Identifying rate-limiting nodes in large-scale cortical networks for visuospatial processing: an illustration using fMRI

With the advent of functional neuroimaging techniques, in particular functional magnetic resonance imaging (fMRI), we have gained greater insight into the neural correlates of visuospatial function. However, it may not always be easy to identify the cerebral regions most specifically associated with performance on a given task. One approach is to examine the quantitative relationships between regional activation and behavioral performance measures. In the present study, we investigated the functional neuroanatomy of two different visuospatial processing tasks, judgement of line orientation and mental rotation. Twenty-four normal participants were scanned with fMRI using blocked periodic designs for experimental task presentation. Accuracy and reaction time (RT) to each trial of both activation and baseline conditions in each experiment was recorded. Both experiments activated dorsal and ventral visual cortical areas as well as dorsolateral prefrontal cortex. More regionally specific associations with task performance were identified by estimating the association between (sinusoidal) power of functional response and mean RT to the activation condition; a permutation test based on spatial statistics was used for inference. There was significant behavioral-physiological association in right ventral extrastriate cortex for the line orientation task and in bilateral (predominantly right) superior parietal lobule for the mental rotation task. Comparable associations were not found between power of response and RT to the baseline conditions of the tasks. These data suggest that one region in a neurocognitive network may be most strongly associated with behavioral performance and this may be regarded as the computationally least efficient or rate-limiting node of the network.

Aluminophosphate-based mesoporous molecular sieves: synthesis and characterization of TAPOs

Mesoporous Ti-substituted aluminophosphates (AlPOs) with a hexagonal, cubic and lamellar pore structure, characteristic of MCM-41, MCM-48. and MCM-50, respectively, were synthesized. The stability of these mesophases upon template removal was studied. The pore structures, surface properties, and local atom environments of Al, P, and Ti of the hexagonal and cubic Ti-containing mesoporous products were extensively characterized using X-ray diffraction, magic angle spinning nuclear magnetic resonance, AAS, XPS, ultraviolet-visible, and adsorption of nitrogen and water vapor techniques while the lamellar mesophase was not further characterized due to its very poor thermal stability. Ti-containing mesoporous AlPO materials show a reasonable thermal stability upon template removal, a hydrophilic surface property, and high porosity showing application potentials in catalytic oxidation of hydrocarbons. (C) 2001 Elsevier Science B,V. All rights reserved.

Charge ordering and antiferromagnetic exchange in layered molecular crystals of the theta type

We consider the electronic properties of layered molecular crystals of the type theta -D(2)A where A is an anion and D is a donor molecule such as bis-(ethylenedithia-tetrathiafulvalene) (BEDT-TTF), which is arranged in the theta -type pattern within the layers. We argue that the simplest strongly correlated electron model that can describe the rich phase diagram of these materials is the extended Hubbard model on the square lattice at one-quarter filling. In the limit where the Coulomb repulsion on a single site is large, the nearest-neighbor Coulomb repulsion V plays a crucial role. When V is much larger than the intermolecular hopping integral t the ground state is an insulator with charge ordering. In this phase antiferromagnetism arises due to a novel fourth-order superexchange process around a plaquette on the square lattice. We argue that the charge ordered phase is destroyed below a critical nonzero value V, of the order of t. Slave-boson theory is used to explicitly demonstrate this for the SU(N) generalization of the model, in the large-N limit. We also discuss the relevance of the model to the all-organic family beta-(BEDT-TTF)(2)SF5YSO3 where Y=CH2CF2, CH2, CHF.

Enzymology and molecular biology of prokaryotic sulfite oxidation

Despite its toxicity, sulfite plays a key role in oxidative sulfur metabolism and there are even some microorganisms which can use it as sole electron source. Sulfite is the main intermediate in the oxidation of sulfur compounds to sulfate, the major product of most dissimilatory sulfur-oxidizing prokaryotes. Two pathways of sulfite oxidation are known: (1) direct oxidation to sulfate catalyzed by a sulfite: acceptor oxidoreductase, which is thought to be a molybdenum-containing enzyme; (2) indirect oxidation under the involvement of the enzymes adenylylsulfate (APS) reductase and ATP sulfurylase and/or adenylylsulfate phosphate adenylyltransferase with APS as an intermediate. The latter pathway allows substrate phosphorylation and occurs in the bacterial cytoplasm. Direct oxidation appears to have a wider distribution; however, a redundancy of pathways has been described for diverse photo- or chemotrophic, sulfite-oxidizing prokaryotes. In many pro- and also eukaryotes sulfite is formed as a degradative product from molecules containing sulfur as a heteroatom. In these organisms detoxification of sulfite is generally achieved by direct oxidation to sulfate. (C) 2001 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Clinical and molecular genetics of myoclonic-astatic epilepsy and severe myoclonic epilepsy in infancy (Dravet syndrome)

The majority of severe epileptic encephalopathies of early childhood are symptomatic where a clear etiology is apparent. There is a small subgroup, however, where no etiology is found on imaging and metabolic studies, and genetic factors are important. Myoclonic-astatic epilepsy (MAE) and severe myoclonic epilepsy in infancy (SMEI), also known as Dravet syndrome, are epileptic encephalopathies where multiple seizure types begin in the first few years of life associated with developmental slowing. Clinical and molecular genetic studies of the families of probands with MAE and SMEI suggest a genetic basis. MAE was originally identified as part of the genetic epilepsy syndrome generalized epilepsy with febrile seizures plus (GEFS(+)). Recent clinical genetic studies suggest that SMEI forms the most severe end of the spectrum of the GEFS(+). GEF(+) has now been associated with molecular defects in three sodium channel subunit genes and a GABA subunit gene. Molecular defects of these genes have been identified in patients with MAE and SMEI. Interestingly, the molecular defects in MAE have been found in the setting of large GEFS(+) pedigrees, whereas, more severe truncation mutations arising de novo have been identified in patients with SMEI. It is likely that future molecular studies will shed light on the interaction of a number of genes, possibly related to the same or different ion channels, which result in a severe phenotype such as MAE and SMEI. (C) 2001 Elsevier Science B.V. All rights reserved.

Porous clays and pillared clays-based catalysts. Part 2: A review of the catalytic and molecular sieve applications

Metal oxide pillared clay (PILC) possesses several interesting properties, such as large surface area, high pore volume and tunable pore size (from micropore to mesopore), high thermal stability, strong surface acidity and catalytic active substrates/metal oxide pillars. These unique characteristics make PILC an attractive material in catalytic reactions. It can be made either as catalyst support or directly used as catalyst. This paper is a continuous work from Kloprogge's review (J.T. Kloprogge, J. Porous Mater. 5, 5 1998) on the synthesis and properties of smectites and related PILCs and will focus on the diverse applications of clay pillared with different types of metal oxides in the heterogeneous catalysis area and adsorption area. The relation between the performance of the PILC and its physico-chemical features will be addressed.

Methods for prediction of peptide binding to MHC molecules: A comparative study

Background: A variety of methods for prediction of peptide binding to major histocompatibility complex (MHC) have been proposed. These methods are based on binding motifs, binding matrices, hidden Markov models (HMM), or artificial neural networks (ANN). There has been little prior work on the comparative analysis of these methods. Materials and Methods: We performed a comparison of the performance of six methods applied to the prediction of two human MHC class I molecules, including binding matrices and motifs, ANNs, and HMMs. Results: The selection of the optimal prediction method depends on the amount of available data (the number of peptides of known binding affinity to the MHC molecule of interest), the biases in the data set and the intended purpose of the prediction (screening of a single protein versus mass screening). When little or no peptide data are available, binding motifs are the most useful alternative to random guessing or use of a complete overlapping set of peptides for selection of candidate binders. As the number of known peptide binders increases, binding matrices and HMM become more useful predictors. ANN and HMM are the predictive methods of choice for MHC alleles with more than 100 known binding peptides. Conclusion: The ability of bioinformatic methods to reliably predict MHC binding peptides, and thereby potential T-cell epitopes, has major implications for clinical immunology, particularly in the area of vaccine design.

Magnetic-field-induced superconductivity in layered organic molecular crystals with localized magnetic moments

The synthetic organic compound λ(BETS)2FeCl4 undergoes successive transitions from an antiferromagnetic insulator to a metal and then to a superconductor as a magnetic field is increased. We use a Hubbard-Kondo model to clarify the role of the Fe3+ magnetic ions in these phase transition. In the high-field regime, the magnetic field acting on the electron spins is compensated by the exchange field He due to the magnetic ions. This suggests that the field-induced superconducting state is the same as the zero-field superconducting state which occurs under pressure or when the Fe3+ ions are replaced by non-magnetic Ga3+ ions. We show how Hc can be extracted from the observed splitting of the Shybnikov-de Haas frequencies. Furthermore, we use this method of extracting He to predict the field range for field-induced superconductivity in other materials. We also show that at high fields the spin fluctuations of the localized spins are not important.

Ecological interface design for pasteurizer II: A process description of semantic mapping

Ecological interface design (EID) is proving to be a promising approach to the design of interfaces for complex dynamic systems. Although the principles of EID and examples of its effective use are widely available, few readily available examples exist of how the individual displays that constitute an ecological interface are developed. This paper presents the semantic mapping process within EID in the context of prior theoretical work in this area. The semantic mapping process that was used in developing an ecological interface for the Pasteurizer II microworld is outlined, and the results of an evaluation of the ecological interface against a more conventional interface are briefly presented. Subjective reports indicate features of the ecological interface that made it particularly valuable for participants. Finally, we outline the steps of an analytic process for using EID. The findings presented here can be applied in the design of ecological interfaces or of configural displays for dynamic processes.

Visualization of learning in multilayer perceptron networks using principal component analysis

This paper is concerned with the use of scientific visualization methods for the analysis of feedforward neural networks (NNs). Inevitably, the kinds of data associated with the design and implementation of neural networks are of very high dimensionality, presenting a major challenge for visualization. A method is described using the well-known statistical technique of principal component analysis (PCA). This is found to be an effective and useful method of visualizing the learning trajectories of many learning algorithms such as back-propagation and can also be used to provide insight into the learning process and the nature of the error surface.

Polydnavirus particle proteins with similarities to molecular chaperones, heat-shock protein 70 and calreticulin

Multipartite nucleic acid-containing virus-like particles, known as polydnaviruses, are special structures produced by female parasitoid wasps to deliver wasp components into the body of their host at oviposition. The particles confer protection for the developing parasitoid by passive and active means. Although several genes expressed from the circular DNA of these particles have been identified from various host-parasitoid systems, there is not much known about the structural proteins of these particles. Here we report on two genes encoding Cotesia rubecula particle proteins with similarities to molecular chaperones, calreticulin and heat-shock protein 70.