43 research outputs found
Calibrating Long Period Variables as Standard Candles with Machine Learning
Variable stars with well-calibrated period-luminosity relationships provide
accurate distance measurements to nearby galaxies and are therefore a vital
tool for cosmology and astrophysics. While these measurements typically rely on
samples of Cepheid and RR-Lyrae stars, abundant populations of luminous
variable stars with longer periods of days remain largely unused.
We apply machine learning to derive a mapping between lightcurve features of
these variable stars and their magnitude to extend the traditional
period-luminosity (PL) relation commonly used for Cepheid samples. Using
photometric data for long period variable stars in the Large Magellanic cloud
(LMC), we demonstrate that our predictions produce residual errors comparable
to those obtained on the corresponding Cepheid population. We show that our
model generalizes well to other samples by performing a blind test on
photometric data from the Small Magellanic Cloud (SMC). Our predictions on the
SMC again show small residual errors and biases, comparable to results that
employ PL relations fitted on Cepheid samples. The residual biases are
complementary between the long period variable and Cepheid fits, which provides
exciting prospects to better control sources of systematic error in
cosmological distance measurements. We finally show that the proposed
methodology can be used to optimize samples of variable stars as standard
candles independent of any prior variable star classification.Comment: 14 pages, 10 figures, 1 table, updated to match the version accepted
by the MNRA
LSST Science Book, Version 2.0
A survey that can cover the sky in optical bands over wide fields to faint
magnitudes with a fast cadence will enable many of the exciting science
opportunities of the next decade. The Large Synoptic Survey Telescope (LSST)
will have an effective aperture of 6.7 meters and an imaging camera with field
of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over
20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with
fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a
total point-source depth of r~27.5. The LSST Science Book describes the basic
parameters of the LSST hardware, software, and observing plans. The book
discusses educational and outreach opportunities, then goes on to describe a
broad range of science that LSST will revolutionize: mapping the inner and
outer Solar System, stellar populations in the Milky Way and nearby galaxies,
the structure of the Milky Way disk and halo and other objects in the Local
Volume, transient and variable objects both at low and high redshift, and the
properties of normal and active galaxies at low and high redshift. It then
turns to far-field cosmological topics, exploring properties of supernovae to
z~1, strong and weak lensing, the large-scale distribution of galaxies and
baryon oscillations, and how these different probes may be combined to
constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at
http://www.lsst.org/lsst/sciboo
Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia
Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the
Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material
We present a survey of the early evolution of 12 Type IIn supernovae (SNe IIn) at ultraviolet and visible light wavelengths. We use this survey to constrain the geometry of the circumstellar material (CSM) surrounding SN IIn explosions, which may shed light on their progenitor diversity. In order to distinguish between aspherical and spherical CSM, we estimate the blackbody radius temporal evolution of the SNe IIn of our sample, following the method introduced by Soumagnac et al. We find that higher-luminosity objects tend to show evidence for aspherical CSM. Depending on whether this correlation is due to physical reasons or to some selection bias, we derive a lower limit between 35% and 66% for the fraction of SNe IIn showing evidence for aspherical CSM. This result suggests that asphericity of the CSM surrounding SNe IIn is common—consistent with data from resolved images of stars undergoing considerable mass loss. It should be taken into account for more realistic modeling of these events
Refined histopathological predictors of BRCA1 and BRCA2 mutation status : a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia
Abstract
Introduction
The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling.
Methods
Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70Â years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach.
Results
ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)).
Conclusions
These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management
A phase 1 study of eribulin mesylate (E7389), a novel microtubule targeting chemotherapeutic agent in children with refractory or recurrent solid tumors (excluding CNS), including lymphomas: a Children's Oncology Group Phase 1 Consortium study (ADVL1314).
Maternal folate genes and aberrant DNA hypermethylation in pediatric acute lymphoblastic leukemia
<div><p>Background</p><p>There is evidence that maternal genotypes in folate-related genes are associated with pediatric acute lymphoblastic leukemia (ALL) independent of offspring genotype. We evaluated the relationship between maternal genotypes in methionine synthase (<i>MTR</i>) and DNA methylation status in ALL to better characterize the molecular mechanism underlying this association.</p><p>Procedure</p><p>We obtained bone marrow samples from 51 patients with ALL at diagnosis and from 6 healthy donors. Mothers of patients provided a saliva sample and were genotyped at 11 tagSNPs in <i>MTR</i>. DNA methylation was measured in bone marrow mononuclear cells of patients and six healthy marrow donors. We used hierarchical clustering to identify patients with a hypermethylator phenotype based on 281 differentially methylated promoter CpGs. We used logistic regression to estimate the effects of maternal genotype on the likelihood of DNA hypermethylation in ALL and Ingenuity Pathway Analysis to identify networks enriched for differentially methylated genes.</p><p>Results</p><p>Twenty-two cases (43%) demonstrated promoter hypermethylation, which was more frequent among those with <i>ETV6-RUNX1</i> fusion and initial white blood cell count < 50 x 10<sup>9</sup>/L. Maternal rs12759827 was associated with aberrant DNA methylation (odds ratio [OR] 4.67, 95% confidence interval 1.46–16.31); non-significantly elevated ORs were observed for all other SNPs. Aberrantly methylated promoter CpGs aligned to genes with known cancer-related functions.</p><p>Discussion</p><p>Maternal folate metabolic genotype may be associated with DNA methylation patterns in ALL in their offspring. Therefore, the effect of maternal genotypes on ALL susceptibility may act through aberrant promoter methylation, which may contribute to the <i>in utero</i> origins of ALL.</p></div