A1 expression is involved in DNA damage-induced cell death. - Abstract: Cyclin A1 is an A-type cyclin that directly binds to CDK2 to regulate cell-cycle progression. In the present study, we found that doxorubicin decreased the expression of cyclin A1 at the protein level in A549 lung cancer cells, while markedly downregulating its mRNA levels. Interestingly, doxorubicin upregulated caspase-1 in a concentration-dependent manner, and z-YAVD-fmk, a specific inhibitor of caspase-1, reversed the doxorubicin-induced decrease in cyclin A1 in A549 lung cancer and MCF7 breast cancer cells. Active caspase-1 effectively cleaved cyclin A1 at D165 into two fragments, which in vitro cleavage assays showed were further cleaved by caspase-3. Finally, we found that overexpression of cyclin A1 significantly reduced the cytotoxicity of doxorubicin, and knockdown of cyclin A1 by RNA interference enhanced the sensitivity of cells to ionizing radiation. Our data suggest a new mechanism for the downregulation of cyclin A1 by DNA-damaging stimuli that could be intimately involved in the cell death induced by DNA damage-inducing stimuli, including doxorubicin and ionizing radiation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

A galaxy-driven model of type Ia supernova luminosity variations

ABSTRACT Type Ia supernovae (SNe Ia) are used as standardizable candles to measure cosmological distances, but differences remain in their corrected luminosities which display a magnitude step as a function of host galaxy properties such as stellar mass and rest-frame U−R colour. Identifying the cause of these steps is key to cosmological analyses and provides insight into SN physics. Here we investigate the effects of SN progenitor ages on their light-curve properties using a galaxy-based forward model that we compare to the Dark Energy Survey 5-yr SN Ia sample. We trace SN Ia progenitors through time and draw their light-curve width parameters from a bimodal distribution according to their age. We find that an intrinsic luminosity difference between SNe of different ages cannot explain the observed trend between step size and SN colour. The data split by stellar mass are better reproduced by following recent work implementing a step in total-to-selective dust extinction ratio (RV) between low- and high-mass hosts, although an additional intrinsic luminosity step is still required to explain the data split by host galaxy U−R. Modelling the RV step as a function of galaxy age provides a better match overall. Additional age versus luminosity steps marginally improve the match to the data, although most of the step is absorbed by the width versus luminosity coefficient α. Furthermore, we find no evidence that α varies with SN age.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture

Abstract. The use of wireless sensor networks to measure soil parameters eliminates the need to remove sensors for field operations, such as tillage, thus allowing long-term measurements without multiple disturbances to soil structure. Wireless sensors also reduce above-ground cables and the risk of undesired equipment damage and potential data loss. However, implementing wireless sensor networks in field studies usually requires advanced and costly engineering knowledge. This study presents a new underground, wireless, open-source, low-cost system for monitoring soil oxygen, temperature, and soil moisture. The process of system design, assembly, programming, deployment, and power management is presented. The system can be left underground for several years without the need to change the battery. Emphasis was given on modularity so that it can be easily duplicated or changed if needed and deployed without previous engineering knowledge. Data from this type of system have a wide range of applications, including precision agriculture and high-resolution modelling.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Hybrid functional band gap calculation of SnO{sub 6} containing perovskites and their derived structures

We have studied the properties of SnO{sub 6} octahedra-containing perovskites and their derived structures using ab initio calculations with different density functionals. In order to predict the correct band gap of the materials, we have used B3LYP hybrid density functional, and the results of B3LYP were compared with those obtained using the local density approximation and generalized gradient approximation data. The calculations have been conducted for the orthorhombic ground state of the SnO{sub 6} containing perovskites. We also have expended the hybrid density functional calculation to the ASnO{sub 3}/A'SnO{sub 3} system with different cation orderings. We propose an empirical relationship between the tolerance factor and the band gap of SnO{sub 6} containing oxide materials based on first principles calculation. - Graphical abstract: (a) Structure of ASnO{sub 3} for orthorhombic ground state. The green ball is A (Ba, Sr, Ca) cation and the small (red) ball on edge is oxygen. SnO{sub 6} octahedrons are plotted as polyhedron. (b) Band gap of ASnO{sub 3} as a function of the tolerance factor for different density functionals. The experimental values of the band gap are marked as green pentagons. (c) ASnO{sub 3}/A'SnO{sub 3} superlattices with two types cation arrangement: [001] layered structure and [111] rocksalt structure, respectively. (d) B3LYP hybrid functional band gaps of ASnO{sub 3}, [001] ordered superlattices, and [111] ordered superlattices of ASnO{sub 3}/A'SnO{sub 3} as a function of the effective tolerance factor. Note the empirical linear relationship between the band gap and effective tolerance factor. - Highlights: • We report the hybrid functional band gap calculation of ASnO{sub 3} and ASnO{sub 3}/A'SnO{sub 3}. • The band gap of ASnO{sub 3} using B3LYP functional reproduces the experimental value. • We propose the linear relationship between the tolerance factor and the band gap.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2015

Mechanism for Clastogenic Activity of Naphthalene: Quarterly Technical Progress Report, March 2015

The project has two main goals: 1) Identify the types of adducts naphthalene (NA) forms with DNA and 2) determine whether adduct formation correlates with site selective tumor formation in defined subcompartments of the respiratory tract (respiratory and olfactory nasal epithelium and airways of mice, rats and rhesus monkeys). Five tasks are associated with the completion of the goals. Task 1: Contracting and Animal Use Approvals. IACUC and ACURO approvals are complete, The subcontract with UC Davis (UCD) was executed in December 2014. Task 2: Perform In Vitro Study for Goal 1. Rat samples exposed in December 2014. Task 3: Perform In Vitro Study for Goal 2. Mouse ex vivo samples completed. Rat and monkey samples need to be completed in the next quarter. Task 4: Sample Preparation and Analysis. Mouse Goal 2 samples completed. Other samples to remain to be done. Task 5: Data Interpretation and Reporting. Waiting for more data. Insufficient data to submit abstract to SOT by mid January 2015 deadline.

59 BASIC BIOLOGICAL SCIENCES↗