Adenovirus as Tools in Animal Health

Adenoviruses have long been identified as good candidates for use as viral vectors in gene therapy and as vaccines. These viruses can infect multiple cell types, while in division or in quiescence, and are relatively easy to manipulate so that parts of their genome can be replaced with exogenous genes. Progressive safety improvements in replication-deficient adenoviral vectors have been achieved with the second and third generation, and ending with the gutless adenoviral vectors. Adenoviral vectors are immunogenic and can act as adjuvants. Nonetheless, the potency of human recombinant adenoviral vaccines was below expectations in clinical trials mainly because of the pre-existing adenoviral immunity found in the general population. This drawback can however become advantageous in animal health, as no previous immunity to human adenoviral vectors exists in animals. Other viral vectors viruses are used as vaccine, but adenoviruses remain the most employed and promising recombinant vector in veterinary medicine. In this chapter, we review the generation of adenoviral vectors, the immune response they trigger, and their advantages and disadvantages for veterinary use in terms of safety and efficacy. This chapter also describes how recombinant adenoviral vectors can be integrated as tools for vaccination and immunomodulation in veterinary medicine

Plectranthias lamillai, a new Anthiine fish species (Perciformes, Serranidae) from the Juan Fernández Archipelago, Chile

Plectranthias lamillai new species, is described and illustrated as a new anthiine serranid fish from Alejandro Selkirk Island, the westernmost island of the Juan Fernández Archipelago, about 700 km west of Chile at 33°45´S, 80°51´W. The following combination of characters distinguishes it from all other serranids: dorsal fin rays X,16; principal caudal-fin rays 17 (8+9); pectoral-fin rays 16; gillrakers 28 (8+20); tubed lateral-line scales 40-41; 10 rows of scales on cheek; maxilla narrow and rounded; posterior margin of bony opercle with three spinous processes, the middle one largest; subopercle 2-6 small serrae; pseudobranch with 24 filaments; circumpeduncular scales 16; pelvic fin inserted beneath base of pectoral fin, the tip reaching a vertical through base of tenth dorsal-fin spine, falling short of the anus; a broad red bar from sixth dorsal-fin spine to base of fifth ray, extending to anus and above anal fin as a narrow band that widens on the peduncle and then bifurcates over the upper and lower margins of the caudal fin; rest of the caudal fin yellowish. Pectoral fins orange; pelvic and anal fins whitish.No disponibl

Chapter Adenovirus as Tools in Animal Health

Adenoviruses have long been identified as good candidates for use as viral vectors in gene therapy and as vaccines. These viruses can infect multiple cell types, while in division or in quiescence, and are relatively easy to manipulate so that parts of their genome can be replaced with exogenous genes. Progressive safety improvements in replication-deficient adenoviral vectors have been achieved with the second and third generation, and ending with the gutless adenoviral vectors. Adenoviral vectors are immunogenic and can act as adjuvants. Nonetheless, the potency of human recombinant adenoviral vaccines was below expectations in clinical trials mainly because of the pre-existing adenoviral immunity found in the general population. This drawback can however become advantageous in animal health, as no previous immunity to human adenoviral vectors exists in animals. Other viral vectors viruses are used as vaccine, but adenoviruses remain the most employed and promising recombinant vector in veterinary medicine. In this chapter, we review the generation of adenoviral vectors, the immune response they trigger, and their advantages and disadvantages for veterinary use in terms of safety and efficacy. This chapter also describes how recombinant adenoviral vectors can be integrated as tools for vaccination and immunomodulation in veterinary medicine

The time-scales of major mergers from simulations of isolated binary galaxy collisions

A six-dimensional parameter space based on high-resolution numerical simulations of isolated binary galaxy collisions has been constructed to investigate the dynamical friction timescales, $\tau_{\rm mer}$, for major mergers. Our experiments follow the gravitational encounters between $\sim 600$ pairs of similarly massive late- and early-type galaxies with orbital parameters compliant to the predictions of the LambdaCDM cosmology. We analyze the performance of different schemes for tracking the secular evolution of mergers, finding that the product of the intergalactic distance and velocity is best suited to identify the time of coalescence. In contrast, a widely used merger time estimator such as the exhaustion of the orbital spin is shown to systematically underpredict $\tau_ {\rm mer}$, resulting in relative errors that can reach 60% for nearly radial encounters. Regarding the internal spins of the progenitors, we find that they can lead to total variations in the merger times above 30% in highly circular encounters, whereas only that of the principal halo is capable of modulating the strength of the interaction prevailing throughout a merger. The comparison of our simulated merger times with predictions from different variants of a well-known fitting formula has revealed an only partially satisfactory agreement, which has led us to recalculate the values of the coefficients of these expressions to obtain relations that fit perfectly major mergers. The observed biases between data and predictions, that do not only apply to the present work, are inconsistent with expectations from differences in the degree of idealization of the collisions, their metric, spin-related biases, or the simulation set-up. This hints to a certain lack of accuracy of the dynamical friction modelling, arising perhaps from a still not quite complete identification of the parameters governing orbital decay.Comment: 20 pages, 11 figures, 3 tables. Accepted for publication in A&

Day-ahead optimal battery operation in islanded hybrid energy systems and its impact on greenhouse gas emissions

This paper proposes a management strategy for the daily operation of an isolated hybrid energy system (HES) using heuristic techniques. Incorporation of heuristic techniques to the optimal scheduling in day-head basis allows us to consider the complex characteristics of a specific battery energy storage system (BESS) and the associated electronic converter efficiency. The proposed approach can determine the discharging time to perform the load peak-shaving in an appropriate manner. A recently proposed version of binary particle swarm optimization (BPSO), which incorporates a time-varying mirrored S-shaped (TVMS) transfer function, is proposed for day-ahead scheduling determination. Day-ahead operation and greenhouse gas (GHG) emissions are studied through different operating conditions. The complexity of the optimization problem depends on the available wind resource and its relationship with load profile. In this regard, TVMS-BPSO has important capabilities for global exploration and local exploitation, which makes it a powerful technique able to provide a high-quality solution comparable to that obtained from a genetic algorithm

Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

Multiple sequence alignments (MSAs) have become one of the most studied approaches in bioinformatics to perform other outstanding tasks such as structure prediction, biological function analysis or next-generation sequencing. However, current MSA algorithms do not always provide consistent solutions, since alignments become increasingly difficult when dealing with low similarity sequences. As widely known, these algorithms directly depend on specific features of the sequences, causing relevant influence on the alignment accuracy. Many MSA tools have been recently designed but it is not possible to know in advance which one is the most suitable for a particular set of sequences. In this work, we analyze some of the most used algorithms presented in the bibliography and their dependences on several features. A novel intelligent algorithm based on least square support vector machine is then developed to predict how accurate each alignment could be, depending on its analyzed features. This algorithm is performed with a dataset of 2180 MSAs. The proposed system first estimates the accuracy of possible alignments. The most promising methodologies are then selected in order to align each set of sequences. Since only one selected algorithm is run, the computational time is not excessively increased