Decoupled Roles for the Atypical,Bifurcated Binding Pocket of the ybfF Hydrolase

Serine hydrolases have diverse intracellular substrates, biological functions, and structural plasticity, and are thus important for biocatalyst design. Amongst serine hydrolases, the recently described ybfF enzyme family are promising novel biocatalysts with an unusual bifurcated substrate‐binding cleft and the ability to recognize commercially relevant substrates. We characterized in detail the substrate selectivity of a novel ybfF enzyme from Vibrio cholerae (Vc‐ybfF) by using a 21‐member library of fluorogenic ester substrates. We assigned the roles of the two substrate‐binding clefts in controlling the substrate selectivity and folded stability of Vc‐ybfF by comprehensive substitution analysis. The overall substrate preference of Vc‐ybfF was for short polar chains, but it retained significant activity with a range of cyclic and extended esters. This broad substrate specificity combined with the substitutional analysis demonstrates that the larger binding cleft controls the substrate specificity of Vc‐ybfF. Key selectivity residues (Tyr116, Arg120, Tyr209) are also located at the larger binding pocket and control the substrate specificity profile. In the structure of ybfF the narrower binding cleft contains water molecules prepositioned for hydrolysis, but based on substitution this cleft showed only minimal contribution to catalysis. Instead, the residues surrounding the narrow binding cleft and at the entrance to the binding pocket contributed significantly to the folded stability of Vc‐ybfF. The relative contributions of each cleft of the binding pocket to the catalytic activity and folded stability of Vc‐ybfF provide a valuable map for designing future biocatalysts based on the ybfF scaffold.     

Independent components of magnetoencephalography: localization

We applied second-order blind identification (SOBI), an independent component analysis method, to MEG data collected during cognitive tasks. We explored SOBI's ability to help isolate underlying neuronal sources with relatively poor signal-to-noise ratios, allowing their identification and localization. We compare localization of the SOBI-separated components to localization from unprocessed sensor signals, using an equivalent current dipole modeling method. For visual and somatosensory modalities, SOBI preprocessing resulted in components that can be localized to physiologically and anatomically meaningful locations. Furthermore, this preprocessing allowed the detection of neuronal source activations that were otherwise undetectable. This increased probability of neuronal source detection and localization can be particularly beneficial for MEG studies of higher-level cognitive functions, which often have greater signal variability and degraded signal-to-noise ratios than sensory activation tasks.     

Effects of alcohol versus expectancy for alcohol on the incidence of graffiti following an experimental task.

Experimentally manipulated the conditions of beverage content and expectancy for alcohol in 29 heavy social-drinking (as determined by the Drinking Practices Questionnaire) male undergraduates. After completing a pencil-and-paper task, Ss found themselves in a situation where graffiti could apparently be written in and around the immediate surroundings with impunity. Regardless of expectations, Ss who actually drank alcohol were significantly more likely to write graffiti in this situation than were Ss who did not drink alcohol. This finding supports the importance of alcohol rather than expectancy as a causal influence on this form of disinhibited behavior. (12 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Minimax mutual information approach for independent component analysis

Minimum output mutual information is regarded as a natural criterion for independent component analysis (ICA) and is used as the performance measure in many ICA algorithms. Two common approaches in information-theoretic ICA algorithms are minimum mutual information and maximum output entropy approaches. In the former approach, we substitute some form of probability density function (pdf) estimate into the mutual information expression, and in the latter we incorporate the source pdf assumption in the algorithm through the use of nonlinearities matched to the corresponding cumulative density functions (cdf). Alternative solutions to ICA use higher-order cumulant-based optimization criteria, which are related to either one of these approaches through truncated series approximations for densities. In this article, we propose a new ICA algorithm motivated by the maximum entropy principle (for estimating signal distributions). The optimality criterion is the minimum output mutual information, where the estimated pdfs are from the exponential family and are approximate solutions to a constrained entropy maximization problem. This approach yields an upper bound for the actual mutual information of the output signals - hence, the name minimax mutual information ICA algorithm. In addition, we demonstrate that for a specific selection of the constraint functions in the maximum entropy density estimation procedure, the algorithm relates strongly to ICA methods using higher-order cumulants.     

Extracellular recordings from patterned neuronal networks using planar microelectrode arrays

Neuronal cell networks have been reconstructed on planar microelectrode arrays (MEAs) from dissociated hippocampal pyramidal neurons. Microcontact printing (microCP) and a photoresist-liftoff method were used to selectively localize poly-L-lysine (PLL) on the surface of MEAs. Haptotaxis led to the organization of the neurons into networks localized adjacent to microelectrodes. Various grids of PLL with 2-25-microm-wide lines spaced by 50-200 microm with 15-25-microm nodes at intersection points were used to guide cell body attachment and neurite outgrowth. Bursting activity with spike amplitude attenuation was observed, and multichannel recordings detected instances of coincident firing activity. Finally, we present here an extracellular recording from a approximately 2 microm bundle of guided neurites.