Epigenomic regulation of heart failure: integrating histone marks, long noncoding RNAs, and chromatin architecture.

Epigenetic processes are known to have powerful roles in organ development across biology. It has recently been found that some of the chromatin modulatory machinery essential for proper development plays a previously unappreciated role in the pathogenesis of cardiac disease in adults. Investigations using genetic and pharmacologic gain- and loss-of-function approaches have interrogated the function of distinct epigenetic regulators, while the increased deployment of the suite of next-generation sequencing technologies have fundamentally altered our understanding of the genomic targets of these chromatin modifiers. Here, we review recent developments in basic and translational research that have provided tantalizing clues that may be used to unlock the therapeutic potential of the epigenome in heart failure. Additionally, we provide a hypothesis to explain how signal-induced crosstalk between histone tail modifications and long non-coding RNAs triggers chromatin architectural remodeling and culminates in cardiac hypertrophy and fibrosis

Technology -- Climate Interactions in the Green Revolution in India

This paper present a model of the Green Revolution in India, in which the development and diffusion of HYVs, the expansion of irrigation and the expansion of multiple-cropping are treated as endogenous responses to more basic investments in agricultural technology and infrastructure, as well as to climate and edaphic endowments. We incorporate explicit climate-technology interactions in the model, in order to identify climate effects on the diffusion of HYVs, irrigation and multiple- cropping, and on Net Revenue to agriculture. We find that climate affects technology development and diffusion, and that technology development and diffusion affect the impacts of climate on agricultural productivity in India.Green Revolution, India, HYV, Rice, Wheat, Climate, Agricultural Research

Spatial methods for event reconstruction in CLEAN

In CLEAN (Cryogenic Low Energy Astrophysics with Noble gases), a proposed neutrino and dark matter detector, background discrimination is possible if one can determine the location of an ionizing radiation event with high accuracy. We simulate ionizing radiation events that produce multiple scintillation photons within a spherical detection volume filled with liquid neon. We estimate the radial location of a particular ionizing radiation event based on the observed count data corresponding to that event. The count data are collected by detectors mounted at the spherical boundary of the detection volume. We neglect absorption, but account for Rayleigh scattering. To account for wavelength-shifting of the scintillation light, we assume that photons are absorbed and re-emitted at the detectors. Here, we develop spatial Maximum Likelihood methods for event reconstruction, and study their performance in computer simulation experiments. We also study a method based on the centroid of the observed count data. We calibrate our estimates based on training data