Absence of the 7-repeat variant of the DRD4 VNTR is associated with drifting sustained attention in children with ADHD but not in controls

Many genetic studies have demonstrated an association between the 7-repeat (7r) allele of a 48-base pair variable number of tandem repeats (VNTR) in exon 3 of the DRD4 gene and the phenotype of attention deficit hyperactivity disorder (ADHD). Previous studies have shown inconsistent associations between the 7r allele and neurocognitive performance in children with ADHD. We investigated the performance of 128 children with and without ADHD on the Fixed and Random versions of the Sustained Attention to Response Task (SART). We employed timeseries analyses of reaction-time data to allow a fine-grained analysis of reaction time variability, a candidate endophenotype for ADHD. Children were grouped into either the 7r-present group (possessing at least one copy of the 7r allele) or the 7r-absent group. The ADHD group made significantly more commission errors and was significantly more variable in RT in terms of fast moment-to-moment variability than the control group, but no effect of genotype was found on these measures. Children with ADHD without the 7r allele made significantly more omission errors, were significantly more variable in the slow frequency domain and showed less sensitivity to the signal (d') than those children with ADHD the 7r and control children with or without the 7r. These results highlight the utility of time-series analyses of reaction time data for delineating the neuropsychological deficits associated with ADHD and the DRD4 VNTR. Absence of the 7-repeat allele in children with ADHD is associated with a neurocognitive profile of drifting sustained attention that gives rise to variable and inconsistent performance. (c) 2008 Wiley-Liss, Inc.

An allosteric potentiator of M4 mAChR modulates hippocampal synaptic transmission.

Muscarinic acetylcholine receptors (mAChRs) provide viable targets for the treatment of multiple central nervous system disorders. We have used cheminformatics and medicinal chemistry to develop new, highly selective M₄ allosteric potentiators. VU10010, the lead compound, potentiates the M₄ response to acetylcholine 47-fold while having no activity at other mAChR subtypes. This compound binds to an allosteric site on the receptor and increases affinity for acetylcholine and coupling to G proteins. Whole-cell patch clamp recordings revealed that selective potentiation of M₄ with VU10010 increases carbachol-induced depression of transmission at excitatory but not inhibitory synapses in the hippocampus. The effect was not mimicked by an inactive analog of VU10010 and was absent in M₄ knockout mice. Selective regulation of excitatory transmission by M₄ suggests that targeting of individual mAChR subtypes could be used to differentially regulate specific aspects of mAChR modulation of function in this important forebrain structure.

Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash

Self-compacting concrete (SCC) flows into place and around obstructions under its own weight to fill the formwork completely and self-compact without any segregation and blocking. Elimination of the need for compaction leads to better quality concrete and substantial improvement of working conditions. This investigation aimed to show possible applicability of genetic programming (GP) to model and formulate the fresh and hardened properties of self-compacting concrete (SCC) containing pulverised fuel ash (PFA) based on experimental data. Twenty-six mixes were made with 0.38 to 0.72 water-to-binder ratio (W/B), 183–317 kg/m³ of cement content, 29–261 kg/m³ of PFA, and 0 to 1% of superplasticizer, by mass of powder. Parameters of SCC mixes modelled by genetic programming were the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength at 7, 28 and 90 days. GP is constructed of training and testing data using the experimental results obtained in this study. The results of genetic programming models are compared with experimental results and are found to be quite accurate. GP has showed a strong potential as a feasible tool for modelling the fresh properties and the compressive strength of SCC containing PFA and produced analytical prediction of these properties as a function as the mix ingredients. Results showed that the GP model thus developed is not only capable of accurately predicting the slump flow, JRing combined to the Orimet, JRing combined to cone, and the compressive strength used in the training process, but it can also effectively predict the above properties for new mixes designed within the practical range with the variation of mix ingredients.

sgen1: A generator of small but difficult satisfiability benchmarks

The satisfiability problem is known to be NP-Complete; therefore, there should be relatively small problem instances that take a very long time to solve. However, most of the smaller benchmarks that were once thought challenging, especially the satisfiable ones, can be processed quickly by modern SAT-solvers. We describe and make available a generator that produces both unsatisfiable and, more significantly, satisfiable formulae that take longer to solve than any others known. At the two most recent international SAT Competitions, the smallest unsolved benchmarks were created by this generator. We analyze the results of all solvers in the most recent competition when applied to these benchmarks and also present our own more focused experiments.