Strengthening of laterality of verbal and visuospatial functions during childhood and adolescence

Cognitive functions in the child's brain develop in the context of complex adaptive processes, determined by genetic and environmental factors. Little is known about the cerebral representation of cognitive functions during development. In particular, knowledge about the development of right hemispheric (RH) functions is scarce. Considering the dynamics of brain development, localization and lateralization of cognitive functions must be expected to change with age. Twenty healthy subjects (8.6-20.5 years) were examined with fMRI and neuropsychological tests. All participants completed two fMRI tasks known to activate left hemispheric (LH) regions (language tasks) and two tasks known to involve predominantly RH areas (visual search tasks). A laterality index (LI) was computed to determine the asymmetry of activation. Group analysis revealed unilateral activation of the LH language circuitry during language tasks while visual search tasks induced a more widespread RH activation pattern in frontal, superior temporal, and occipital areas. Laterality of language increased between the ages of 8-20 in frontal (r = 0.392, P = 0.049) and temporal (r = 0.387, P = 0.051) areas. The asymmetry of visual search functions increased in frontal (r = -0.525, P = 0.009) and parietal (r = -0.439, P = 0.027) regions. A positive correlation was found between Verbal-IQ and the LI during a language task (r = 0.585, P = 0.028), while visuospatial skills correlated with LIs of visual search (r = -0.621, P = 0.018). To summarize, cognitive development is accompanied by changes in the functional representation of neuronal circuitries, with a strengthening of lateralization not only for LH but also for RH functions. Our data show that age and performance, independently, account for the increases of laterality with age.

Stochastic rank correlation: a robust merit function for 2D/3D registration of image data obtained at different energies

In this article, the authors evaluate a merit function for 2D/3D registration called stochastic rank correlation (SRC). SRC is characterized by the fact that differences in image intensity do not influence the registration result; it therefore combines the numerical advantages of cross correlation (CC)-type merit functions with the flexibility of mutual-information-type merit functions. The basic idea is that registration is achieved on a random subset of the image, which allows for an efficient computation of Spearman's rank correlation coefficient. This measure is, by nature, invariant to monotonic intensity transforms in the images under comparison, which renders it an ideal solution for intramodal images acquired at different energy levels as encountered in intrafractional kV imaging in image-guided radiotherapy. Initial evaluation was undertaken using a 2D/3D registration reference image dataset of a cadaver spine. Even with no radiometric calibration, SRC shows a significant improvement in robustness and stability compared to CC. Pattern intensity, another merit function that was evaluated for comparison, gave rather poor results due to its limited convergence range. The time required for SRC with 5% image content compares well to the other merit functions; increasing the image content does not significantly influence the algorithm accuracy. The authors conclude that SRC is a promising measure for 2D/3D registration in IGRT and image-guided therapy in general.

Measurements of spin correlation in top-antitop quark events from proton-proton collisions at √s=7 TeV using the ATLAS detector

Measurements of spin correlation in top quark pair production are presented using data collected with the ATLAS detector at the LHC with proton-proton collisions at a center-of-mass energy of 7 TeV, corresponding to an integrated luminosity of 4.6  fb −1 . Events are selected in final states with two charged leptons and at least two jets and in final states with one charged lepton and at least four jets. Four different observables sensitive to different properties of the top quark pair production mechanism are used to extract the correlation between the top and antitop quark spins. Some of these observables are measured for the first time. The measurements are in good agreement with the Standard Model prediction at next-to-leading-order accuracy.

Stereoselective virtual screening of the ZINC database using atom pair 3D-fingerprints

Background Tools to explore large compound databases in search for analogs of query molecules provide a strategically important support in drug discovery to help identify available analogs of any given reference or hit compound by ligand based virtual screening (LBVS). We recently showed that large databases can be formatted for very fast searching with various 2D-fingerprints using the city-block distance as similarity measure, in particular a 2D-atom pair fingerprint (APfp) and the related category extended atom pair fingerprint (Xfp) which efficiently encode molecular shape and pharmacophores, but do not perceive stereochemistry. Here we investigated related 3D-atom pair fingerprints to enable rapid stereoselective searches in the ZINC database (23.2 million 3D structures). Results Molecular fingerprints counting atom pairs at increasing through-space distance intervals were designed using either all atoms (16-bit 3DAPfp) or different atom categories (80-bit 3DXfp). These 3D-fingerprints retrieved molecular shape and pharmacophore analogs (defined by OpenEye ROCS scoring functions) of 110,000 compounds from the Cambridge Structural Database with equal or better accuracy than the 2D-fingerprints APfp and Xfp, and showed comparable performance in recovering actives from decoys in the DUD database. LBVS by 3DXfp or 3DAPfp similarity was stereoselective and gave very different analogs when starting from different diastereomers of the same chiral drug. Results were also different from LBVS with the parent 2D-fingerprints Xfp or APfp. 3D- and 2D-fingerprints also gave very different results in LBVS of folded molecules where through-space distances between atom pairs are much shorter than topological distances. Conclusions 3DAPfp and 3DXfp are suitable for stereoselective searches for shape and pharmacophore analogs of query molecules in large databases. Web-browsers for searching ZINC by 3DAPfp and 3DXfp similarity are accessible at www.gdb.unibe.ch webcite and should provide useful assistance to drug discovery projects.

Repression of {\it neu} oncogene by E1A: Mechanisms and biological functions

The potential effects of the E1A gene products on the promoter activities of neu were investigated. Transcription of the neu oncogene was found to be strongly repressed by the E1A gene products and this requires that conserved region 2 of the E1A proteins. The target for E1A repression was localized within a 140 base pair (bp) DNA fragment in the upstream region of the neu promoter. To further study if this transcriptional repression of neu by E1A can inhibit the transforming ability of the neu transformed cells, the E1A gene was introduced into the neu oncogene transformed B104-1-1 cells and developed B-E1A cell lines that express E1A proteins. These B-E1A stable transfectants have reduced transforming activity compared to the parental B104-1-1 cell line and we conclude that E1A can suppress the transformed phenotypes of the neu oncogene transformed cells via transcriptional repression of neu.^ To study the effects of E1A on metastasis, we first introduced the mutation-activated rat neu oncogene into 3T3 cells and showed that both the neu oncogene transformed NIH3T3 cells and Swiss Webster 3T3 cells exhibited metastatic properties in vitro and in vivo, while their parental 3T3 cells did not. Additionally, the neu-specific monoclonal antibody 7.16.4, which can down regulate neu-encoded p185 protein, effectively reduced the metastatic properties induced by neu. To investigate if E1A can reduce the metastatic potential of neu-transformed cells, we also compared the metastatic properties of B-E1A cell lines and B104-1-1 cell. B-E1A cell lines showed reduced invasiveness and lung colonization than the parental neu transformed B104-1-1 cells. We conclude that E1A gene products also have inhibitory effect on the metastatic phenotypes of the neu oncogene transformed cells.^ The product of human retinoblastoma (RB) susceptibility gene has been shown to complex with E1A gene products and is speculated to regulate gene expression. We therefore investigated in E1A-RB interaction might be involved in the regulation of neu oncogene expression. We found that the RB gene product can decrease the E1A-mediated repression of neu oncogene and the E1A binding region of the RB protein is required for the derepression function. ^

Characterization of cellular and molecular functions of the p21 -activated kinase, Shk1, in the fission yeast, Schizosaccharomyces pombe

The p21-activated kinase, Shk1, is an essential serine/threonine kinase required for normal cell polarity, proper mating response, and hyperosmotic stress response, in the fission yeast, Schizosaccharomyces pombe. This study has established a novel role for Shk1 as a microtubule regulator in fission yeast and, in addition, characterized a potential biological substrate of Shk1. Cells defective in Shk1 function were found to exhibit malformed interphase and mitotic microtubules, are hypersensitive to the microtubule disrupting drug thiabendazole (TBZ), and are cold sensitive for growth. Microtubule disruption by TBZ results in a significant reduction of Shk1 kinase activity, which is restored after cells are released from the drug, thus providing a correlation between Shk1 kinase activity and active microtubule polymerization. Consistent with a role for Shk1 as a microtubule regulator, GFP-Shk1 fusion proteins localize to interphase microtubules and mitotic microtubule spindles. Furthermore, loss of Tea1, a presumptive microtubule regulator in fission yeast, exacerbates the growth and microtubule defects of cells deficient in Shk1 function, and results in illicit Shk1 localization. Moreover, loss of the Cdc2 inhibitory kinase Wee1, which has been implicated as a mediator of the Shk1 pathway, leads to significant microtubule defects. Intriguingly, Wee1 protein levels are markedly reduced both by partial loss of Shk1 function and by treatment with TBZ. These results suggest that Shk1 is required for proper regulation of microtubule dynamics in fission yeast and may interact with Tea1 and Wee1 in this regulatory process. ^ To further understand Shk1 function in fission yeast, a yeast two-hybrid screen for proteins that interact with the Shk1 catalytic domain was performed. This screen led to the identification of a novel protein, Skb10 (for S&barbelow;hk1 k&barbelow;inase b&barbelow;inding protein 10). Coprecipitation experiments demonstrated that Skb10 associates with Shk1 in S. pombe cells. (Abstract shortened by UMI.) ^

NMR scalar couplings across Watson–Crick base pair hydrogen bonds in DNA observed by transverse relaxation-optimized spectroscopy

This paper describes the NMR observation of 15N—15N and 1H—15N scalar couplings across the hydrogen bonds in Watson–Crick base pairs in a DNA duplex, hJNN and hJHN. These couplings represent new parameters of interest for both structural studies of DNA and theoretical investigations into the nature of the hydrogen bonds. Two dimensional [15N,1H]-transverse relaxation-optimized spectroscopy (TROSY) with a 15N-labeled 14-mer DNA duplex was used to measure hJNN, which is in the range 6–7 Hz, and the two-dimensional hJNN-correlation-[15N,1H]-TROSY experiment was used to correlate the chemical shifts of pairs of hydrogen bond-related 15N spins and to observe, for the first time, hJHN scalar couplings, with values in the range 2–3.6 Hz. TROSY-based studies of scalar couplings across hydrogen bonds should be applicable for large molecular sizes, including protein-bound nucleic acids.

Detection of protein fold similarity based on correlation of amino acid properties

An increasing number of proteins with weak sequence similarity have been found to assume similar three-dimensional fold and often have similar or related biochemical or biophysical functions. We propose a method for detecting the fold similarity between two proteins with low sequence similarity based on their amino acid properties alone. The method, the proximity correlation matrix (PCM) method, is built on the observation that the physical properties of neighboring amino acid residues in sequence at structurally equivalent positions of two proteins of similar fold are often correlated even when amino acid sequences are different. The hydrophobicity is shown to be the most strongly correlated property for all protein fold classes. The PCM method was tested on 420 proteins belonging to 64 different known folds, each having at least three proteins with little sequence similarity. The method was able to detect fold similarities for 40% of the 420 sequences. Compared with sequence comparison and several fold-recognition methods, the method demonstrates good performance in detecting fold similarities among the proteins with low sequence identity. Applied to the complete genome of Methanococcus jannaschii, the method recognized the folds for 22 hypothetical proteins.

Histone H1 overexpressed to high level in tobacco affects certain developmental programs but has limited effect on basal cellular functions.

Histone H1, a major structural component of chromatin fiber, is believed to act as a general repressor of transcription. To investigate in vivo the role of this protein in transcription regulation during development of a multicellular organism, we made transgenic tobacco plants that overexpress the gene for Arabidopsis histone H1. In all plants that overexpressed H1 the total H1-to-DNA ratio in chromatin increased 2.3-2.8 times compared with the physiological level. This was accompanied by 50-100% decrease of native tobacco H1. The phenotypic changes in H1-overexpressing plants ranged from mild to severe perturbations in morphological appearance and flowering. No correlation was observed between the extent of phenotypic change and the variation in the amount of overexpressed H1 or the presence or absence of the native tobacco H1. However, the severe phenotypic changes were correlated with early occurrence during plant growth of cells with abnormally heterochromatinized nuclei. Such cells occurred considerably later in plants with milder changes. Surprisingly, the ability of cells with highly heterochromatinized nuclei to fulfill basic physiological functions, including differentiation, was not markedly hampered. The results support the suggestion that chromatin structural changes dependent on H1 stoichiometry and on the profile of major H1 variants have limited regulatory effect on the activity of genes that control basal cellular functions. However, the H1-mediated chromatin changes can be of much greater importance for the regulation of genes involved in control of specific developmental programs.

How optimization of potential functions affects protein folding.

The relationship between the optimization of the potential function and the foldability of theoretical protein models is studied based on investigations of a 27-mer cubic-lattice protein model and a more realistic lattice model for the protein crambin. In both the simple and the more complicated systems, optimization of the energy parameters achieves significant improvements in the statistical-mechanical characteristics of the systems and leads to foldable protein models in simulation experiments. The foldability of the protein models is characterized by their statistical-mechanical properties--e.g., by the density of states and by Monte Carlo folding simulations of the models. With optimized energy parameters, a high level of consistency exists among different interactions in the native structures of the protein models, as revealed by a correlation function between the optimized energy parameters and the native structure of the model proteins. The results of this work are relevant to the design of a general potential function for folding proteins by theoretical simulations.

Cyclobutadiene automerization and rotation of ethylene: Energetics of the barriers by using Spin-polarized wave functions

Spin-projected spin polarized Møller–Plesset and spin polarized coupled clusters calculations have been made to estimate the cyclobutadiene automerization, the ethylene torsion barriers in their ground state, and the gap between the singlet and triplet states of ethylene. The results have been obtained optimizing the geometries at MP4 and/or CCSD levels, by an extensive Gaussian basis set. A comparative analysis with more complex calculations, up to MP5 and CCSDTQP, together with others from the literature, have also been made, showing the efficacy of using spin-polarized wave functions as a reference wave function for Møller–Plesset and coupled clusters calculations, in such problems.

Chemical diversity and potential biological functions of the pygidial gland secretions in two species of Neotropical dung roller beetles

Dung roller beetles of the genus Canthon (Coleoptera: Scarabaeinae) emit an odorous secretion from a pair of pygidial glands. To investigate the chemical composition of these secretions, we used stir bar sorptive extraction (SBSE), coupled with gas chromatography–mass spectrometry (GC–MS) for analysis of extracts of pygidial gland secretions secreted by the dung roller beetles Canthon femoralis femoralis and Canthon cyanellus cyanellus. Chemical analyses of volatiles collected from pygidial gland secretions comprise a great diversity of the functional groups. Chemical profile comparisons showed high intra- and interspecific variability. The pygidial gland secretion of Canthon f. femoralis was dominated by sesquiterpene hydrocarbons, whereas the profile of Canthon c. cyanellus was dominated by carboxylic acids. The different pygidial secretions have a high diversity of chemical compounds suggesting a multifunctional nature involving some key functions in the biology. We discuss the biological potential of these compounds found in the pygidial glands of each species with respect to their ecological and behavioral relevance.

Protein contact prediction using patterns of correlation

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two windows of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. (C) 2004 Wiley-Liss, Inc.

Identification of nonlinear systems by correlation using pseudorandom signals

This thesis is concerned with the measurement of the characteristics of nonlinear systems by crosscorrelation, using pseudorandom input signals based on m sequences. The systems are characterised by Volterra series, and analytical expressions relating the rth order Volterra kernel to r-dimensional crosscorrelation measurements are derived. It is shown that the two-dimensional crosscorrelation measurements are related to the corresponding second order kernel values by a set of equations which may be structured into a number of independent subsets. The m sequence properties determine how the maximum order of the subsets for off-diagonal values is related to the upper bound of the arguments for nonzero kernel values. The upper bound of the arguments is used as a performance index, and the performance of antisymmetric pseudorandom binary, ternary and quinary signals is investigated. The performance indices obtained above are small in relation to the periods of the corresponding signals. To achieve higher performance with ternary signals, a method is proposed for combining the estimates of the second order kernel values so that the effects of some of the undesirable nonzero values in the fourth order autocorrelation function of the input signal are removed. The identification of the dynamics of two-input, single-output systems with multiplicative nonlinearity is investigated. It is shown that the characteristics of such a system may be determined by crosscorrelation experiments using phase-shifted versions of a common signal as inputs. The effects of nonlinearities on the estimates of system weighting functions obtained by crosscorrelation are also investigated. Results obtained by correlation testing of an industrial process are presented, and the differences between theoretical and experimental results discussed for this case;

Fast algorithms for automatic mapping with space-limited covariance functions

In this paper we discuss a fast Bayesian extension to kriging algorithms which has been used successfully for fast, automatic mapping in emergency conditions in the Spatial Interpolation Comparison 2004 (SIC2004) exercise. The application of kriging to automatic mapping raises several issues such as robustness, scalability, speed and parameter estimation. Various ad-hoc solutions have been proposed and used extensively but they lack a sound theoretical basis. In this paper we show how observations can be projected onto a representative subset of the data, without losing significant information. This allows the complexity of the algorithm to grow as O(n m 2), where n is the total number of observations and m is the size of the subset of the observations retained for prediction. The main contribution of this paper is to further extend this projective method through the application of space-limited covariance functions, which can be used as an alternative to the commonly used covariance models. In many real world applications the correlation between observations essentially vanishes beyond a certain separation distance. Thus it makes sense to use a covariance model that encompasses this belief since this leads to sparse covariance matrices for which optimised sparse matrix techniques can be used. In the presence of extreme values we show that space-limited covariance functions offer an additional benefit, they maintain the smoothness locally but at the same time lead to a more robust, and compact, global model. We show the performance of this technique coupled with the sparse extension to the kriging algorithm on synthetic data and outline a number of computational benefits such an approach brings. To test the relevance to automatic mapping we apply the method to the data used in a recent comparison of interpolation techniques (SIC2004) to map the levels of background ambient gamma radiation. © Springer-Verlag 2007.