108 research outputs found

    Phenotypic redshifts with self-organizing maps: A novel method to characterize redshift distributions of source galaxies for weak lensing

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    Wide-field imaging surveys such as the Dark Energy Survey (DES) rely on coarse measurements of spectral energy distributions in a few filters to estimate the redshift distribution of source galaxies. In this regime, sample variance, shot noise, and selection effects limit the attainable accuracy of redshift calibration and thus of cosmological constraints. We present a new method to combine wide-field, few-filter measurements with catalogs from deep fields with additional filters and sufficiently low photometric noise to break degeneracies in photometric redshifts. The multi-band deep field is used as an intermediary between wide-field observations and accurate redshifts, greatly reducing sample variance, shot noise, and selection effects. Our implementation of the method uses self-organizing maps to group galaxies into phenotypes based on their observed fluxes, and is tested using a mock DES catalog created from N-body simulations. It yields a typical uncertainty on the mean redshift in each of five tomographic bins for an idealized simulation of the DES Year 3 weak-lensing tomographic analysis of σΔz=0.007\sigma_{\Delta z} = 0.007, which is a 60% improvement compared to the Year 1 analysis. Although the implementation of the method is tailored to DES, its formalism can be applied to other large photometric surveys with a similar observing strategy.Comment: 24 pages, 11 figures; matches version accepted to MNRA

    In vitro Anticancer Screening of 24 Locally Used Nigerian Medicinal Plants

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    Background: Plants that are used as traditional medicine represent a relevant pool for selecting plant candidates that may have anticancer properties. In this study, the ethnomedicinal approach was used to select several medicinal plants native to Nigeria, on the basis of their local or traditional uses. The collected plants were then evaluated for cytoxicity. Methods: The antitumor activity of methanolic extracts obtained from 24 of the selected plants, were evaluated in vitro on five human cancer cell lines. Results: Results obtained from the plants screened indicate that 18 plant extracts of folk medicine exhibited promising cytotoxic activity against human carcinoma cell lines. Erythrophleum suaveolens (Guill. & Perr.) Brenan was found to demonstrate potent anti-cancer activity in this study exhibiting IC50 = 0.2-1.3 μ\mug/ml. Conclusions: Based on the significantly potent activity of some plants extracts reported here, further studies aimed at mechanism elucidation and bio-guided isolation of active anticancer compounds is currently underway.Chemistry and Chemical Biolog

    Association between HSV1 Seropositivity and Obesity: Data from the National Health and Nutritional Examination Survey, 2007–2008

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    BACKGROUND: Herpes simplex virus (HSV) is among the most common sexually transmitted pathogens in the United States and worldwide. HSV has a high incidence of undetected cases. In addition, there is no treatment, and there is a lack of knowledge why disparities among populations exist. Research studies suggest that fat tissue may participate in body's immune responses, and the impact of obesity on susceptibility to HSV1 infection is not clear. The purpose of this study was to examine whether obesity is a risk factor for HSV1 infection using a large sample from the general population. METHODS/PRINCIPAL FINDINGS: This cross-sectional study used data from the National Health and Examination and Nutritional Examination Survey (NHANES) from 2007-2008. Variables, gender, age, race/ethnicity, marital status, education, poverty level, and diabetes represented potential confounders and were included in analyses. The two-tailed Pearson's chi square, student's t test, and a multiple logistic regression analysis were applied to evaluate associations using a significance value of p≤0.05. Adjusted odds ratios with 95% confidence interval represented the degree of these associations. The prevalence of HSV1 infection in US population between 20 and 49 years old was 60.3% (n = 1,536). In this study, having a BMI classified as the obese group (BMI 30-39.9) was significantly associated with HSV1 infection before [unadjusted OR = 1.74 (95% CI 1.20-2.51), p = 0.006] and after controlling for socio-demographic factors [adjusted OR = 1.50 (95%CI 1.06-2.13)], p = 0.026]. This association was stronger than three already established risk factors of age, female gender, and poverty level. CONCLUSIONS/SIGNIFICANCE: This study provides evidence that obesity may play a role in the susceptibility to HSV1 infection. Findings from this study suggest that obesity should be considered when designing preventive measures for HSV1 infection. These results may also explain why some people acquire HSV1 infections and some do not. Further, these findings may justify an increased emphasis on the control and prevention of HSV1 transmission and other pathogens in overweight and obese populations

    A GWAS in Latin Americans highlights the convergent evolution of lighter skin pigmentation in Eurasia

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    We report a genome-wide association scan in >6,000 Latin Americans for pigmentation of skin and eyes. We found eighteen signals of association at twelve genomic regions. These include one novel locus for skin pigmentation (in 10q26) and three novel loci for eye pigmentation (in 1q32, 20q13 and 22q12). We demonstrate the presence of multiple independent signals of association in the 11q14 and 15q13 regions (comprising the GRM5/TYR and HERC2/OCA2 genes, respectively) and several epistatic interactions among independently associated alleles. Strongest association with skin pigmentation at 19p13 was observed for an Y182H missense variant (common only in East Asians and Native Americans) in MFSD12, a gene recently associated with skin pigmentation in Africans. We show that the frequency of the derived allele at Y182H is significantly correlated with lower solar radiation intensity in East Asia and infer that MFSD12 was under selection in East Asians, probably after their split from Europeans

    Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

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    We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source" galaxies and magnification biases of nearer "lens" galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1–8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses

    Dark Energy Survey Year 3 results: marginalization over redshift distribution uncertainties using ranking of discrete realizations

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    Cosmological information from weak lensing surveys is maximized by sorting source galaxies into tomographic redshift subsamples. Any uncertainties on these redshift distributions must be correctly propagated into the cosmological results. We present hyperrank, a new method for marginalizing over redshift distribution uncertainties, using discrete samples from the space of all possible redshift distributions, improving over simple parametrized models. In hyperrank, the set of proposed redshift distributions is ranked according to a small (between one and four) number of summary values, which are then sampled, along with other nuisance parameters and cosmological parameters in the Monte Carlo chain used for inference. This approach can be regarded as a general method for marginalizing over discrete realizations of data vector variation with nuisance parameters, which can consequently be sampled separately from the main parameters of interest, allowing for increased computational efficiency. We focus on the case of weak lensing cosmic shear analyses and demonstrate our method using simulations made for the Dark Energy Survey (DES). We show that the method can correctly and efficiently marginalize over a wide range of models for the redshift distribution uncertainty. Finally, we compare hyperrank to the common mean-shifting method of marginalizing over redshift uncertainty, validating that this simpler model is sufficient for use in the DES Year 3 cosmology results presented in companion papers

    Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations

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    As the statistical power of galaxy weak lensing reaches per cent level precision, large, realistic, and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as survey depths increase. To capture the coupled effects of blending in both shear and photometric redshift calibration, we define the effective redshift distribution for lensing, nγ(z), and describe how to estimate it using image simulations. We use an extensive suite of tailored image simulations to characterize the performance of the shear estimation pipeline applied to the Dark Energy Survey (DES) Year 3 data set. We describe the multiband, multi-epoch simulations, and demonstrate their high level of realism through comparisons to the real DES data. We isolate the effects that generate shear calibration biases by running variations on our fiducial simulation, and find that blending-related effects are the dominant contribution to the mean multiplicative bias of approximately −2rmpercent-2{{ rm per cent}}. By generating simulations with input shear signals that vary with redshift, we calibrate biases in our estimation of the effective redshift distribution, and demonstrate the importance of this approach when blending is present. We provide corrected effective redshift distributions that incorporate statistical and systematic uncertainties, ready for use in DES Year 3 weak lensing analyses

    Dark Energy Survey year 3 results: Constraints on cosmological parameters and galaxy-bias models from galaxy clustering and galaxy-galaxy lensing using the redMaGiC sample

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    We constrain cosmological parameters and galaxy-bias parameters using the combination of galaxy clustering and galaxy-galaxy lensing measurements from the Dark Energy Survey (DES) year-3 data. We describe our modeling framework and choice of scales analyzed, validating their robustness to theoretical uncertainties in small-scale clustering by analyzing simulated data. Using a linear galaxy-bias model and redMaGiC galaxy sample, we obtain 10% constraints on the matter density of the Universe. We also implement a nonlinear galaxy-bias model to probe smaller scales that includes parametrization based on hybrid perturbation theory and find that it leads to a 17% gain in cosmological constraining power. We perform robustness tests of our methodology pipeline and demonstrate stability of the constraints to changes in the theory model. Using the redMaGiC galaxy sample as foreground lens galaxies and adopting the best-fitting cosmological parameters from DES year-1 data, we find the galaxy clustering and galaxy-galaxy lensing measurements to exhibit significant signals akin to decorrelation between galaxies and mass on large scales, which is not expected in any current models. This likely systematic measurement error biases our constraints on galaxy bias and the S8 parameter. We find that a scale-, redshift-and sky-Area-independent phenomenological decorrelation parameter can effectively capture this inconsistency between the galaxy clustering and galaxy-galaxy lensing. We trace the source of this correlation to a color-dependent photometric issue and minimize its impact on our result by changing the selection criteria of redMaGiC galaxies. Using this new sample, our constraints on the S8 parameter are consistent with previous studies and we find a small shift in the ωm constraints compared to the fiducial redMaGiC sample. We infer the constraints on the mean host-halo mass of the redMaGiC galaxies in this new sample from the large-scale bias constraints, finding the galaxies occupy halos of mass approximately 1.6×10 13 M⊙/h
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