A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment. Protein Sci. 12,923-929]. However, the major limitation of previous methods was in ability in predicting Tariquidar clinical trial gamma-turn types. In a recent investigation we introduced a sequence based predictor model for predicting gamma-turn types in proteins [Jahandideh, S., Sabet Sarvestani, A., Abdolmaleki, P., Jahandideh, M., Barfeie, M, 2007a. gamma-turn types prediction in proteins using the support vector machines. J. Theor. Biol. 249,785-790]. In the present work, in order to analyze the effect
of sequence and structure in the formation of gamma-turn types and predicting gamma-turn types in proteins, we applied novel hybrid neural discriminant modeling procedure. As the result, this study clarified the efficiency of using the statistical model preprocessors in determining click here the effective parameters. Moreover, the optimal structure of neural network can be simplified by a preprocessor in the first stage of hybrid approach, there by reducing the needed time for neural network training procedure in the second stage and the probability of over fitting occurrence decreased and a high precision and reliability obtained in this way. (C) 2009
Elsevier Ltd. All rights reserved.”
“Background: Children with Attention Deficit Hyperactivity Disorder (ADHD) have deficits in motivation and attention that can be ameliorated with the indirect dopamine agonist Methylphenidate (MPH). We used functional magnetic resonance imaging (fMRI) to investigate the effects of MPH in medication-naive children with ADHD on the activation and functional from connectivity of “”cool”" attentional as well as “”hot”" motivation networks.
Methods: 13
medication-naive children with ADHD were scanned twice, under either an acute clinical dose of MPH or Placebo, in a randomised, double-blind design, while they performed a rewarded continuous performance task that measured vigilant selective attention and the effects of reward. Brain activation and functional connectivity was compared to that of 13 healthy age-matched controls to test for normalisation effects of MPH.
Results: MPH normalised performance deficits that were observed in children with ADHD compared to controls. Under placebo, children with ADHD showed reduced activation and functional inter-connectivity in bilateral fronto-striato-parieto-cerebellar networks during the attention condition, but enhanced activation in the orbitofrontal and superior temporal cortices for reward. MPH within children with ADHD enhanced the activation of fronto-striato-cerebellar and parieto-temporal regions.