Tree decomposition and parameterized algorithms for RNA structure-sequence alignment including tertiary interactions and pseudoknots

We present a general setting for structure-sequence comparison in a large class of RNA structures that unifies and generalizes a number of recent works on specific families on structures. Our approach is based on tree decomposition of structures and gives rises to a general parameterized algorithm, where the exponential part of the complexity depends on the family of structures. For each of the previously studied families, our algorithm has the same complexity as the specific algorithm that had been given before.Comment: (2012

Applications of stable water and carbon isotopes in watershed research: Weathering, carbon cycling, and water balances

Research on rivers has traditionally involved concentration and flux measurements to better understand weathering, transport and cycling of materials from land to ocean. As a relatively new tool, stable isotope measurements complement this type of research by providing an extra label to characterize origin of the transportedmaterial, its transfer mechanisms, and natural versus anthropogenic influences. These new stable isotope techniques are scalable across a wide range of geographic and temporal scales. This review focuses on three aspects of hydrological and geochemical river research that are of prime importance to the policy issues of climate change and include utilization of stable water and carbon isotopes: (i) silicate and carbonate weathering in river basins, (ii) the riverine carbon and oxygen cycles, and (iii) water balances at the catchment scale. Most studies at watershed scales currently focus on water and carbon balances but future applications hold promise to integrate sediment fluxes and turnover, ground and surface water interactions, as well as the understanding of contaminant sources and their effects in river systems

Algorithmique de l'alignement structure-séquence d'ARN (une approche générale et paramétrée)

L'alignement de macromolécules biologiques comme les protéines, l'ADN ou encore l'ARN est une problématique biologique et bio-informatique qui a pour but de révéler une partie des mystères du fonctionnement des cellules, constituants des êtres vivants. Les ARN non-codant sont des macromolécules intervenant dans le métabolisme de tout être vivant et les deux problématiques majeurs les concernant sont: la prédiction de leur structure pour mieux comprendre leur fonctionnement et leur détection dans des bases de données ou des génomes. L'une des approches: l'alignement structure-séquence d'ARN, répond à ces deux problématiques. Le problème d'alignement structure-séquence consiste à aligner une structure connue d'un premier ARN avec la séquence d'un deuxième ARN.La structure est représentée sous la forme d'un graphe ou de façon équivalente sous la forme d'une séquence arc-annotées et la séquence représente la suite des nucléotides de l'ARN.Pour résoudre ce problème, nous cherchons à optimiser l'alignement selon une fonction de coût. C'est donc un problème d'optimisation, qui malheureusement se révèle NP-Difficile.En conséquence différents travaux définissent des classes d'instances réduites pour lesquelles ils proposent des algorithmes spécifiques mais à complexités polynomiales.Les travaux de ma thèse unifient et la généralisent les approches précédentes par la construction d'un algorithme à complexité paramétrée non spécifique à une classe d'instances. En utilisant cet algorithme, il est possible de résoudre le problème d'alignement structure-séquence pour toutes les instances possibles, et aussi efficacement que les précédentes approches sur leur domaine de résolution respectif. Cet algorithme utilise une technique empruntée à la théorie des graphes: la décomposition arborescente, c'est-à-dire qu'il transforme la structure donnée en une décomposition arborescente et c'est ensuite cette décomposition qui est alignée avec la séquence donnée. L'alignement entre une décomposition arborescente et une séquence se fait par programmation dynamique.Sa mise en place a nécessité une reformulation du problème ainsi qu'une modification importante de l'utilisation classique de la programmation dynamique pour les décompositions arborescentes. Au final, cela conduit à un algorithme paramétré dont le paramètre est entièrement lié à la décomposition arborescente. La construction des décompositions arborescentes pour lesquelles l'alignement s'effectuera plus le efficacement possible est malheureusement un problème lui aussi NP-Difficile. Néanmoins, nous avons créé une heuristique de construction de décompositions adaptée aux structures d'ARN.Nous avons alors défini des nouvelles classes de structures pour lesquelles notre algorithme (décomposition et alignement) possède une faible complexité. Ces classes incluent notamment toutes les autres classes précédemment définies et la complexité de notre algorithme est au moins aussi faible que celles des algorithmes spécifiques sur leurs classes de structures respectives. Ces classes de structures représentent la majorité des structures connues et contiennent de nombreux éléments importants jusqu'alors non pris en compte (tel que les motifs tertiaires d'ARN). Le problème de l'alignement structure-séquence tente de répondre aux problématiques de prédictions de structures et de recherche d'ARN. Néanmoins, la qualité des résultats obtenus par sa résolution dépendent de la fonction de coût utilisée. Durant ma thèse j'ai commencé la mise place de la construction par apprentissage d'une nouvelle fonction de coût, adaptée aux nouvelles classes de structures que nous avons défini. Enfin de par la nature de l'algorithme, le travail réalisé permet des améliorations non négligeables, en terme de qualité des résultats et de rapidité de calcul comme la recherche de solution sous-optimales ou l'utilisation de l'algorithme au sein d'heuristiques dérivées d'heuristiques classiques.The alignment of biological macromolecules such as proteins, DNA or RNA is a biological and bio-informatics problematic which aims to reveal some of the mysteries of how cells works. The non-coding RNA are involved in the metabolism of all living beings. The two major issues concerning them are: the prediction of their structure to better understand their function and their detection in databases or genomes. One approach, the structure-sequence alignment of RNA, addresses these two issues. The work done during my thesis provides some constructive elements on this problem and led me to call the graph algorithmic for its resolution. The alignment problem is to align a structure of a first RNA with the sequence of a second RNA. The structure on the first RNA is represented as a graph or equivalently as an arc-annotated sequence and the sequence represents the nucleotide sequence of the second RNA.To solve this problem, we aim to compute a minimal cost alignment, according to a given cost function. So, this is an optimization problem, which turns out to be NP-hard.Accordingly, different works define several reduced structure classes for which they propose specific algorithms but with polynomial complexity. The work of my thesis unifies and generalizes previous approaches by the construction of a unique (not class specific) parameterized algorithm. Using this algorithm, it is possible to solve the problem of structure-sequence alignment for all possible instances, and as effectively as previous approaches in their respective field of resolution.This algorithm uses a technique from graph theory: the tree decomposition, that is to say, it transforms the given structure into a tree-decomposition and the decomposition is then aligned with the sequence. The alignment between a tree-decomposition and a sequence is done by dynamic programming. Its implementation requires a reformulation of the problem as well as a substantial modifications to the conventional use of dynamic programming for tree decompositions. This leads to an algorithm whose parameter is entirely related to the tree-decomposition.The construction of tree decompositions for which the alignment is the most effective is unfortunately a NP-Hard problem. Nevertheless, we have developed a heuristic construction of decompositions adapted to RNA structures. We then defined new structure classes which extend existing ones without degrading the complexity of the alignment but which can represent the majority of known structures containing many important elements that had not be taken into account previously (such as RNA tertiary motifs).The sequence-structure alignment problem attempts to answer the problem of prediction of structures and RNA research. However, the quality of the results obtained by its resolution depends on the cost function. During my PhD I started to define new cost functions adapted to the new structure classes by a machine learning approach. Finally, the work allows significant improvements in terms of quality of results and computation. For example the approach directly allows the search for sub-optimal solutions or its use within heuristics derived from traditional heuristic methods.PARIS11-SCD-Bib. électronique (914719901) / SudocSudocFranceF

Outcomes of capsulolabral reconstruction for posterior shoulder instability

BACKGROUND: Surgical treatment of isolated posterior shoulder instability-a rare and often misdiagnosed condition-is controversial because of poor outcomes. Failure of physical therapy in symptomatic young athletes requires capsulolabral reconstruction or bone block procedures. The goal of this study was to report the outcomes of patients who have undergone surgical capsulolabral reconstruction and to look for risk factors that contribute to failure of this procedure. MATERIAL AND METHOD: We analyzed the outcomes of 101 patients who underwent capsulolabral reconstruction: 83 included retrospectively, 18 included prospectively. The procedures were performed alone or in combination with capsular shift, labral repair, closure of the rotator interval and notch remplissage. The primary endpoint was failure of the procedure, defined as recurrence of the instability and/or pain. We also determined the outcomes based on specific (Walch-Duplay, modified Rowe) and non-specific (Constant, resumption of activities) scores of shoulder instability. RESULTS: The results were satisfactory despite a high failure rate: 35% in the retrospective cohort with 4.8±2.6 years' follow-up and 22% in the prospective cohort with 1.1±0.3 years' follow-up. The various outcome scores improved significantly. Ninety-two percent of patients returned to work and 80% of athletes returned to their pre-injury level of sports. Eighty-five percent of patients were satisfied or very satisfied after the surgery. No risk factors for failure were identified; however, failures were more common in older patients, those who underwent an isolated procedure and those who had unclassified clinical forms. CONCLUSION: Treatment of posterior shoulder instability by capsulolabral reconstruction leads to good clinical outcomes; however, the recurrence rate is high

Mastering tricyclic ring systems for desirable functional cannabinoid activity

There is growing interest in using cannabinoid receptor 2 (CB2) agonists for the treatment of neuropathic pain and other indications. In continuation of our ongoing program aiming for the development of new small molecule cannabinoid ligands, we have synthesized a novel series of carbazole and γ-carboline derivatives. The affinities of the newly synthesized compounds were determined by a competitive radioligand displacement assay for human CB2 cannabinoid receptor and rat CB1 cannabinoid receptor. Functional activity and selectivity at human CB1 and CB2 receptors were characterized using receptor internalization and [35S]GTP-γ-S assays. The structure–activity relationship and optimization studies of the carbazole series have led to the discovery of a non-selective CB1 and CB2 agonist, compound 4. Our subsequent research efforts to increase CB2 selectivity of this lead compound have led to the discovery of CB2 selective compound 64, which robustly internalized CB2 receptors. Compound 64 had potent inhibitory effects on pain hypersensitivity in a rat model of neuropathic pain. Other potent and CB2 receptor–selective compounds, including compounds 63 and 68, and a selective CB1 agonist, compound 74 were also discovered. In addition, we identified the CB2 ligand 35 which failed to promote CB2 receptor internalization and inhibited compound CP55,940-induced CB2 internalization despite a high CB2 receptor affinity. The present study provides novel tricyclic series as a starting point for further investigations of CB2 pharmacology and pain treatment.Fil: Petrov, Ravil R.. University Of Montana; Estados UnidosFil: Knight, Lindsay. Indiana University; Estados UnidosFil: Chen, Shao Rui. University Of Texas; Estados UnidosFil: Wager Miller, Jim. Indiana University; Estados UnidosFil: McDaniel, Steven W.. University Of Montana; Estados UnidosFil: Diaz, Fanny. University Of Montana; Estados UnidosFil: Barth, Francis. Sanofi-aventis R&D; FranciaFil: Pan, Hui Lin. University Of Texas; Estados UnidosFil: Mackie, Ken. Indiana University; Estados UnidosFil: Cavasotto, Claudio Norberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigación en Biomedicina de Buenos Aires; ArgentinaFil: Diaz, Philippe. University Of Montana; Estados Unido

Model-free control algorithms for micro air vehicles with transitioning flight capabilities

Micro air vehicles with transitioning flight capabilities, or simply hybrid micro air vehicles, combine the beneficial features of fixed-wing configurations, in terms of endurance, with vertical take-off and landing capabilities of rotorcrafts to perform five different flight phases during typical missions, such as vertical takeoff, transitioning flight, forward flight, hovering and vertical landing. This promising micro air vehicle class has a wider flight envelope than conventional micro air vehicles, which implies new challenges for both control community and aerodynamic designers. One of the major challenges of hybrid micro air vehicles is the fast variation of aerodynamic forces and moments during the transition flight phase which is difficult to model accurately. To overcome this problem, we propose a flight control architecture that estimates and counteracts in real-time these fast dynamics with an intelligent feedback controller. The proposed flight controller is designed to stabilize the hybrid micro air vehicle attitude as well as its velocity and position during all flight phases. By using model-free control algorithms, the proposed flight control architecture bypasses the need for a precise hybrid micro air vehicle model that is costly and time consuming to obtain. A comprehensive set of flight simulations covering the entire flight envelope of tailsitter micro air vehicles is presented. Finally, real-world flight tests were conducted to compare the model-free control performance to that of the Incremental Nonlinear Dynamic Inversion controller, which has been applied to a variety of aircraft providing effective flight performances

EST-derived SSR markers used as anchor loci for the construction of a consensus linkage map in ryegrass (Lolium spp.)

BACKGROUND: Genetic markers and linkage mapping are basic prerequisites for marker-assisted selection and map-based cloning. In the case of the key grassland species Lolium spp., numerous mapping populations have been developed and characterised for various traits. Although some genetic linkage maps of these populations have been aligned with each other using publicly available DNA markers, the number of common markers among genetic maps is still low, limiting the ability to compare candidate gene and QTL locations across germplasm. RESULTS: A set of 204 expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers has been assigned to map positions using eight different ryegrass mapping populations. Marker properties of a subset of 64 EST-SSRs were assessed in six to eight individuals of each mapping population and revealed 83% of the markers to be polymorphic in at least one population and an average number of alleles of 4.88. EST-SSR markers polymorphic in multiple populations served as anchor markers and allowed the construction of the first comprehensive consensus map for ryegrass. The integrated map was complemented with 97 SSRs from previously published linkage maps and finally contained 284 EST-derived and genomic SSR markers. The total map length was 742 centiMorgan (cM), ranging for individual chromosomes from 70 cM of linkage group (LG) 6 to 171 cM of LG 2. CONCLUSIONS: The consensus linkage map for ryegrass based on eight mapping populations and constructed using a large set of publicly available Lolium EST-SSRs mapped for the first time together with previously mapped SSR markers will allow for consolidating existing mapping and QTL information in ryegrass. Map and markers presented here will prove to be an asset in the development for both molecular breeding of ryegrass as well as comparative genetics and genomics within grass species

A Real-Space Full Multigrid study of the fragmentation of Li11+ clusters

We have studied the fragmentation of Li11+ clusters into the two experimentally observed products (Li9+,Li2) and (Li10+,Li) The ground state structures for the two fragmentation channels are found by Molecular Dynamics Simulated Annealing in the framework of Local Density Functional theory. Energetics considerations suggest that the fragmentation process is dominated by non-equilibrium processes. We use a real-space approach to solve the Kohn-Sham problem, where the Laplacian operator is discretized according to the Mehrstellen scheme, and take advantage of a Full MultiGrid (FMG) strategy to accelerate convergence. When applied to isolated clusters we find our FMG method to be more efficient than state-of-the-art plane wave calculations.Comment: 9 pages + 6 Figures (in gzipped tar file

Self-assembly of three bacterially-derived bioactive lipopeptides

The self-assembly in aqueous solution of three lipopeptides obtained from Bacillus subtilis has been investigated. The lipopeptides surfactin, plipastatin and mycosubtilin contain distinct cyclic peptide headgroups as well as differences in alkyl chain length, branching and chain length distribution. Cryogenic transmission electron microscopy and X-ray scattering reveal that surfactin and plipastatin aggregate into 2 nm-radius spherical micelles, whereas in complete contrast mycosubtilin self-assembles into extended nanotapes based on bilayer ordering of the lipopeptides. Circular dichroism and FTIR spectroscopy indicate the presence of turn structures in the cyclic peptide headgroup. The unexpected distinct mode of self-assembly of mycosubtilin compared to the other two lipopeptides is ascribed to differences in the surfactant packing parameter. This in turn is due to specific features of the conformation of the peptide headgroup and alkyl chain branching

Myofibroblastic reaction is a common event in metastatic disease of breast carcinoma: a descriptive study

BACKGROUND: The modification of stromal components with the disappearance of CD34 positive fibrocytes and by contrast the acquisition of smooth-muscle actin positive myofibroblasts is a frequent event in breast carcinomas but has been little studied in its metastatic sites. Therefore, the aim of the present study is to examine the stromal expression of CD34 and SMA in lymph node and liver metastases which are two of the most frequent metastatic breast cancer sites.SCOPUS: ar.jinfo:eu-repo/semantics/publishe