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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Host galaxy spectra and consequences for supernova typing from the SDSS SN survey

We present the spectroscopy from 5254 galaxies that hosted supernovae (SNe) or other transient events in the Sloan Digital Sky Survey II (SDSS-II). Obtained during SDSS-I, SDSS-II, and the Baryon Oscillation Spectroscopic Survey, this sample represents the largest systematic, unbiased, magnitude limited spectroscopic survey of SN host galaxies. Using the host galaxy redshifts, we test the impact of photometric SN classification based on SDSS imaging data with and without using spectroscopic redshifts of the host galaxies. Following our suggested scheme, there are a total of 1166 photometrically classified SNe Ia when using a flat redshift prior and 1126 SNe Ia when the host spectroscopic redshift is assumed. For 1024 (87.8%) candidates classified as likely SNe Ia without redshift information, we find that the classification is unchanged when adding the host galaxy redshift. Using photometry from SDSS imaging data and the host galaxy spectra, we also report host galaxy properties for use in future analysis of SN astrophysics. Finally, we investigate the differences in the interpretation of the light curve properties with and without knowledge of the redshift. Without host galaxy redshifts, we find that SALT2 light curve fits are systematically biased toward lower photometric redshift estimates and redder colors in the limit of low signal-to-noise data. The general improvements in performance of the light curve fitter and the increased diversity of the host galaxy sample highlights the importance of host galaxy spectroscopy for current photometric SN surveys such as the Dark Energy Survey and future surveys such as the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

SPIRAL INSTABILITY CAN DRIVE THERMONUCLEAR EXPLOSIONS IN BINARY WHITE DWARF MERGERS

Thermonuclear, or Type Ia supernovae (SNe Ia), originate from the explosion of carbon–oxygen white dwarfs, and serve as standardizable cosmological candles. However, despite their importance, the nature of the progenitor systems that give rise to SNe Ia has not been hitherto elucidated. Observational evidence favors the double-degenerate channel in which merging white dwarf binaries lead to SNe Ia. Furthermore, significant discrepancies exist between observations and theory, and to date, there has been no self-consistent merger model that yields a SNe Ia. Here we show that a spiral mode instability in the accretion disk formed during a binary white dwarf merger leads to a detonation on a dynamical timescale. This mechanism sheds light on how white dwarf mergers may frequently yield SNe Ia.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Optical and X-ray GRB Fundamental Planes as cosmological distance indicators

ABSTRACT Gamma-ray bursts (GRBs), can be employed as standardized candles, extending the distance ladder beyond Type Ia supernovae (SNe Ia, z = 2.26). We standardize GRBs using the three-dimensional (3D) Fundamental Plane relation (the Dainotti relation) among the rest-frame end time of the X-ray plateau emission, its corresponding luminosity, and the peak prompt luminosity. Combining SNe Ia and GRBs, we constrain ΩM = 0.299 ± 0.009 assuming a flat Λ cold dark matter (ΛCDM) cosmology with and without correcting GRBs for selection biases and redshift evolution. Using a 3D optical Dainotti correlation, we find this sample is as efficacious in the determination of ΩM as the X-ray sample. We trimmed our GRB samples to achieve tighter planes to simulate additional GRBs. We determined how many GRBs are needed as stand-alone probes to achieve a comparable precision on ΩM to the one obtained by SNe Ia only. We reach the same error measurements derived using SNe Ia in 2011 and 2014 with 142 and 284 simulated optical GRBs, respectively, considering the error bars on the variables halved. These error limits will be reached in 2038 and in 2047, respectively. Using a doubled sample (obtained by future machine learning approaches allowing a light-curve reconstruction and the estimates of GRB redshifts when z is unknown) compared to the current sample, with error bars halved we will reach the same precision as SNe Ia in 2011 and 2014, now and in 2026, respectively. If we consider the current SNe precision, this will be reached with 390 optical GRBs by 2054.

Dainotti, M. G.↗
DOE OSTI2018

Measuring the scale dependence of intrinsic alignments using multiple shear estimates

We present a new method for measuring the scale dependence of the intrinsic alignment (IA) contamination to the galaxy–galaxy lensing signal, which takes advantage of multiple shear estimation methods applied to the same source galaxy sample. By exploiting the resulting correlation of both shape noise and cosmic variance, our method can provide an increase in the signal-to-noise of the measured IA signal as compared to methods which rely on the difference of the lensing signal from multiple photometric redshift bins. For a galaxy–galaxy lensing measurement which uses LSST sources and DESI lenses, the signal-to-noise on the IA signal from our method is predicted to improve by a factor of ~2 relative to the method of Blazek et al. (2012), for pairs of shear estimates which yield substantially different measured IA amplitudes and highly correlated shape noise terms. We show that statistical error necessarily dominates the measurement of IAs using our method. We also consider a physically motivated extension of the Blazek et al. (2012) method which assumes that all nearby galaxy pairs, rather than only excess pairs, are subject to IA. In this case, the signal-to-noise of the method of Blazek et al. (2012) is improved.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Monte Carlo control loops for cosmic shear cosmology with DES Year 1 data

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. Monte Carlo control loops (MCCL) is a forward modeling method designed to tackle this problem. It relies on the ultra fast image generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. Here, we present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_ℓ$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, point spread function (PSF), an approximate Bayesian computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and a fast method to estimate the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a nontomographic setting, we derive a set of $C_ℓ$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $Ω_m$, $σ_8$, and intrinsic alignment amplitude $A_{IA}$, defined as $S_8D_{IA}=σ_8(Ω_m/0.3)^{0.5}D_{IA}$, where $D_{IA}=1-0.11(A_{IA}-1)$. We find $S_8D_{IA}=0.8954_{-0.039}^{+0.054}$, where systematics are at the level of roughly 60% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Latent Space Simulation for Carbon Capture Design Optimization

The CO2 capture efficiency in solvent-based carbon capture systems (CCSs) critically depends on the gas-solvent interfacial area (IA), making maximization of IA a foundational challenge in CCS design. While the IA associated with a particular CCS design can be estimated via a computational fluid dynamics (CFD) simulation, using CFD to derive the IAs associated with numerous CCS designs is prohibitively costly. However, previous works such as Deep Fluids (Kim et al., 2019) show that large simulation speed-ups and low error are achievable by replacing CFD simulators with neural-network (NN) surrogates that mimic the CFD simulation process. This raises the possibility for a fast, accurate replacement for a CFD simulator, and thus computationally feasible IA-based CCS-design optimization. As such, here, we explore whether an existing NN-surrogate approach (and variants we develop) can successfully be applied to our complex carbon-capture CFD simulations, with the ultimate goal of obtaining a fast and accurate simulator for our CCS-design application. Our experiments build on the Deep Fluids approach and find that resulting surrogates can produce large speed ups (4000x) while maintaining IA relative errors as low as 4% on unseen CCS configurations (interpolating between configurations seen during training). Thus, despite less faithfulness to the underlying physics of the problem, NN surrogates may be a promising tool for our CCS design optimization problem. Notably, though, the Deep Fluids approach has limitations for our application (such as model non-transferability to CCS-packing changes), which we discuss. We conclude with potential directions for future work that may, like innovations we introduced here (e.g., transformer-based dynamics prediction), improve performance on our complicated dataset of CCS CFD simulations.

AI Surrogate Simulation, Carbon Capture, design op↗
DOE OSTI2024

An Empirical Model For Intrinsic Alignments: Insights From Cosmological Simulations

We extend current models of the halo occupation distribution (HOD) to include a flexible, empirical framework for the forward modeling of the intrinsic alignment (IA) of galaxies. A primary goal of this work is to produce mock galaxy catalogs for the purpose of validating existing models and methods for the mitigation of IA in weak lensing measurements. This technique can also be used to produce new, simulation-based predictions for IA and galaxy clustering. Our model is probabilistically formulated, and rests upon the assumption that the orientations of galaxies exhibit a correlation with their host dark matter (sub)halo orientation or with their position within the halo. We examine the necessary components and phenomenology of such a model by considering the alignments between (sub)halos in a cosmological dark matter only simulation. We then validate this model for a realistic galaxy population in a set of simulations in the Illustris-TNG suite. We create an HOD mock with Illustris-like correlations using our method, constraining the associated IA model parameters, with the $\mathcal{X}$$^{2}_{dof}$ between our model’s correlations and those of Illustris matching as closely as 1.4 and 1.1 for orientation–position and orientation–orientation correlation functions, respectively. By modeling the misalignment between galaxies and their host halo, we show that the 3-dimensional two-point position and orientation correlation functions of simulated (sub)halos and galaxies can be accurately reproduced from quasi-linear scales down to 0.1 $\mathcal{h}$ –1 Mpc. We also find evidence for environmental influence on IA within a halo. Our publicly-available software provides a key component enabling efficient determination of Bayesian posteriors on IA model parameters using observational measurements of galaxy-orientation correlation functions in the highly nonlinear regime.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

WHITE DWARF MERGERS ON ADAPTIVE MESHES. I. METHODOLOGY AND CODE VERIFICATION

The Type Ia supernova (SN Ia) progenitor problem is one of the most perplexing and exciting problems in astrophysics, requiring detailed numerical modeling to complement observations of these explosions. One possible progenitor that has merited recent theoretical attention is the white dwarf (WD) merger scenario, which has the potential to naturally explain many of the observed characteristics of SNe Ia. To date there have been relatively few self-consistent simulations of merging WD systems using mesh-based hydrodynamics. This is the first paper in a series describing simulations of these systems using a hydrodynamics code with adaptive mesh refinement. In this paper we describe our numerical methodology and discuss our implementation in the compressible hydrodynamics code CASTRO, which solves the Euler equations, and the Poisson equation for self-gravity, and couples the gravitational and rotation forces to the hydrodynamics. Standard techniques for coupling gravitation and rotation forces to the hydrodynamics do not adequately conserve the total energy of the system for our problem, but recent advances in the literature allow progress and we discuss our implementation here. We present a set of test problems demonstrating the extent to which our software sufficiently models a system where large amounts of mass are advected on the computational domain over long timescales. Future papers in this series will describe our treatment of the initial conditions of these systems and will examine the early phases of the merger to determine its viability for triggering a thermonuclear detonation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Star Formation, Supernovae, Iron, and α: Consistent Cosmic and Galactic Histories

Recent versions of the observed cosmic star formation history (SFH) have resolved an inconsistency with the stellar mass density history. We show that the revised SFH also scales up the delay-time distribution (DTD) of Type Ia supernovae (SNe Ia), as determined from the observed volumetric SN Ia rate history, aligning it with other field-galaxy SN Ia DTD measurements. The revised-SFH-based DTD has a t{sup −1.1±0.1} form and a Hubble-time-integrated production efficiency of N/M{sub ⋆}=1.3±0.1 SNe Ia per 1000 M{sub ⊙} of formed stellar mass. Using these revised histories and updated empirical iron yields of the various SN types, we re-derive the cosmic iron accumulation history. Core-collapse SNe and SNe Ia have contributed about equally to the total mass of iron in the universe today. We find the track of the average cosmic gas element in the [α/Fe] versus [Fe/H] abundance-ratio plane. The track is broadly similar to the observed main locus of Galactic stars in this plane, indicating a Milky Way (MW) SFH similar in form to the cosmic one. We easily find a simple MW SFH that makes the track closely match this stellar locus. Galaxy clusters appear to have a higher-normalization DTD. This cluster DTD, combined with a short-burst MW SFH peaked at z = 3, produces a track that matches remarkably well the observed “high-α” locus of MW stars, suggesting the halo/thick-disk population has had a galaxy-cluster-like formation mode. Thus, a simple two-component SFH, combined with empirical DTDs and SN iron yields, suffices to closely reproduce the MW’s stellar abundance patterns.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

The Foundation Supernova Survey: Measuring Cosmological Parameters with Supernovae from a Single Telescope

Measurements of the dark energy equation-of-state parameter, w, have been limited by uncertaintyin the selection effects and photometric calibration of $z <0.1$ Type Ia supernovae (SNe Ia). The Foundation Supernova Survey is designed to lower these uncertainties by creating a new sample of $z < 0.1$ SNe Ia observed on the Pan-STARRS system. Here, we combine the Foundation sample with SNe from the Pan-STRRS Medium Deep Survey and measure cosmological parameters with 1,338 SNe from a single telescope and a single, well-calibrated photometric system. For the firsttime, both the low-z and high-z data are predominantly discovered by surveys that do not target pre-selected galaxies, reducing selection bias uncertainties. The $z > 0.1$ data include 875 SNe without spectroscopic classifications and we show that we can robustly marginalize over CC SN contamination. We measure Foundation Hubble residuals to be fainter than the pre-existing low-z Hubble residualsby 0.046±0.027 mag (stat+sys). By combining the SN Ia data with cosmic microwave backgroundconstraints, we find w = -0.938±0.053, consistent with $Λ$CDM. With 463 spectroscopically classified SNe Ia alone, we measure w = -0.933±0.061. Using the more homogeneous and better-characterized Foundation sample gives a 55% reduction in the systematic uncertainty attributed to SN Ia sampleselection biases. Although use of just a single photometric system at low and high redshift increases the impact of photometric calibration uncertainties in this analysis, previous low-z samples may have correlated calibration uncertainties that were neglected in past studies. The full Foundation sample will observe up to 800 SNe to anchor the LSST and WFIRST Hubble diagrams.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The HST See Change Program. I. Survey Design, Pipeline, and Supernova Discoveries*

The See Change survey was designed to make z > 1 cosmological measurements by efficiently discovering high-redshift Type Ia supernovae (SNe Ia) and improving cluster mass measurements through weak lensing. This survey observed twelve galaxy clusters with the Hubble Space Telescope (HST) spanning the redshift range z = 1.13–1.75, discovering 57 likely transients and 27 likely SNe Ia at z ~ 0.8–2.3. As in similar previous surveys, this proved to be a highly efficient use of HST for supernova observations; the See Change survey additionally tested the feasibility of maintaining, or further increasing, the efficiency at yet higher redshifts, where we have less detailed information on the expected cluster masses and star formation rates. Furthermore, we find that the resulting number of SNe Ia per orbit is a factor of ~8 higher than for a field search, and 45% of our orbits contained an active SN Ia within 22 rest-frame days of peak, with one of the clusters by itself yielding 6 of the SNe Ia. We present the survey design, pipeline, and supernova discoveries. Novel features include fully blinded supernova searches, the first random forest candidate classifier for undersampled IR data (with a 50% detection threshold within 0.05 mag of human searchers), real-time forward-modeling photometry of candidates, and semi-automated photometric classifications and follow-up forecasts. We also describe the spectroscopic follow-up, instrumental in measuring host galaxy redshifts. The cosmology analysis of our sample will be presented in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Is the expansion of the universe accelerating? All signs point to yes

The accelerating expansion of the universe is one of the most profound discoveries in modern cosmology, suggesting a universe in which 70% of the mass-energy density has an unknown form spread uniformly across the universe. This result has been well established using a combination of cosmological probes, resulting in a “standard model” of modern cosmology that is a combination of a cosmological constant with cold dark matter and baryons. The first compelling evidence for the acceleration came in the late 1990s, when two independent teams studying Type Ia supernovae discovered that distant SNe Ia were dimmer than expected. The combined analysis of modern cosmology experiments, including SNe Ia, the Hubble constant, baryon acoustic oscillations, and the cosmic microwave background, has now measured the contributions of matter and the cosmological constant to the energy density of the universe to better than 0.01, providing a secure measurement of acceleration. A recent study has claimed that the evidence for acceleration from SNe Ia is “marginal.” Here we demonstrate errors in that analysis that reduce the acceleration significance from SNe Ia, and further demonstrate that conservative constraints on the curvature or matter density of the universe increase the significance even more. Analyzing the Joint Light-curve Analysis supernova sample, we find 4.2σ evidence for acceleration with SNe Ia alone, and 11.2σ in a flat universe. With our improved supernova analysis and not rejecting all other cosmological constraints, we find that acceleration is quite secure.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

The Examination of Individual Factors and AFTE Training Outcomes

Introduction: Motion sickness is common among military aviators. It describes a specific group of symptoms that include epigastric awareness, nausea, pallor, sweating, salivation, and fatigue. Occurrences of these symptoms can pose a significant risk to safety and adversely impact mission success. Accordingly, researchers have developed specific interventions to act as countermeasures. For example, Autogenic Feedback Training Exercise has been empirically validated as a training method that mitigates the impact of motion sickness. However, it remains unclear the extent to which individual factors moderate (or mediate) the effects of this intervention. The examination of individual factors such as interoceptive accuracy (IA) and specific personality traits might provide insight into whom may benefit most from AFTE. Methods: Participants were administered the Big Five Inventory (BFI) and State Trait Anxiety Inventory (STAI). In addition, they were given an interoceptive accuracy task (i.e., heartbeat counting task). The participants’ reported value was then compared to the actual number of heart beats obtained via ECG. Completion of the IA task was followed by pre- AFTE and Post-AFTE rotating chair tests to evaluate motion sickness and the effects of AFTE training. Results: Participants (n=16) were evaluated on IA, personality factors (i.e., BFI & STAI) and performance on the rotating chair. IA was unrelated to personality traits (p > .05), but inversely related to state anxiety post training (p < .05). Finally, IA did not predict performance (i.e., rotations or minutes tolerated ?) on rotating chair F (1, 14) = 1.18, p> .05). Discussion:(1) IA is unrelated to personality traits as measured by BFI and STAI. (2) Individual factors are unrelated to AFTE training outcome. (3) AFTE training can be beneficial for all.

motion sickness↗
DOE OSTI2019

Monte Carlo Control Loops for Cosmic Shear Cosmology with DES Year 1

Weak lensing by large-scale structure is a powerful probe of cosmology and of the dark universe. This cosmic shear technique relies on the accurate measurement of the shapes and redshifts of background galaxies and requires precise control of systematic errors. The Monte Carlo Control Loops (MCCL) is a forward modelling method designed to tackle this problem. It relies on the Ultra Fast Image Generator (UFig) to produce simulated images tuned to match the target data statistically, followed by calibrations and tolerance loops. We present the first end-to-end application of this method, on the Dark Energy Survey (DES) Year 1 wide field imaging data. We simultaneously measure the shear power spectrum $C_{\ell}$ and the redshift distribution $n(z)$ of the background galaxy sample. The method includes maps of the systematic sources, Point Spread Function (PSF), an Approximate Bayesian Computation (ABC) inference of the simulation model parameters, a shear calibration scheme, and the fast estimation of the covariance matrix. We find a close statistical agreement between the simulations and the DES Y1 data using an array of diagnostics. In a non-tomographic setting, we derive a set of $C_\ell$ and $n(z)$ curves that encode the cosmic shear measurement, as well as the systematic uncertainty. Following a blinding scheme, we measure the combination of $\Omega_m$, $\sigma_8$, and intrinsic alignment amplitude $A_{\rm{IA}}$, defined as $S_8D_{\rm{IA}} = \sigma_8(\Omega_m/0.3)^{0.5}D_{\rm{IA}}$, where $D_{\rm{IA}}=1-0.11(A_{\rm{IA}}-1)$. We find $S_8D_{\rm{IA}}=0.895^{+0.054}_{-0.039}$, where systematics are at the level of roughly 60\% of the statistical errors. We discuss these results in the context of earlier cosmic shear analyses of the DES Y1 data. Our findings indicate that this method and its fast runtime offer good prospects for cosmic shear measurements with future wide-field surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Conceptualizing impact assessment as a learning process

This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values. Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Arsenic methylation capacity in relation to nutrient intake and genetic polymorphisms in one-carbon metabolism

Highlights: • FOLH1 CC, MTR GG, and MTHFD1 GG carriers had better iAs methylation capacity. • Vitamin B12 interacted with FOLH1 c.223 T > C on iAs metabolism. • One-carbon nutrients and genetic variants may jointly influence iAs metabolism. Nutrients and genetic polymorphisms participating in one-carbon metabolism may explain interindividual differences in inorganic arsenic (iAs) methylation capacity, which in turn may account for variations in susceptibility to iAs-induced diseases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Urinary arsenic metabolism in a Western Chinese population exposed to high-dose inorganic arsenic in drinking water: Influence of ethnicity and genetic polymorphisms

To investigate the differences in urinary arsenic metabolism patterns of individuals exposed to a high concentration of inorganic arsenic (iAs) in drinking water, an epidemiological investigation was conducted with 155 individuals living in a village where the arsenic concentration in the drinking water was 969 μg/L. Blood and urine samples were collected from 66 individuals including 51 cases with skin lesions and 15 controls without skin lesions. The results showed that monomethylated arsenic (MMA), the percentage of MMA (%MMA) and the ratio of MMA to iAs (MMA/iAs) were significantly increased in patients with skin lesions as compared to controls, while dimethylated arsenic (DMA), the percentage of DMA (%DMA) and the ratio of DMA to MMA (DMA/MMA) were significantly reduced. The percent DMA of individuals with the Ala/Asp genotype of glutathione S-transferase omega 1 (GSTO1) was significantly lower than those with Ala/Ala. The percent MMA of individuals with the A2B/A2B genotype of arsenic (+ 3 oxidation state) methyltransferase (AS3MT) was significantly lower than those with AB/A2B. The iAs and total arsenic (tAs) content in the urine of a Tibetan population were significantly higher than that of Han and Hui ethnicities, whereas MMA/iAs was significantly lower than that of Han and Hui ethnicities. Our results showed that when exposed to the same arsenic environment, different individuals exhibited different urinary arsenic metabolism patterns. Gender and ethnicity affect these differences and above polymorphisms may be effectors too. - Highlights: • We first survey a village with high iAs content in the drinking water (969 μg/L). • 90 villagers suffered typical skin lesions with a morbidity rate of 58%. • Cases exhibited higher %MMA and MMA/iAs, and lower %DMA and DMA/MMA than controls. • Gender and ethnicity affect the differences of iAs methylation metabolism levels. • GSTO1 and AS3MT gene polymorphisms may be factors too.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Arsenic methylation capacity is associated with breast cancer in northern Mexico

Exposure to environmental contaminants, dietary factors and lifestyles may explain worldwide different breast cancer (BC) incidence. Inorganic arsenic (iAs) in the drinking water is a concern in many regions, such as northern Mexico. Studies in several countries have associated the proportion of urinary monomethylarsenic (%MMA) with increased risks for many As-related diseases, including cancer. To investigate the potential relationships between the risk of BC and the capacity to methylate iAs, a hospital-based case–control study (1016 cases/1028 controls) was performed in northern Mexico. Women were directly interviewed about their reproductive histories. The profile of As metabolites in urine was determined by HPLC-ICP-MS and methylation capacity was assessed by metabolite percentages and indexes. Total urinary As, excluding arsenobetaine (TAs-AsB), ranged from 0.26 to 303.29 μg/L. Most women (86%) had TAs-AsB levels below As biological exposure index (35 μg/L). Women with higher %MMA and/or primary methylation index (PMI) had an increased BC risk (%MMA OR{sub Q5vs.Q1} = 2.63; 95%CI 1.89,3.66; p for trend < 0.001; PMI OR{sub Q5vs.Q1} = 1.90; 95%CI 1.39,2.59, p for trend < 0.001). In contrast, women with higher proportion of urinary dimethylarsenic (%DMA) and/or secondary methylation index (SMI) had a reduced BC risk (%DMA OR{sub Q5vs.Q1} = 0.63; 95%CI 0.45,0.87, p for trend 0.006; SMI OR{sub Q5vsQ1} = 0.42, 95%CI 0.31,0.59, p for trend < 0.001). Neither %iAs nor total methylation index was associated to BC risk. Inter-individual variations in iAs metabolism may play a role in BC carcinogenesis. Women with higher capacity to methylate iAs to MMA and/or a lower capacity to further methylate MMA to DMA were at higher BC risk. - Highlights: • Arsenic methylation capacity is associated to an increased breast cancer (BC) risk. • Women with higher capacity to methylate arsenic to MMA were at higher BC risk. • Women with higher capacity to methylate arsenic to DMA were at lower BC risk. • Associations occurred at urinary As levels near the biological exposure index.

60 APPLIED LIFE SCIENCES↗