Effects of voluntary running on spatial memory and mature brain-derived neurotrophic factor expression in mice hippocampus after status epilepticus

Voluntary physical activity improves memory and learning ability in rodents, whereas status epilepticus has been associated with memory impairment. Physical activity and seizures have been associated with enhanced hippocampal expression of BDNF, indicating that this protein may have a dual role in epilepsy. The influence of voluntary physical activity on memory and BDNF expression has been poorly studied in experimental models of epilepsy. In this paper, we have investigated the effect of voluntary physical activity on memory and BDNF expression in mice with pilocarpine-incluced epilepsy. Male Swiss mice were assigned to four experimental groups: pilocarpine sedentary (PS), pilocarpine runners (PRs), saline sedentary (SS) and saline runners (SRs). Two days after pilocarpine-induced status epilepticus, the affected mice (PR) and their running controls (SR) were housed with access to a running wheel for 28 days. After that, the spatial memory and the expression of the precursor and mature forms of hippocampal BDNF were assessed. PR mice performed better than PS mice in the water maze test. In addition, PR mice had a higher amount of mature BDNF (14 kDa) relative to the total BDNF (14 kDa + 28 kDa + 32 kDa forms) content when compared with PS mice. These results show that voluntary physical activity improved the spatial memory and increased the hippocampal content of mature BDNF of mice with pilocarpine-induced status epilepticus. (C) 2009 Elsevier B.V. All rights reserved.

Gradual Decline in Malaria-Specific Memory T Cell Responses Leads to Failure to Maintain Long-Term Protective Immunity to Plasmodium chabaudi AS Despite Persistence of B Cell Memory and Circulating Antibody

The mechanisms responsible for the generation and maintenance of immunological memory to Plasmodium are poorly understood and the reasons why protective immunity in humans is so difficult to achieve and rapidly lost remain a matter for debate. A possible explanation for the difficulty in building up an efficient immune response against this parasite is the massive T cell apoptosis resulting from exposure to high-dose parasite Ag. To determine the immunological mechanisms required for long-term protection against P. chabaudi malaria and the consequences of high and low acute phase parasite loads for acquisition of protective immunity, we performed a detailed analysis of T and B cell compartments over a period of 200 days following untreated and drug-treated infections in female C57BL/6 mice. By comparing several immunological parameters with the capacity to control a secondary parasite challenge, we concluded that loss of full protective immunity is not determined by acute phase parasite load nor by serum levels of specific IgG2a and IgG1. Abs, but appears to be a consequence of the progressive decline in memory T cell response to parasites, which occurs similarly in untreated and drug-treated mice with time after infection. Furthermore, by analyzing adoptive transfer experiments, we confirmed the major role of CD4(+) T cells for guaranteeing long-term full protection against P. chabaudi malaria. The Journal of Immunology, 2008, 181: 8344-8355.

Transcriptional memory and switching in the Plasmodium falciparum rif gene family

The human malaria parasite Plasmodium falciparum expresses erythrocyte-surface directed variant antigens which are important virulence factors Many are transcribed from multigene families and presumably their mode of expression is strictly controlled to guarantee immune evasion in the human host. In order to elucidate the dynamics of rif transcription and to investigate if rif switching is comparable to var switching we monitored rif variant gene expression in parasites with different cytoadhesive properties as well as after a number of reinvasions. We found identical transcripts in parasite lines with different adhesive phenotypes suggesting that rif genes do not have a critical role in determining the cytoadhesion specificity of infected erythrocytes. We show for the first time that rif genes may show a conserved mode of transcription, maintaining the previously dominant rif transcript in subsequent reinvasions, but also observed rapid switching at rates up to 45% per generation, much higher than for the var gene family. (C) 2009 Elsevier B.V. All rights reserved.

Circadian phase and intertrial interval interfere with social recognition memory

A modified version of the social habituation/dis-habituation paradigm was employed to examine social recognition memory in Wistar rats during two opposing (active and inactive) circadian phases, using different intertrial intervals (30 and 60 min). Wheel-running activity was monitored continuously to identify circadian phase. To avoid possible masking effects of the light-dark cycle, the rats were synchronized to a skeleton photoperiod, which allowed testing during different circadian phases under identical lighting conditions. In each trial, an infantile intruder was introduced into an adult`s home-cage for a 5-minute interaction session, and social behaviors were registered. Rats were exposed to 5 trials per day for 4 consecutive days: oil days I and 2, each resident was exposed to the same intruder; on days 3 and 4, each resident was exposed to a different intruder in each trial. I he resident`s social investigatory behavior was more intense when different intruders were presented compared to repeated presentation of the same intruder, suggesting social recognition memory. This effect was stronger when the rats were tested during the inactive phase and when the intertrial interval was 60 min, These findings Suggest that social recognition memory, as evaluated in this modified habituation/dis-habituation paradigm, is influenced by the circadian rhythm phase during which testing is performed, and by intertrial interval. (C) 2008 Elsevier Inc. All rights reserved.

Involvement of Eukaryotic Translation Initiation Factor 5A (eIF5A) in Skeletal Muscle Stem Cell Differentiation

The eukaryotic translation initiation factor 5A (eIF5A) contains a special amino acid residue named hypusine that is required for its activity, being produced by a post-translational modification using spermidine as substrate. Stem cells from rat skeletal muscles (satellite cells) were submitted to differentiation and an increase of eIF5A gene expression was observed. Higher content of eIF5A protein was found in satellite cells on differentiation in comparison to non-differentiated satellite cells and skeletal muscle. The treatment with NI-guanyl- 1,7-diaminoheptane (GC7), a hypusination inhibitor, reversibly abolished the differentiation process. In association with the differentiation blockage, an increase of glucose consumption and lactate production and a decrease of glucose and palmitic acid oxidation were observed. A reduction in cell proliferation and protein synthesis was also observed. L-Arginine, a spermidine precursor and partial suppressor of muscle dystrophic phenotype, partially abolished the GC7 inhibitory effect on satellite cell differentiation. These results reveal a new physiological role for eIF5A and contribute to elucidate the molecular mechanisms involved in muscle regeneration.

Slicing the metric space to provide quick indexing of complex data in the main memory

Searching in a dataset for elements that are similar to a given query element is a core problem in applications that manage complex data, and has been aided by metric access methods (MAMs). A growing number of applications require indices that must be built faster and repeatedly, also providing faster response for similarity queries. The increase in the main memory capacity and its lowering costs also motivate using memory-based MAMs. In this paper. we propose the Onion-tree, a new and robust dynamic memory-based MAM that slices the metric space into disjoint subspaces to provide quick indexing of complex data. It introduces three major characteristics: (i) a partitioning method that controls the number of disjoint subspaces generated at each node; (ii) a replacement technique that can change the leaf node pivots in insertion operations; and (iii) range and k-NN extended query algorithms to support the new partitioning method, including a new visit order of the subspaces in k-NN queries. Performance tests with both real-world and synthetic datasets showed that the Onion-tree is very compact. Comparisons of the Onion-tree with the MM-tree and a memory-based version of the Slim-tree showed that the Onion-tree was always faster to build the index. The experiments also showed that the Onion-tree significantly improved range and k-NN query processing performance and was the most efficient MAM, followed by the MM-tree, which in turn outperformed the Slim-tree in almost all the tests. (C) 2010 Elsevier B.V. All rights reserved.

A thermoelastic system of memory type in noncylindrical domains

In this paper, we consider a hyperbolic thermoelastic system of memory type in domains with moving boundary. The problem models vibrations of an elastic bar under thermal effects according to the heat conduction law of Gurtin and Pipkin. Global existence is proved by using the penalty method of Lions. (c) 2007 Elsevier Inc. All rights reserved.

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.

Structural modeling and mutational analysis of yeast eukaryotic translation initiation factor 5A reveal new critical residues and reinforce its involvement in protein synthesis

Eukaryotic translation initiation factor 5A (eIF5A) is a protein that is highly conserved and essential for cell viability. This factor is the only protein known to contain the unique and essential amino acid residue hypusine. This work focused on the structural and functional characterization of Saccharomyces cerevisiae eIF5A. The tertiary structure of yeast eIF5A was modeled based on the structure of its Leishmania mexicana homologue and this model was used to predict the structural localization of new site-directed and randomly generated mutations. Most of the 40 new mutants exhibited phenotypes that resulted from eIF-5A protein-folding defects. Our data provided evidence that the C-terminal alpha-helix present in yeast eIF5A is an essential structural element, whereas the eIF5A N-terminal 10 amino acid extension not present in archaeal eIF5A homologs, is not. Moreover, the mutants containing substitutions at or in the vicinity of the hypusine modification site displayed nonviable or temperature-sensitive phenotypes and were defective in hypusine modification. Interestingly, two of the temperature-sensitive strains produced stable mutant eIF5A proteins - eIF5A(K56A) and eIF5A(Q22H,L93F)- and showed defects in protein synthesis at the restrictive temperature. Our data revealed important structural features of eIF5A that are required for its vital role in cell viability and underscored an essential function of eIF5A in the translation step of gene expression.

Structured minimal-memory inexact quasi-Newton method and secant preconditioners for augmented Lagrangian optimization

Augmented Lagrangian methods for large-scale optimization usually require efficient algorithms for minimization with box constraints. On the other hand, active-set box-constraint methods employ unconstrained optimization algorithms for minimization inside the faces of the box. Several approaches may be employed for computing internal search directions in the large-scale case. In this paper a minimal-memory quasi-Newton approach with secant preconditioners is proposed, taking into account the structure of Augmented Lagrangians that come from the popular Powell-Hestenes-Rockafellar scheme. A combined algorithm, that uses the quasi-Newton formula or a truncated-Newton procedure, depending on the presence of active constraints in the penalty-Lagrangian function, is also suggested. Numerical experiments using the Cute collection are presented.