Evaluation of the EVA Descriptor for QSAR Studies: 3. The use of a Genetic Algorithm to Search for Models with Enhanced Predictive Properties (EVA_GA)

The EVA structural descriptor, based upon calculated fundamental molecular vibrational frequencies, has proved to be an effective descriptor for both QSAR and database similarity calculations. The descriptor is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as structural superposition is not required. The original technique involves a standardisation method wherein uniform Gaussians of fixed standard deviation (σ) are used to smear out frequencies projected onto a linear scale. This smearing function permits the overlap of proximal frequencies and thence the extraction of a fixed dimensional descriptor regardless of the number and precise values of the frequencies. It is proposed here that there exist optimal localised values of σ in different spectral regions; that is, the overlap of frequencies using uniform Gaussians may, at certain points in the spectrum, either be insufficient to pick up relationships where they exist or mix up information to such an extent that significant correlations are obscured by noise. A genetic algorithm is used to search for optimal localised σ values using crossvalidated PLS regression scores as the fitness score to be optimised. The resultant models are then validated against a previously unseen test set of compounds. The performance of EVA_GA is compared to that of EVA and analogous CoMFA studies

The EVA spectral descriptor

The EVA descriptor is derived from fundamental IR- and Raman range molecular vibrational frequencies. EVA is sensitive to 3D structure but has an advantage over field-based 3D-QSAR methods inasmuch as it is invariant to both translation and rotation of the structures concerned and thus structural superposition is not required. The latter property and the demonstration of the effectiveness of the descriptor for QSAR means that EVA has been the subject of a great deal of interest from the modelling community. This review describes the derivation of the descriptor, details its main parameters and how to apply them, and provides an overview of the validation that has been done with the descriptor. A recent enhancement to the technique is described which involves the localised adjustment of variance in such a way that enhanced internal and external predictivity may be obtained. Despite the statistical quality of EVA QSAR models the main draw-back to the descriptor at present is the difficulty associated with back-tracking from a PLS model to an EVA pharmacophore. Brief comment is made on the use of the EVA descriptor for diversity studies and the similarity searching of chemical structure databases

JTpack90: A parallel, object-based, Fortran 90 linear algebra package

The authors have developed an object-based linear algebra package, currently with emphasis on sparse Krylov methods, driven primarily by needs of the Los Alamos National Laboratory parallel unstructured-mesh casting simulation tool Telluride. Support for a number of sparse storage formats, methods, and preconditioners have been implemented, driven primarily by application needs. They describe the object-based Fortran 90 approach, which enhances maintainability, performance, and extensibility, the parallelization approach using a new portable gather/scatter library (PGSLib), current capabilities and future plans, and present preliminary performance results on a variety of platforms

A high resolution finite volume method for efficient parallel simulation of casting processes on unstructured meshes

We discuss selected aspects of a new parallel three-dimensional (3-D) computational tool for the unstructured mesh simulation of Los Alamos National Laboratory (LANL) casting processes. This tool, known as {bold Telluride}, draws upon on robust, high resolution finite volume solutions of metal alloy mass, momentum, and enthalpy conservation equations to model the filling, cooling, and solidification of LANL castings. We briefly describe the current {bold Telluride} physical models and solution methods, then detail our parallelization strategy as implemented with Fortran 90 (F90). This strategy has yielded straightforward and efficient parallelization on distributed and shared memory architectures, aided in large part by new parallel libraries {bold JTpack9O} for Krylov-subspace iterative solution methods and {bold PGSLib} for efficient gather/scatter operations. We illustrate our methodology and current capabilities with source code examples and parallel efficiency results for a LANL casting simulation

The Strong CP Problem and Axions

I describe how the QCD vacuum structure, necessary to resolve the $U(1)_A$ problem, predicts the presence of a P, T and CP violating term proportional to the vacuum angle $\bar{\theta}$. To agree with experimental bounds, however, this parameter must be very small $(\bar{\theta} \leq 10^{-9}$). After briefly discussing some possible other solutions to this, so-called, strong CP problem, I concentrate on the chiral solution proposed by Peccei and Quinn which has associated with it a light pseudoscalar particle, the axion. I discuss in detail the properties and dynamics of axions, focusing particularly on invisible axion models where axions are very light, very weakly coupled and very long-lived. Astrophysical and cosmological bounds on invisible axions are also briefly touched upon.Comment: 14 pages, to appear in the Lecture Notes in Physics volume on Axions, (Springer Verlag

The algebra of lexical semantics

Abstract. The current generative theory of the lexicon relies primar-ily on tools from formal language theory and mathematical logic. Here we describe how a different formal apparatus, taken from algebra and automata theory, resolves many of the known problems with the gener-ative lexicon. We develop a finite state theory of word meaning based on machines in the sense of Eilenberg [11], a formalism capable of de-scribing discrepancies between syntactic type (lexical category) and se-mantic type (number of arguments). This mechanism is compared both to the standard linguistic approaches and to the formalisms developed in AI/KR. 1 Problem Statement In developing a formal theory of lexicography our starting point will be the informal practice of lexicography, rather than the more immediately related for-mal theories of Artificial Intelligence (AI) and Knowledge Representation (KR). Lexicography is a relatively mature field, with centuries of work experience an

Structural Requirements for Dihydrobenzoxazepinone Anthelmintics: Actions against Medically Important and Model Parasites: Trichuris muris, Brugia malayi, Heligmosomoides polygyrus, and Schistosoma mansoni

Nine hundred million people are infected with the soil-transmitted helminths Ascaris lumbricoides (roundworm), hookworm, and Trichuris trichiura (whipworm). However, low single-dose cure rates of the benzimidazole drugs, the mainstay of preventative chemotherapy for whipworm, together with parasite drug resistance, mean that current approaches may not be able to eliminate morbidity from trichuriasis. We are seeking to develop new anthelmintic drugs specifically with activity against whipworm as a priority and previously identified a hit series of dihydrobenzoxazepinone (DHB) compounds that block motility of ex vivo Trichuris muris. Here, we report a systematic investigation of the structure–activity relationship of the anthelmintic activity of DHB compounds. We synthesized 47 analogues, which allowed us to define features of the molecules essential for anthelmintic action as well as broadening the chemotype by identification of dihydrobenzoquinolinones (DBQs) with anthelmintic activity. We investigated the activity of these compounds against other parasitic nematodes, identifying DHB compounds with activity against Brugia malayi and Heligmosomoides polygyrus. We also demonstrated activity of DHB compounds against the trematode Schistosoma mansoni, a parasite that causes schistosomiasis. These results demonstrate the potential of DHB and DBQ compounds for further development as broad-spectrum anthelmintics

Can forest management based on natural disturbances maintain ecological resilience?

Given the increasingly global stresses on forests, many ecologists argue that managers must maintain ecological resilience: the capacity of ecosystems to absorb disturbances without undergoing fundamental change. In this review we ask: Can the emerging paradigm of natural-disturbance-based management (NDBM) maintain ecological resilience in managed forests? Applying resilience theory requires careful articulation of the ecosystem state under consideration, the disturbances and stresses that affect the persistence of possible alternative states, and the spatial and temporal scales of management relevance. Implementing NDBM while maintaining resilience means recognizing that (i) biodiversity is important for long-term ecosystem persistence, (ii) natural disturbances play a critical role as a generator of structural and compositional heterogeneity at multiple scales, and (iii) traditional management tends to produce forests more homogeneous than those disturbed naturally and increases the likelihood of unexpected catastrophic change by constraining variation of key environmental processes. NDBM may maintain resilience if silvicultural strategies retain the structures and processes that perpetuate desired states while reducing those that enhance resilience of undesirable states. Such strategies require an understanding of harvesting impacts on slow ecosystem processes, such as seed-bank or nutrient dynamics, which in the long term can lead to ecological surprises by altering the forest's capacity to reorganize after disturbance

Large-scale pathways-based association study in amyotrophic lateral sclerosis

Sporadic amyotrophic lateral sclerosis (ALS), a devastating neurodegenerative disease, most likely results from complex genetic and environmental interactions. Although a number of association studies have been performed in an effort to find genetic components of sporadic ALS, most of them resulted in inconsistent findings due to a small number of genes investigated in relatively small sample sizes, while the replication of results was rarely attempted. Defects in retrograde axonal transport, vesicle trafficking and xenobiotic metabolism have been implicated in neurodegeneration and motor neuron death both in human disease and animal models. To assess the role of common genetic variation in these pathways in susceptibility to sporadic ALS, we performed a pathway-based candidate gene case-control association study with replication. Furthermore, we determined reliability of whole genome amplified DNA in a large-scale association study. In the first stage of the study, 1277 putative functional and tagging SNPs in 134 genes spanning 8.7 Mb were genotyped in 822 British sporadic ALS patients and 872 controls using whole genome amplified DNA. To detect variants with modest effect size and discriminate among false positive findings 19 SNPs showing a trend of association in the initial screen were genotyped in a replication sample of 580 German sporadic ALS patients and 361 controls. We did not detect strong evidence of association with any of the genes investigated in the discovery sample (lowest uncorrected P-value 0.00037, lowest permutation corrected P-value 0.353). None of the suggestive associations was replicated in a second sample, further excluding variants with moderate effect size. We conclude that common variation in the investigated pathways is unlikely to have a major effect on susceptibility to sporadic ALS. The genotyping efficiency was only slightly decreased (∼1%) and genotyping quality was not affected using whole genome amplified DNA. It is reliable for large scale genotyping studies of diseases such as ALS, where DNA sample collections are limited because of low disease prevalence and short survival time. © 2007 The Author(s)