Optimization of a mouse immunization protocol with Paracoccidioides brasiliensis antigens

The objectives of the present study were to optimize the protocol of mouse immunization with Paracoccidioides brasiliensis antigens (Rifkind's protocol) and to test the modulation effect of cyclophosphamide (Cy) on the delayed hypersensitivity response (DHR) of immunized animals. Experiments were carried out using one to four immunizing doses of either crude particulate P. brasiliensis antigen or yeast-cell antigen, followed by DHR test four or seven days after the last immunizing dose. The data demonstrated that an immunizing dose already elicited response; higher DHR indices were obtained with two or three immunizing doses; there were no differences between DHR indices of animals challenged four or seven days after the last dose. Overall the inoculation of two or three doses of the yeast-cell antigen, which is easier to prepare, and DHR test at day 4 simplify the original Rifkind's immunization protocol and shorten the duration of the experiments. The modulation effect of Cy on DHR was assayed with administration of 2.5, 20 and 100 mg/kg weight at seven day intervals starting from day 4 prior to the first immunizing dose. Only the treatment with 2.5 mg Cy increased the DHR indices. Treatment with 100 mg Cy inhibited the DHR, whereas 20 mg Cy did not affect the DHR indices. Results suggest an immunostimulating effect of low dose of Cy on the DHR of mice immunized with P. brasiliensis antigens.

Comparison of Some Molecular-genetic Techniques for Identification of Leishmania Circulating in Natural Foci of Zoonotic Cutaneous Leishmaniasis in the Central Asia Region

Different molecular-genetic methods were used to identify a cohort of Leishmania strains from natural foci of zoonotic cutaneous leishmaniasis located in Central Asia, on the former USSR territory. The results obtained using isoenzymes, PCR, restriction fragment length polymorphisms of kDNA and molecular hybridization techniques are discussed in terms of their applicability, discrimination power and feasibility for answering questions related to molecular epidemiological research and for detecting mixed Leishmania infections

Optimum in vitro expansion of human antigen-specific CD8 T cells for adoptive transfer therapy.

Increasing evidence suggests that adoptive transfer of antigen-specific CD8(+) T cells could represent an effective strategy in the fight against chronic viral infections and malignancies such as melanoma. None the less, a major limitation in the implementation of such therapy resides in the difficulties associated with achieving rapid and efficient expansion of functional T cells in culture necessary to obtain the large numbers required for intravenous infusion. Recently, the critical role of the cytokines interleukin (IL)-2, IL-7 and IL-15 in driving T cell proliferation has been emphasized, thus suggesting their use in the optimization of expansion protocols. We have used major histocompatibility complex (MHC) class I/peptide multimers to monitor the expansion of antigen-specific CD8 T lymphocytes from whole blood, exploring the effect of antigenic peptide dose, IL-2, IL-7 and IL-15 concentrations on the magnitude and functional characteristics of the antigen-specific CD8(+) T cells generated. We show here that significant expansions of antigen-specific T cells, up to 50% of the CD8(+) T cell population, can be obtained after a single round of antigen/cytokine (IL-2 or IL-15) stimulation, and that these cells display good cytolytic and interferon (IFN)-gamma secretion capabilities. Our results provide an important basis for the rapid in vitro expansion of autologous T cells from the circulating lymphocyte pool using a simple procedure, which is necessary for the development of adoptive transfer therapies.

Analysis and optimization of the satellite-to-plane link of an aeronautical global system

En aquest projecte s’ha analitzat i optimitzat l’enllaç satèl·lit amb avió per a un sistema aeronàutic global. Aquest nou sistema anomenat ANTARES està dissenyat per a comunicar avions amb estacions base mitjançant un satèl·lit. Aquesta és una iniciativa on hi participen institucions oficials en l’aviació com ara l’ECAC i que és desenvolupat en una col·laboració europea d’universitats i empreses. El treball dut a terme en el projecte compren bàsicament tres aspectes. El disseny i anàlisi de la gestió de recursos. La idoneïtat d’utilitzar correcció d’errors en la capa d’enllaç i en cas que sigui necessària dissenyar una opció de codificació preliminar. Finalment, estudiar i analitzar l’efecte de la interferència co-canal en sistemes multifeix. Tots aquests temes són considerats només per al “forward link”. L’estructura que segueix el projecte és primer presentar les característiques globals del sistema, després centrar-se i analitzar els temes mencionats per a poder donar resultats i extreure conclusions.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

A linear optimization technique for graph pebbling

Graph pebbling is a network model for studying whether or not a given supply of discrete pebbles can satisfy a given demand via pebbling moves. A pebbling move across an edge of a graph takes two pebbles from one endpoint and places one pebble at the other endpoint; the other pebble is lost in transit as a toll. It has been shown that deciding whether a supply can meet a demand on a graph is NP-complete. The pebbling number of a graph is the smallest t such that every supply of t pebbles can satisfy every demand of one pebble. Deciding if the pebbling number is at most k is NP 2 -complete. In this paper we develop a tool, called theWeight Function Lemma, for computing upper bounds and sometimes exact values for pebbling numbers with the assistance of linear optimization. With this tool we are able to calculate the pebbling numbers of much larger graphs than in previous algorithms, and much more quickly as well. We also obtain results for many families of graphs, in many cases by hand, with much simpler and remarkably shorter proofs than given in previously existing arguments (certificates typically of size at most the number of vertices times the maximum degree), especially for highly symmetric graphs. Here we apply theWeight Function Lemma to several specific graphs, including the Petersen, Lemke, 4th weak Bruhat, Lemke squared, and two random graphs, as well as to a number of infinite families of graphs, such as trees, cycles, graph powers of cycles, cubes, and some generalized Petersen and Coxeter graphs. This partly answers a question of Pachter, et al., by computing the pebbling exponent of cycles to within an asymptotically small range. It is conceivable that this method yields an approximation algorithm for graph pebbling.

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases.

On the stability of the optimal value and the optimal set in optimization problems

The paper develops a stability theory for the optimal value and the optimal set mapping of optimization problems posed in a Banach space. The problems considered in this paper have an arbitrary number of inequality constraints involving lower semicontinuous (not necessarily convex) functions and one closed abstract constraint set. The considered perturbations lead to problems of the same type as the nominal one (with the same space of variables and the same number of constraints), where the abstract constraint set can also be perturbed. The spaces of functions involved in the problems (objective and constraints) are equipped with the metric of the uniform convergence on the bounded sets, meanwhile in the space of closed sets we consider, coherently, the Attouch-Wets topology. The paper examines, in a unified way, the lower and upper semicontinuity of the optimal value function, and the closedness, lower and upper semicontinuity (in the sense of Berge) of the optimal set mapping. This paper can be seen as a second part of the stability theory presented in [17], where we studied the stability of the feasible set mapping (completed here with the analysis of the Lipschitz-like property).

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

Neuroimaging techniques in Alzheimer's disease

Neuroimaging techniques provide valuable tools for diagnosing Alzheimer's disease (AD), monitoring disease progression and evaluating responses to treatment. There is currently a wide array of techniques available including computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), and, for recording electrical brain activity, electroencephalography (EEG). The choice of technique depends on the contrast between tissues of interest, spatial resolution, temporal resolution, requirements for functional data and the probable number of scans required. For example, while PET, CT and MRI can be used to differentiate between AD and other dementias, MRI is safer and provides better contrast of soft tissues. Neuroimaging is a technique spanning many disciplines and requires effective communication between doctors requesting a scan of a patient or group of patients and those with technical expertise. Consideration and discussion of the most suitable type of scan and the necessary settings to achieve the best results will help ensure appropriate techniques are chosen and used effectively. Neuroimaging techniques are currently expanding understanding of the structural and functional changes that occur in dementia. Further research may allow identification of early neurological signs ofAD, before clinical symptoms are evident, providing the opportunity to test preventative therapies. CombiningMRI and machine learning techniques may be a powerful approach to improve diagnosis ofAD and to predict clinical outcomes.

Evaluation of two minimally invasive techniques for electroencephalogram recording in wild or freely behaving animals.

Insight into the function of sleep may be gained by studying animals in the ecological context in which sleep evolved. Until recently, technological constraints prevented electroencephalogram (EEG) studies of animals sleeping in the wild. However, the recent development of a small recorder (Neurologger 2) that animals can carry on their head permitted the first recordings of sleep in nature. To facilitate sleep studies in the field and to improve the welfare of experimental animals, herein, we test the feasibility of using minimally invasive surface and subcutaneous electrodes to record the EEG in barn owls. The EEG and behaviour of four adult owls in captivity and of four chicks in a nest box in the field were recorded. We scored a 24-h period for each adult bird for wakefulness, slow-wave sleep (SWS), and rapid-eye movement (REM) sleep using 4 s epochs. Although the quality and stability of the EEG signals recorded via subcutaneous electrodes were higher when compared to surface electrodes, the owls' state was readily identifiable using either electrode type. On average, the four adult owls spent 13.28 h awake, 9.64 h in SWS, and 1.05 h in REM sleep. We demonstrate that minimally invasive methods can be used to measure EEG-defined wakefulness, SWS, and REM sleep in owls and probably other animals.