Implications of a transition in the dark energy equation of state for the H-0 and sigma(8) tensions
JOURNAL OF COSMOLOGY AND ASTROPARTICLE PHYSICS 2019:12 (2019) 35
Abstract:
© 2019 IOP Publishing Ltd and Sissa Medialab. We explore the implications of a rapid appearance of dark energy between the redshifts (z) of one and two on the expansion rate and growth of perturbations. Using both Gaussian process regression and a parametric model, we show that this is the preferred solution to the current set of low-redshift (z<3) distance measurements if H0=73 km s-1 Mpc-1 to within 1% and the high-redshift expansion history is unchanged from the ΛCDM inference by the Planck satellite. Dark energy was effectively non-existent around z=2, but its density is close to the ΛCDM model value today, with an equation of state greater than-1 at z<0.5. If sources of clustering other than matter are negligible, we show that this expansion history leads to slower growth of perturbations at z<1, compared to ΛCDM, that is measurable by upcoming surveys and can alleviate the σ8 tension between the Planck CMB temperature and low-redshift probes of the large-scale structure.Integrated Analysis of Structural Variation and RNA Expression of FGFR2 and Its Splicing Modulator ESRP1 Highlight the ESRP1amp-FGFR2norm-FGFR2-IIIchigh Axis in Diffuse Gastric Cancer.
Cancers 12:1 (2019) E70
Abstract:
Gastric Cancer (GC) is one of the most common and deadliest types of cancer in the world. To improve GC prognosis, increasing efforts are being made to develop new targeted therapies. Although FGFR2 genetic amplification and protein overexpression in GC have been targeted in clinical trials, so far no improvement in patient overall survival has been found. To address this issue, we studied genetic and epigenetic events affecting FGFR2 and its splicing regulator ESRP1 in GC that could be used as new therapeutic targets or predictive biomarkers. We performed copy number variation (CNV), DNA methylation, and RNA expression analyses of FGFR2/ESRP1 across several cohorts. We discovered that both genes were frequently amplified and demethylated in GC, resulting in increased ESRP1 expression and of a specific FGFR2 isoform: FGFR2-IIIb. We also showed that ESRP1 amplification in GC correlated with a significant decreased expression of FGFR2-IIIc, an alternative FGFR2 splicing isoform. Furthermore, when we performed a survival analysis, we observed that patients harboring diffuse-type tumors with low FGFR2-IIIc expression revealed a better overall survival than patients with FGFR2-IIIc high-expressing diffuse tumors. Our results encourage further studies on the role of ESRP1 in GC and support FGFR2-IIIc as a relevant biomarker in GC.Disconnected pseudo-Cℓ covariances for projected large-scale structure data
Journal of Cosmology and Astroparticle Physics IOP Publishing 2019:11 (2019) 043-043
Disconnected pseudo-Cℓ covariances for projected large-scale structure data
Journal of Cosmology and Astroparticle Physics IOP Publishing 2019:11 (2019) 043
Abstract:
The disconnected part of the power spectrum covariance matrix (also known as the "Gaussian" covariance) is the dominant contribution on large scales for galaxy clustering and weak lensing datasets. The presence of a complicated sky mask causes non-trivial correlations between different Fourier/harmonic modes, which must be accurately characterized in order to obtain reliable cosmological constraints. This is particularly relevant for galaxy survey data. Unfortunately, an exact calculation of these correlations involves O(ℓmax6) operations that become computationally impractical very quickly. We present an implementation of approximate methods to estimate the Gaussian covariance matrix of power spectra involving spin-0 and spin-2 flat- and curved-sky fields, expanding on existing algorithms {developed in the context of CMB analyses}. These methods achieve an O(ℓmax3) scaling, which makes the computation of the covariance matrix as fast as the computation of the power spectrum itself. We quantify the accuracy of these methods on large-scale structure and weak lensing data, making use of a large number of Gaussian but otherwise realistic simulations. We show that, using the approximate covariance matrix, we are able to recover the true posterior distribution of cosmological parameters to high accuracy. We also quantify the shortcomings of these methods, which become unreliable on the very largest scales, as well as for covariance matrix elements involving cosmic shear B modes. The algorithms presented here are implemented in the public code NaMaster https://github.com/LSSTDESC/NaMaster.The impact of the connectivity of the cosmic web on the physical properties of galaxies at its nodes
Monthly Notices of the Royal Astronomical Society Oxford University Press 491:3 (2019) 4294-4309