A programming and a modelling perspective on the evaluation of Java card implementations

Java Card Technology has provided a huge step forward in programming smart cards: from assembler to using a high level Object Oriented language. However, the authors have found some differences between the current Java Card version (2.1) and main stream Java that may restrict the benefits of using Java achievable in smartcard programming. In particular, efforts towards evaluating Java Card implementations at a high level of assurance may be hampered by the presence of these differences as well as by the complexity of the Java Card VM and API. The goal of the present paper is to detail the differences from a programming and a modelling point of view

Employing machine learning for reliable miRNA target identification in plants

<p>Abstract</p> <p>Background</p> <p>miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.</p> <p>Result</p> <p>In the present work, a Support Vector Regression (SVR) approach has been implemented for plant miRNA target identification, utilizing position specific dinucleotide density variation information around the target sites, to yield highly reliable result. It has been named as p-TAREF (plant-Target Refiner). Performance comparison for p-TAREF was done with other prediction tools for plants with utmost rigor and where p-TAREF was found better performing in several aspects. Further, p-TAREF was run over the experimentally validated miRNA targets from species like <it>Arabidopsis</it>, <it>Medicago</it>, Rice and Tomato, and detected them accurately, suggesting gross usability of p-TAREF for plant species. Using p-TAREF, target identification was done for the complete Rice transcriptome, supported by expression and degradome based data. miR156 was found as an important component of the Rice regulatory system, where control of genes associated with growth and transcription looked predominant. The entire methodology has been implemented in a multi-threaded parallel architecture in Java, to enable fast processing for web-server version as well as standalone version. This also makes it to run even on a simple desktop computer in concurrent mode. It also provides a facility to gather experimental support for predictions made, through on the spot expression data analysis, in its web-server version.</p> <p>Conclusion</p> <p>A machine learning multivariate feature tool has been implemented in parallel and locally installable form, for plant miRNA target identification. The performance was assessed and compared through comprehensive testing and benchmarking, suggesting a reliable performance and gross usability for transcriptome wide plant miRNA target identification.</p

Cloning and Characterization of Maize miRNAs Involved in Responses to Nitrogen Deficiency

Although recent studies indicated that miRNAs regulate plant adaptive responses to nutrient deprivation, the functional significance of miRNAs in adaptive responses to nitrogen (N) limitation remains to be explored. To elucidate the molecular biology underlying N sensing/signaling in maize, we constructed four small RNA libraries and one degradome from maize seedlings exposed to N deficiency. We discovered a total of 99 absolutely new loci belonging to 47 miRNA families by small RNA deep sequencing and degradome sequencing, as well as 9 new loci were the paralogs of previously reported miR169, miR171, and miR398, significantly expanding the reported 150 high confidence genes within 26 miRNA families in maize. Bioinformatic and subsequent small RNA northern blot analysis identified eight miRNA families (five conserved and three newly identified) differentially expressed under the N-deficient condition. Predicted and degradome-validated targets of the newly identified miRNAs suggest their involvement in a broad range of cellular responses and metabolic processes. Because maize is not only an important crop but is also a genetic model for basic biological research, our research contributes to the understanding of the regulatory roles of miRNAs in plant adaption to N-deficiency stress

A Collection of Target Mimics for Comprehensive Analysis of MicroRNA Function in Arabidopsis thaliana

Many targets of plant microRNAs (miRNAs) are thought to play important roles in plant physiology and development. However, because plant miRNAs are typically encoded by medium-size gene families, it has often been difficult to assess their precise function. We report the generation of a large-scale collection of knockdowns for Arabidopsis thaliana miRNA families; this has been achieved using artificial miRNA target mimics, a recently developed technique fashioned on an endogenous mechanism of miRNA regulation. Morphological defects in the aerial part were observed for ∼20% of analyzed families, all of which are deeply conserved in land plants. In addition, we find that non-cleavable mimic sites can confer translational regulation in cis. Phenotypes of plants expressing target mimics directed against miRNAs involved in development were in several cases consistent with previous reports on plants expressing miRNA–resistant forms of individual target genes, indicating that a limited number of targets mediates most effects of these miRNAs. That less conserved miRNAs rarely had obvious effects on plant morphology suggests that most of them do not affect fundamental aspects of development. In addition to insight into modes of miRNA action, this study provides an important resource for the study of miRNA function in plants

Discovery of barley miRNAs through deep sequencing of short reads

Background: MicroRNAs are important components of the regulatory network of biological systems and thousands have been discovered in both animals and plants. Systematic investigations performed in species with sequenced genomes such as Arabidopsis, rice, poplar and Brachypodium have provided insights into the evolutionary relationships of this class of small RNAs among plants. However, miRNAs from barley, one of the most important cereal crops, remain unknown. Results: We performed a large scale study of barley miRNAs through deep sequencing of small RNAs extracted from leaves of two barley cultivars. By using the presence of miRNA precursor sequences in related genomes as one of a number of supporting criteria, we identified up to 100 miRNAs in barley. Of these only 56 have orthologs in wheat, rice or Brachypodium that are known to be expressed, while up to 44 appear to be specifically expressed in barley. Conclusions: Our study, the first large scale investigation of small RNAs in barley, has identified up to 100 miRNAs. We demonstrate that reliable identification of miRNAs via deep sequencing in a species whose genome has not been sequenced requires a more careful analysis of sequencing errors than is commonly performed. We devised a read filtering procedure for dealing with errors. In addition, we found that the use of a large dataset of almost 35 million reads permits the use of read abundance distributions along putative precursor sequences as a practical tool for isolating miRNAs in a large background of reads originating from other non-coding and coding RNAs. This study therefore provides a generic approach for discovering novel miRNAs where no genome sequence is available.Andreas W Schreiber, Bu-Jun Shi, Chun-Yuan Huang, Peter Langridge, Ute Bauman

Au fond du labo a gauche. Recherches bizarres - l'indicateur a un milliard

"C'est en essayant de percer les secrets de la matiere que les physiciens du Centre europeen de recherches nucleaires (Cern) ont decouvert que le TGV Geneve-Paris de 16 h 55 etait toujours a l'heure" (1/2 page)

Building a brain under nutritional restriction: insights on sparing and plasticity from Drosophila studies

International audienceWhile the growth of the developing brain is known to be well-protected compared to other organs in the face of nutrient restriction (NR), careful analysis has revealed a range of structural alterations and long-term neurological defects. Yet, despite intensive studies, little is known about the basic principles that govern brain development under nutrient deprivation. For over 20 years, Drosophila has proved to be a useful model for investigating how a functional nervous system develops from a restricted number of neural stem cells (NSCs). Recently, a few studies have started to uncover molecular mechanisms as well as region-specific adaptive strategies that preserve brain functionality and neuronal repertoire under NR, while modulating neuron numbers. Here, we review the developmental constraints that condition the response of the developing brain to NR. We then analyze the recent Drosophila work to highlight key principles that drive sparing and plasticity in different regions of the central nervous system (CNS). As simple animal models start to build a more integrated picture, understanding how the developing brain copes with NR could help in defining strategies to limit damage and improve brain recovery after birth

Post-transcriptional control of light-harvesting genes expression under light stress.

Plants have to deal with fluctuating light environment and the regulation of the photosynthetic apparatus is crucial for their survival. The large multigenic family of nuclear encoded chloroplastic proteins called light harvesting complex (LHC) is involved in both light harvesting and photoprotection. Changes in light intensity induce a complex set of molecular events within both the chloroplast and the cytoplasmic compartments of the cell leading to reorganization of the photosynthetic apparatus in order to optimize photosynthesis to the new conditions. In this study we have investigated the occurrence of translational regulations during light stress in Arabidopsis thaliana by using polysomes profiling. We have observed a strong effect of light on global translation activity of the cell. We show that individual LHC genes are translationally regulated in response to light conditions by changing the ratio between polysomal versus total messenger RNA. In addition, we found that cytoplasmic translational regulation can precede nuclear transcriptional regulation. Thus translational control appears as an important component of the crosstalk between chloroplast and the nucleus in plant cells