Endurance training activates AMP-activated protein kinase, increases expression of uncoupling protein 2 and reduces insulin secretion from rat pancreatic islets

Endurance exercise is known to enhance peripheral insulin sensitivity and reduce insulin secretion. However, it is unknown whether the latter effect is due to the reduction in plasma substrate availability or alterations in beta-cell secretory machinery. Here, we tested the hypothesis that endurance exercise reduces insulin secretion by altering the intracellular energy-sensitive AMP-activated kinase (AMPK) signaling pathway. Male Wistar rats were submitted to endurance protocol training one, three, or five times per week, over 8 weeks. After that, pancreatic islets were isolated, and glucose-induced insulin secretion (GIIS), glucose transporter 2 (GLUT2) protein content, total and phosphorylated calmodulin kinase kinase (CaMKII), and AMPK levels as well as peroxisome proliferator-activated receptor-gamma coactivator-1-alpha (PGC-1 alpha) and uncoupling protein 2 (UCP2) content were measured. After 8 weeks, chronic endurance exercise reduced GIIS in a dose-response manner proportionally to weekly exercise frequency. Contrariwise, increases in GLUT2 protein content, CaMKII and AMPK phosphorylation levels were observed. These alterations were accompanied by an increase in UCP2 content, probably mediated by an enhancement in PGC-1 alpha protein expression. In conclusion, chronic endurance exercise induces adaptations in beta-cells leading to a reduction in GIIS, probably by activating the AMPK signaling pathway. Journal of Endocrinology (2011) 208, 257-264

5-HT(1B) receptor in the suprachiasmatic nucleus of the common marmoset (Callithrix jacchus)

Serotonin (5-HT) is involved in the fine adjustments at several brain centers including the core of the mammal circadian timing system (CTS) and the hypothalamic suprachiasmatic nucleus (SCN). The SCN receives massive serotonergic projections from the midbrain raphe nuclei, whose inputs are described in rats as ramifying at its ventral portion overlapping the retinohypothalamic and geniculohypothalamic fibers. In the SCN, the 5-HT actions are reported as being primarily mediated by the 5-HT1 type receptor with noted emphasis for 5-HT(1B) subtype, supposedly modulating the retinal input in a presynaptic way. In this study in a New World primate species, the common marmoset (Callithrix jacchus), we showed the 5-HT(1B) receptor distribution at the dorsal SCN concurrent with a distinctive location of 5-HT-immunoreactive fibers. This finding addresses to a new discussion on the regulation and synchronization of the circadian rhythms in recent primates. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Exercise training enhances rat pancreatic islets anaplerotic enzymes content despite reduced insulin secretion

Endurance exercise has been shown to reduce pancreatic islets glucose-stimulated insulin secretion (GSIS). Anaplerotic/cataplerotic pathways are directly related to GSIS signaling. However, the effect of endurance training upon pancreatic islets anaplerotic enzymes is still unknown. In this sense, we tested the hypothesis that endurance exercise decreases GSIS by reducing anaplerotic/cataplerotic enzymes content. Male Wistar rats were randomly assigned to one of the four experimental groups as follows: control sedentary group (CTL), trained 1 day per week (TRE1x), trained 3 days per week (TRE3x) and trained 5 days per week (TRE5x) and submitted to an 8 weeks endurance-training protocol. After the training protocol, pancreatic islets were isolated and incubated with basal (2.8 mM) and stimulating (16.7 mM) glucose concentrations for GSIS measurement by radioimmunoassay. In addition, pyruvate carboxylase (PYC), pyruvate dehydrogenase (PDH), pyruvate dehydrogenase kinase 4 (PDK4), ATP-citrate lyase (ACL) and glutamate dehydrogenase (GDH) content were quantified by western blotting. Our data showed that 8 weeks of chronic endurance exercise reduced GSIS by 50% in a dose-response manner according to weekly exercise frequency. PYC showed significant twofold increase in TRE3x. PYC enhancement was even higher in TRE5x (p < 0.0001). PDH and PDK4 reached significant 25 and 50% enhancement, respectively compared with CTL. ACL and GDH also reported significant 50 and 75% increase, respectively. The absence of exercise-induced correlations among GSIS and anaplerotic/cataplerotic enzymes suggests that exercise may control insulin release by activating other signaling pathways. The observed anaplerotic and cataplerotic enzymes enhancement might be related to beta-cell surviving rather than insulin secretion.

Preliminary report: Leucine supplementation enhances glutamate dehydrogenase expression and restores glucose-induced insulin secretion in protein-malnourished rats

Low-protein diet impairs insulin secretion in response to nutrients and may induce several metabolic disorders including diabetes, obesity, and cardiovascular disease. In the present study, the influence of leucine supplementation on glutamate dehydrogenase (GDH) expression and glucose-induced insulin secretion (GIIS) was investigated in malnourished rats. Four groups were fed with different diets for 12 weeks: a normal-protein diet (17%) without or with leucine supplementation or a low (6%)-protein diet without (LP) or with leucine supplementation (LPL). Leucine (1.5%) was supplied in the drinking water. Western blotting analysis revealed reduced GIN! expression in LP, whereas LPL displayed improved GDH expression, similar to control. The GHS and leucinc-induced insulin release were also enhanced in LPL compared with LP and similar to those observed in rats fed a normal-protein diet without leucine supplementation. In addition, GDH allosteric activators produced an increased insulin secretion in LPL. These findings indicate that leucine supplementation was able to increase GDH expression leading to Cl IS restoration, probably by improved leucine metabolic pathways. (C) 2010 Elsevier Inc. All rights reserved.

Screening of ARHSP-TCC Patients Expands the Spectrum of SPG11 Mutations and Includes a Large Scale Gene Deletion

Autosomal recessive spastic paraplegia with thinning of corpus callosum (ARHSP-TCC) is a complex form of HSP initially described in Japan but subsequently reported to have a worldwide distribution with a particular high frequency in multiple families from the Mediterranean basin. We recently showed that ARHSP-TCC is commonly associated with mutations in SPG11/KIAA1840 on chromosome 15q. We have now screened a collection of new patients mainly originating from Italy and Brazil, in order to further ascertain the spectrum of mutations in SPG11, enlarge the ethnic origin of SPG11 patients, determine the relative frequency at the level of single Countries (i.e., Italy), and establish whether there is one or more common mutation. In 25 index cases we identified 32 mutations; 22 are novel, including 9 nonsense, 3 small deletions, 4 insertions, 1 in/del, 1 small duplication, 1 missense, 2 splice-site, and for the first time a large genomic rearrangement. This brings the total number of SPG11 mutated patients in the SPATAX collection to 111 cases in 44 families and in 17 isolated cases, from 16 Countries, all assessed using homogeneous clinical criteria. While expanding the spectrum of mutations in SPG11, this larger series also corroborated the notion that even within apparently homogeneous population a molecular diagnosis cannot be achieved without full gene sequencing. (C) 2008 Wiley-Liss, Inc.

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.

Learning of shared attention in sociable robotics

Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

PedVis: A Structured, Space-Efficient Technique for Pedigree Visualization

Public genealogical databases are becoming increasingly populated with historical data and records of the current population`s ancestors. As this increasing amount of available information is used to link individuals to their ancestors, the resulting trees become deeper and more dense, which justifies the need for using organized, space-efficient layouts to display the data. Existing layouts are often only able to show a small subset of the data at a time. As a result, it is easy to become lost when navigating through the data or to lose sight of the overall tree structure. On the contrary, leaving space for unknown ancestors allows one to better understand the tree`s structure, but leaving this space becomes expensive and allows fewer generations to be displayed at a time. In this work, we propose that the H-tree based layout be used in genealogical software to display ancestral trees. We will show that this layout presents an increase in the number of displayable generations, provides a nicely arranged, symmetrical, intuitive and organized fractal structure, increases the user`s ability to understand and navigate through the data, and accounts for the visualization requirements necessary for displaying such trees. Finally, user-study results indicate potential for user acceptance of the new layout.

Two-Phase Mapping for Projecting Massive Data Sets

Most multidimensional projection techniques rely on distance (dissimilarity) information between data instances to embed high-dimensional data into a visual space. When data are endowed with Cartesian coordinates, an extra computational effort is necessary to compute the needed distances, making multidimensional projection prohibitive in applications dealing with interactivity and massive data. The novel multidimensional projection technique proposed in this work, called Part-Linear Multidimensional Projection (PLMP), has been tailored to handle multivariate data represented in Cartesian high-dimensional spaces, requiring only distance information between pairs of representative samples. This characteristic renders PLMP faster than previous methods when processing large data sets while still being competitive in terms of precision. Moreover, knowing the range of variation for data instances in the high-dimensional space, we can make PLMP a truly streaming data projection technique, a trait absent in previous methods.

Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.

Interactive Vector Field Feature Identification

We introduce a flexible technique for interactive exploration of vector field data through classification derived from user-specified feature templates. Our method is founded on the observation that, while similar features within the vector field may be spatially disparate, they share similar neighborhood characteristics. Users generate feature-based visualizations by interactively highlighting well-accepted and domain specific representative feature points. Feature exploration begins with the computation of attributes that describe the neighborhood of each sample within the input vector field. Compilation of these attributes forms a representation of the vector field samples in the attribute space. We project the attribute points onto the canonical 2D plane to enable interactive exploration of the vector field using a painting interface. The projection encodes the similarities between vector field points within the distances computed between their associated attribute points. The proposed method is performed at interactive rates for enhanced user experience and is completely flexible as showcased by the simultaneous identification of diverse feature types.

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For this reason we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and nearly equi-areal surface patches, and noise robustness. We show how the evenly distributed patches can be exploited for generating multiresolution high quality uniform meshes. Additionally, our decomposition permits a natural means for carrying out wavelet methods, resulting in an intuitive method for producing feature-sensitive meshes at multiple scales. Published by Elsevier Ltd.

Verifiable Visualization for Isosurface Extraction

Visual representations of isosurfaces are ubiquitous in the scientific and engineering literature. In this paper, we present techniques to assess the behavior of isosurface extraction codes. Where applicable, these techniques allow us to distinguish whether anomalies in isosurface features can be attributed to the underlying physical process or to artifacts from the extraction process. Such scientific scrutiny is at the heart of verifiable visualization - subjecting visualization algorithms to the same verification process that is used in other components of the scientific pipeline. More concretely, we derive formulas for the expected order of accuracy (or convergence rate) of several isosurface features, and compare them to experimentally observed results in the selected codes. This technique is practical: in two cases, it exposed actual problems in implementations. We provide the reader with the range of responses they can expect to encounter with isosurface techniques, both under ""normal operating conditions"" and also under adverse conditions. Armed with this information - the results of the verification process - practitioners can judiciously select the isosurface extraction technique appropriate for their problem of interest, and have confidence in its behavior.

The Schenberg spherical gravitational wave detector: the first commissioning runs

Here we present a status report of the first spherical antenna project equipped with a set of parametric transducers for gravitational detection. The Mario Schenberg, as it is called, started its commissioning phase at the Physics Institute of the University of Sao Paulo, in September 2006, under the full support of FAPESP. We have been testing the three preliminary parametric transducer systems in order to prepare the detector for the next cryogenic run, when it will be calibrated. We are also developing sapphire oscillators that will replace the current ones thereby providing better performance. We also plan to install eight transducers in the near future, six of which are of the two-mode type and arranged according to the truncated icosahedron configuration. The other two, which will be placed close to the sphere equator, will be mechanically non-resonant. In doing so, we want to verify that if the Schenberg antenna can become a wideband gravitational wave detector through the use of an ultra-high sensitivity non-resonant transducer constructed using the recent achievements of nanotechnology.