A Influência Do Carboidrato Na Ativação Cerebral Durante Exercício Físico

The use of carbohydrate (CH) as a nutritional supplement is related to better sports performance. Some studies have noted a relationship between consumption and brain activation influencing the performance. The objective of this study was to evaluate the influence of CH consumption in the activation of certain brain areas during exercise, performed simultaneously the acquisition of functional magnetic resonance imaging (fMRI). Ten men cyclists (32.1 ± 4.1 years, weight 76.8 ± 14.6 kg) performed a pedaling exercise protocol, with high intensity (Borg Scale), on a cycleergometer coupled to magnetic resonance (MR) and ingested 50g CH or placebo in the range of two sets of exercise. The CH ingestion showed influence on brain areas during exercise, activating areas related to decision-making (insula) and motivation (limbic system) and mainly disabling motor areas (frontal lobe) and introspection (precuneus). With the use of placebo, there was also activation of important areas in the motivation of the individual (posterior cingulate). In addition, areas associated with the initiation and maintenance of movement, located on the front lobe and cerebellum, was active. With the use of CH, areas important for maintenance of the exercise have been activated showing that supplementation can influence the brain activation during exercise to improve the sport performance.12111512

Description of diffusive and propagative behavior on fractals

The known properties of diffusion on fractals are reviewed in order to give a general outlook of these dynamic processes. After that, we propose a description developed in the context of the intrinsic metric of fractals, which leads us to a differential equation able to describe diffusion in real fractals in the asymptotic regime. We show that our approach has a stronger physical justification than previous works on this field. The most important result we present is the introduction of a dependence on time and space for the conductivity in fractals, which is deduced by scaling arguments and supported by computer simulations. Finally, the diffusion equation is used to introduce the possibility of reaction-diffusion processes on fractals and analyze their properties. Specifically, an analytic expression for the speed of the corresponding travelling fronts, which can be of great interest for application purposes, is derived

Patterns Of Seizure Control In Patients With Mesial Temporal Lobe Epilepsy With And Without Hippocampus Sclerosis [padrões De Controle De Crises Em Pacientes Com Epilepsia De Lobo Temporal Com Ou Sem Esclerose Hipocampal]

Objective: Patients with mesial temporal lobe epilepsy (MTLE) may present unstable pattern of seizures. We aimed to evaluate the occurrence of relapse-remitting seizures in MTLE with (MTLE-HS) and without (MTLE-NL) hippocampal sclerosis. Method: We evaluated 172 patients with MTLE-HS (122) or MTLE-NL (50). Relapse-remitting pattern was defined as periods longer than two years of seizure-freedom intercalated with seizure recurrence. “Infrequent seizures” was considered as up to three seizures per year and “frequent seizures” as any period of seizures higher than that. Results: Thirty-seven (30%) MTLE-HS and 18 (36%) MTLE-NL patients had relapse-remitting pattern (X2, p = 0.470). This was more common in those with infrequent seizures (X2, p < 0.001). Twelve MTLE-HS and one MTLE-NL patients had prolonged seizure remission between the first and second decade of life (X2, p = 0.06). Conclusion: Similar proportion of MTLE-HS or MTLE-NL patients present relapse-remitting seizures and this occurs more often in those with infrequent seizures.7327982Kwan, P., Brodie, M.J., Early identification of refractory epilepsy (2010) N Engl Jmed, 342 (5), pp. 314-319. , http://dx.doi.org/10.1056/NEJM200002033420503Goodridge, D.M., Shorvon, S.D., Epileptic seizures in a population of 6000. II: Treatment and prognosis (1983) Br Med J, 287 (6393), pp. 645-647. , http://dx.doi.org/10.1136/bmj.287.6393.645Brodie, M.J., Barry, S., Bamagous, G.A., Norrie, J.D., Kwan, P., Patterns of treatment response in newly diagnosed epilepsy (2012) Neurology, 78 (20), pp. 1548-1554. , http://dx.doi.org/10.1212/WNL.0b013e3182563b19Semah, F., Picot, M.C., Adam, C., Broglin, D., Arzimanoglou, A., Bazin, B., Is the underlying cause of epilepsy a major prognostic factor for recurrence? (1998) Neurology, 51 (5), pp. 1256-1262. , http://dx.doi.org/10.1212/WNL.51.5.1256Hauser, W.A., Annegers, J.F., Kurland, L.T., Prevalence of epilepsy in Rochester, Minnesota: 1940-1980 (1991) Epilepsia, 32 (4), pp. 429-445. , http://dx.doi.org/10.1111/j.1528-1157.1991.tb04675.xFrench, J.A., Williamson, P.D., Thadani, V.M., Darcey, T.M., Mattson, R.H., Spencer, S.S., Characteristics of medial temporal lobe epilepsy: I. Results of history and physical examination (1993) Ann Neurol, 34 (6), pp. 774-780. , http://dx.doi.org/10.1002/ana.410340604Berg, A.T., The natural history of mesial temporal lobe epilepsy (2008) Curr Opin Neurol, 21 (2), pp. 173-178. , http://dx.doi.org/10.1097/WCO.0b013e3282f36ccdSillanpää, M., Schmidt, D., Natural history of treated childhood-onset epilepsy: Prospective, long-term population based study (2006) Brain, 129, pp. 617-624. , http://dx.doi.org/10.1093/brain/awh726Coan, A.C., Kubota, B.Y., Bergo, F., Campos, B.M., Cendes, F., 3T MRI quantification of hippocampal volume and signal in mesial temporal lobe epilepsy improves detection of hippocampal sclerosis (2014) AJNR am J Neuroradiol, 35 (1), pp. 77-83. , http://dx.doi.org/10.3174/ajnr.A3640Wieser, H.G., ILAE Commission on Neurosurgery of Epilepsy. Mesial temporal lobe epilepsy with hippocampal sclerosis (2004) Epilepsia, 45 (6), pp. 695-714. , http://dx.doi.org/10.1111/j.0013-9580.2004.09004.xKwan, P., Arzimanoglou, A., Berg, A.T., Brodie, M.J., Allen Hauser, W., Mathern, G., Definition of drug resistant epilepsy: Consensus proposal by the ad hoc Task Force of the ILAE Commission on Therapeutic Strategies (2010) Epilepsia, 51 (6), pp. 1069-1077. , http://dx.doi.org/10.1111/j.1528-1167.2009.02397.xVan Paesschen, W., Connelly, A., King, M.D., Jackson, G.D., Duncan, J.S., The spectrum of hippocampal sclerosis: A quantitative magnetic resonance imaging study (1997) Ann Neurol, 41 (1), pp. 41-51. , http://dx.doi.org/10.1002/ana.410410109Cohen-Gadol, A.A., Bradley, C.C., Williamson, A., Kim, J.H., Westerveld, M., Duckrow, R.B., Normal magnetic resonance imaging and medial temporal lobe epilepsy: The clinical syndrome of paradoxical temporal lobe epilepsy (2005) J Neurosur, 102 (5), pp. 902-909. , http://dx.doi.org/10.3171/jns.2005.102.5.0902Pittau, F., Bisulli, F., Mai, R., Fares, J.E., Vignatelli, L., Labate, A., Prognostic factors in patients with mesial temporal lobe epilepsy (2009) Epilepsia, 50, pp. 41-44. , http://dx.doi.org/10.1111/j.1528-1167.2008.01969.xKobayashi, E., Lopes-Cendes, I., Guerreiro, C.A., Sousa, S.C., Guerreiro, M.M., Cendes, F., Seizure outcome and hippocampal atrophy in familial mesial temporal lobe epilepsy (2001) Neurology, 56 (2), pp. 166-172. , http://dx.doi.org/10.1212/WNL.56.2.166Labate, A., Gambardella, A., Ermann, E., Aguglia, U., Cendes, F., Berkovic, S.F., Benign mesial temporal lobe epilepsy (2011) Nat Rev Neurol, 7 (4), pp. 237-240. , http://dx.doi.org/10.1038/nrneurol.2010.21

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types