Stellar activity cycles and contribution of the deep layers knowledge

It is believed that magnetic activity on the Sun and solar-type stars are tightly related to the dynamo process driven by the interaction between rotation, convection, and magnetic field. However, the detailed mechanisms of this process are still incompletely understood. Many questions remain unanswered, e.g.: why some stars are more active than others?; why some stars have a flat activity?; why is there a Maunder minimum?; are all the cycles regular? A large number of prox- ies are typically used to study the magnetic activity of stars as we cannot resolve stellar discs. Recently, it was shown that asteroseismology can also be used to study stellar activity, making it an even more powerful tool. If short cycles are not so un- common, we expect to detect many of them with missions such as CoRoT, Kepler, and possibly the PLATO mission. We will review some of the latest results obtained with spectroscopic measurements. We will show how asteroseismology can help us to better understand the complex process of dynamo and illustrate how the CoRoT and Kepler missions are revolutionizing our knowledge on stellar activity. A new window is being opened over our understanding of the magnetic variability of stars.Comment: 7 pages. To appear in Astrophysics and Space Science Proceedings series of the 20th Stellar pulsation conference held in Granada (Spain) from 6 to 10 September 2011

The Complete Nucleotide Sequence of the Coffee (Coffea Arabica L.) Chloroplast Genome: Organization and Implications for Biotechnology and Phylogenetic Relationships Amongst Angiosperms

The chloroplast genome sequence of Coffea arabica L., the first sequenced member of the fourth largest family of angiosperms, Rubiaceae, is reported. The genome is 155 189 bp in length, including a pair of inverted repeats of 25 943 bp. Of the 130 genes present, 112 are distinct and 18 are duplicated in the inverted repeat. The coding region comprises 79 protein genes, 29 transfer RNA genes, four ribosomal RNA genes and 18 genes containing introns (three with three exons). Repeat analysis revealed five direct and three inverted repeats of 30 bp or longer with a sequence identity of 90% or more. Comparisons of the coffee chloroplast genome with sequenced genomes of the closely related family Solanaceae indicated that coffee has a portion of rps19 duplicated in the inverted repeat and an intact copy of infA. Furthermore, whole-genome comparisons identified large indels (\u3e 500 bp) in several intergenic spacer regions and introns in the Solanaceae, including trnE (UUC)–trnT (GGU) spacer, ycf4–cemA spacer, trnI (GAU) intron and rrn5–trnR (ACG) spacer. Phylogenetic analyses based on the DNA sequences of 61 protein-coding genes for 35 taxa, performed using both maximum parsimony and maximum likelihood methods, strongly supported the monophyly of several major clades of angiosperms, including monocots, eudicots, rosids, asterids, eurosids II, and euasterids I and II. Coffea (Rubiaceae, Gentianales) is only the second order sampled from the euasterid I clade. The availability of the complete chloroplast genome of coffee provides regulatory and intergenic spacer sequences for utilization in chloroplast genetic engineering to improve this important crop

Epigenetic loss of RNA-methyltransferase NSUN5 in glioma targets ribosomes to drive a stress adaptive translational program

Altres ajuts: This work was supported by the Obra Social "La Caixa" (to M. Esteller).Tumors have aberrant proteomes that often do not match their corresponding transcriptome profiles. One possible cause of this discrepancy is the existence of aberrant RNA modification landscapes in the so-called epitranscriptome. Here, we report that human glioma cells undergo DNA methylation-associated epigenetic silencing of NSUN5, a candidate RNA methyltransferase for 5-methylcytosine. In this setting, NSUN5 exhibits tumor-suppressor characteristics in vivo glioma models. We also found that NSUN5 loss generates an unmethylated status at the C3782 position of 28S rRNA that drives an overall depletion of protein synthesis, and leads to the emergence of an adaptive translational program for survival under conditions of cellular stress. Interestingly, NSUN5 epigenetic inactivation also renders these gliomas sensitive to bioactivatable substrates of the stress-related enzyme NQO1. Most importantly, NSUN5 epigenetic inactivation is a hallmark of glioma patients with long-term survival for this otherwise devastating disease

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype