The Impact of Dynamic Emissivity−Temperature Trends on Spaceborne Data: Applications to the 2001 Mount Etna Eruption

Spaceborne detection and measurements of high-temperature thermal anomalies enable monitoring and forecasts of lava flow propagation. The accuracy of such thermal estimates relies on the knowledge of input parameters, such as emissivity, which notably affects computation of temperature, radiant heat flux, and subsequent analyses (e.g., effusion rate and lava flow distance to run) that rely on the accuracy of observations. To address the deficit of field and laboratory-based emissivity data for inverse and forward modelling, we measured the emissivity of ‘a’a lava samples from the 2001 Mt. Etna eruption, over the wide range of temperatures (773 to 1373 K) and wavelengths (2.17 to 21.0 µm). The results show that emissivity is not only wavelength dependent, but it also increases non-linearly with cooling, revealing considerably lower values than those typically assumed for basalts. This new evidence showed the largest and smallest increase in average emissivity during cooling in the MIR and TIR regions (~30% and ~8% respectively), whereas the shorter wavelengths of the SWIR region showed a moderate increase (~15%). These results applied to spaceborne data confirm that the variable emissivity-derived radiant heat flux is greater than the constant emissivity assumption. For the differences between the radiant heat flux in the case of variable and constant emissivity, we found the median value is 0.06, whereas the 25th and the 75th percentiles are 0.014 and 0.161, respectively. This new evidence has significant impacts on the modelling of lava flow simulations, causing a dissimilarity between the two emissivity approaches of ~16% in the final area and ~7% in the maximum thickness. The multicomponent emissivity input provides means for ‘best practice’ scenario when accurate data required. The novel approach developed here can be used to test an improved version of existing multi-platform, multi-payload volcano monitoring systems

Approaches to link RNA secondary structures with splicing regulation

In higher eukaryotes, alternative splicing is usually regulated by protein factors, which bind to the pre-mRNA and affect the recognition of splicing signals. There is recent evidence that the secondary structure of the pre-mRNA may also play an important role in this process, either by facilitating or by hindering the interaction with factors and small nuclear ribonucleoproteins (snRNPs) that regulate splicing. Moreover, the secondary structure could play a fundamental role in the splicing of yeast species, which lack many of the regulatory splicing factors present in metazoans. This review describes the steps in the analysis of the secondary structure of the pre-mRNA and its possible relation to splicing. As a working example, we use the case of yeast and the problem of the recognition of the 3-prime splice site.Comment: 21 pages, 7 figure

GC content around splice sites affects splicing through pre-mRNA secondary structures

<p>Abstract</p> <p>Background</p> <p>Alternative splicing increases protein diversity by generating multiple transcript isoforms from a single gene through different combinations of exons or through different selections of splice sites. It has been reported that RNA secondary structures are involved in alternative splicing. Here we perform a genomic study of RNA secondary structures around splice sites in humans (<it>Homo sapiens</it>), mice (<it>Mus musculus</it>), fruit flies (<it>Drosophila melanogaster</it>), and nematodes (<it>Caenorhabditis elegans</it>) to further investigate this phenomenon.</p> <p>Results</p> <p>We observe that GC content around splice sites is closely associated with the splice site usage in multiple species. RNA secondary structure is the possible explanation, because the structural stability difference among alternative splice sites, constitutive splice sites, and skipped splice sites can be explained by the GC content difference. Alternative splice sites tend to be GC-enriched and exhibit more stable RNA secondary structures in all of the considered species. In humans and mice, splice sites of first exons and long exons tend to be GC-enriched and hence form more stable structures, indicating the special role of RNA secondary structures in promoter proximal splicing events and the splicing of long exons. In addition, GC-enriched exon-intron junctions tend to be overrepresented in tissue-specific alternative splice sites, indicating the functional consequence of the GC effect. Compared with regions far from splice sites and decoy splice sites, real splice sites are GC-enriched. We also found that the GC-content effect is much stronger than the nucleotide-order effect to form stable secondary structures.</p> <p>Conclusion</p> <p>All of these results indicate that GC content is related to splice site usage and it may mediate the splicing process through RNA secondary structures.</p

Empirical comparison of cross-platform normalization methods for gene expression data

<p>Abstract</p> <p>Background</p> <p>Simultaneous measurement of gene expression on a genomic scale can be accomplished using microarray technology or by sequencing based methods. Researchers who perform high throughput gene expression assays often deposit their data in public databases, but heterogeneity of measurement platforms leads to challenges for the combination and comparison of data sets. Researchers wishing to perform cross platform normalization face two major obstacles. First, a choice must be made about which method or methods to employ. Nine are currently available, and no rigorous comparison exists. Second, software for the selected method must be obtained and incorporated into a data analysis workflow.</p> <p>Results</p> <p>Using two publicly available cross-platform testing data sets, cross-platform normalization methods are compared based on inter-platform concordance and on the consistency of gene lists obtained with transformed data. Scatter and ROC-like plots are produced and new statistics based on those plots are introduced to measure the effectiveness of each method. Bootstrapping is employed to obtain distributions for those statistics. The consistency of platform effects across studies is explored theoretically and with respect to the testing data sets.</p> <p>Conclusions</p> <p>Our comparisons indicate that four methods, DWD, EB, GQ, and XPN, are generally effective, while the remaining methods do not adequately correct for platform effects. Of the four successful methods, XPN generally shows the highest inter-platform concordance when treatment groups are equally sized, while DWD is most robust to differently sized treatment groups and consistently shows the smallest loss in gene detection. We provide an R package, CONOR, capable of performing the nine cross-platform normalization methods considered. The package can be downloaded at <url>http://alborz.sdsu.edu/conor</url> and is available from CRAN.</p

Computational modeling of gene structure in Arabidopsis thaliana

Computational gene identification by sequence inspection remains a challenging problem. For a typical Arabidopsis thaliana gene with five exons, at least one of the exons is expected to have at least one of its borders predicted incorrectly by ab initio gene finding programs. More detailed analysis for individual genomic loci can often resolve the uncertainty on the basis of EST evidence or similarity to potential protein homologues. Such methods are part of the routine annotation process. However, because the EST and protein databases are constantly growing, in many cases original annotation must be re-evaluated, extended, and corrected on the basis of the latest evidence. The Arabidopsis Genome Initiative is undertaking this task on the whole-genome scale via its participating genome centers. The current Arabidopsis genome annotation provides an excellent starting point for assessing the protein repertoire of a flowering plant. More accurate whole-genome annotation will require the combination of high-throughput and individual gene experimental approaches and computational methods. The purpose of this article is to discuss tools available to an individual researcher to evaluate gene structure prediction for a particular locus

Overview of cattle diseases listed under category C, D or E in the animal health law for wich control programmes are in place within Europe

13 páginas, 5 figuras, 3 tablas.The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for non-EU regulated cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A non-EU regulated cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other diseases to further improve the health status of cattle in their country. The control of non-EU regulated cattle diseases is very heterogenous in Europe. Therefore, the standardising of the outputs of these programmes to enable comparison represents a challenge.Peer reviewe

Assessment of genetic diversity of Busa cattle from Bosnia and Herzegovina using microsatellite DNA markers

The variability of 21 microsatellite loci was analyzed in order to estimate the genetic diversity of the Buša cattle breed. A total of 50 animals involved in the study were divided into two groups: Buša from eastern Herzegovina and Buša from western Herzegovina. The mean number of alleles per locus was 6.6. The average expected heterozygosities were 0.6885 and 0.6212 in the eastern and western populations, respectively. The observed heterozygosity values were 0.6579 and 0.6336, in eastern and western population, respectively. The degree of population differentiation (FST) ranged from 0.008 (for ILSTS006 locus) to 0.242 (for BM1818 locus), with a mean of 0.112. Cluster analysis showed that the two populations were clearly clustered into two distinct clades. This report represents the first genetic characterization of pure Buša cattle from Bosnia and Herzegovina. The obtained results are important for the future development of conservation and management strategies for this cattle breed