Neocortical maturation during adolescence: change in neuronal soma dimension.

During adolescence, cognitive abilities increase robustly. To search for possible related structural alterations of the cerebral cortex, we measured neuronal soma dimension (NSD = width times height), cortical thickness and neuronal densities in different types of neocortex in post-mortem brains of five 12-16 and five 17-24 year-olds (each 2F, 3M). Using a generalized mixed model analysis, mean normalized NSD comparing the age groups shows layer-specific change for layer 2 (p < .0001) and age-related differences between categorized type of cortex: primary/primary association cortex (BA 1, 3, 4, and 44) shows a generalized increase; higher-order regions (BA 9, 21, 39, and 45) also show increase in layers 2 and 5 but decrease in layers 3, 4, and 6 while limbic/orbital cortex (BA 23, 24, and 47) undergoes minor decrease (BA 1, 3, 4, and 44 vs. BA 9, 21, 39, and 45: p = .036 and BA 1, 3, 4, and 44 vs. BA 23, 24, and 47: p = .004). These data imply the operation of cortical layer- and type-specific processes of growth and regression adding new evidence that the human brain matures during adolescence not only functionally but also structurally.

The network origins of aggregate fluctuations

This paper argues that in the presence of intersectoral input-output linkages, microeconomicidiosyncratic shocks may lead to aggregate fluctuations. In particular, itshows that, as the economy becomes more disaggregated, the rate at which aggregatevolatility decays is determined by the structure of the network capturing such linkages.Our main results provide a characterization of this relationship in terms of the importanceof different sectors as suppliers to their immediate customers as well as theirrole as indirect suppliers to chains of downstream sectors. Such higher-order interconnectionscapture the possibility of "cascade effects" whereby productivity shocks to asector propagate not only to its immediate downstream customers, but also indirectlyto the rest of the economy. Our results highlight that sizable aggregate volatility isobtained from sectoral idiosyncratic shocks only if there exists significant asymmetryin the roles that sectors play as suppliers to others, and that the "sparseness" of theinput-output matrix is unrelated to the nature of aggregate fluctuations.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Solving heterogeneous-agent models by projection and perturbation

The paper proposes a numerical solution method for general equilibrium models with a continuum of heterogeneous agents, which combines elements of projection and of perturbation methods. The basic idea is to solve first for the stationary solutionof the model, without aggregate shocks but with fully specified idiosyncratic shocks. Afterwards one computes a first-order perturbation of the solution in the aggregate shocks. This approach allows to include a high-dimensional representation of the cross-sectional distribution in the state vector. The method is applied to a model of household saving with uninsurable income risk and liquidity constraints. The model includes not only productivity shocks, but also shocks to redistributive taxation, which cause substantial short-run variation in the cross-sectional distribution of wealth. If those shocks are operative, it is shown that a solution method based on very few statistics of the distribution is not suitable, while the proposed method can solve the model with high accuracy, at least for the case of small aggregate shocks. Techniques are discussed to reduce the dimension of the state space such that higher order perturbations are feasible.Matlab programs to solve the model can be downloaded.

Tax reforms and inequality: theoretical and empirical implications

In this paper we examine the effect of tax policy on the relationship between inequality and growth in a two-sector non-scale model. With non-scale models, the longrun equilibrium growth rate is determined by technological parameters and it is independent of macroeconomic policy instruments. However, this fact does not imply that fiscal policy is unimportant for long-run economic performance. It indeed has important effects on the different levels of key economic variables such as per capita stock of capital and output. Hence, although the economy grows at the same rate across steady states, the bases for economic growth may be different.The model has three essential features. First, we explicitly model skill accumulation, second, we introduce government finance into the production function, and we introduce an income tax to mirror the fiscal events of the 1980¿s and 1990¿s in the US. The fact that the non-scale model is associated with higher order dynamics enables it to replicate the distinctly non-linear nature of inequality in the US with relative ease. The results derived in this paper attract attention to the fact that the non-scale growth model does not only fit the US data well for the long-run (Jones, 1995b) but also that it possesses unique abilities in explaining short term fluctuations of the economy. It is shown that during transition the response of the relative simulated wage to changes in the tax code is rather non-monotonic, quite in accordance to the US inequality pattern in the 1980¿s and early 1990¿s.More specifically, we have analyzed in detail the dynamics following the simulation of an isolated tax decrease and an isolated tax increase. So, after a tax decrease the skill premium follows a lower trajectory than the one it would follow without a tax decrease. Hence we are able to reduce inequality for several periods after the fiscal shock. On the contrary, following a tax increase, the evolution of the skill premium remains above the trajectory carried on by the skill premium under a situation with no tax increase. Consequently, a tax increase would imply a higher level of inequality in the economy

TACI, unlike BAFF-R, is solely activated by oligomeric BAFF and APRIL to support survival of activated B cells and plasmablasts.

The cytokine BAFF binds to the receptors TACI, BCMA, and BAFF-R on B cells, whereas APRIL binds to TACI and BCMA only. The signaling properties of soluble trimeric BAFF (BAFF 3-mer) were compared with those of higher-order BAFF oligomers. All forms of BAFF bound BAFF-R and TACI, and elicited BAFF-R-dependent signals in primary B cells. In contrast, signaling through TACI in mature B cells or plasmablasts was only achieved by higher-order BAFF and APRIL oligomers, all of which were also po-tent activators of a multimerization-dependent reporter signaling pathway. These results indicate that, although BAFF-R and TACI can provide B cells with similar signals, only BAFF-R, but not TACI, can respond to soluble BAFF 3-mer, which is the main form of BAFF found in circulation. BAFF 60-mer, an efficient TACI agonist, was also detected in plasma of BAFF transgenic and nontransgenic mice and was more than 100-fold more active than BAFF 3-mer for the activation of multimerization-dependent signals. TACI supported survival of activated B cells and plasmablasts in vitro, providing a rational basis to explain the immunoglobulin deficiency reported in TACI-deficient persons.

Tax reforms and inequality: theoretical and empirical implications

In this paper we examine the effect of tax policy on the relationship between inequality and growth in a two-sector non-scale model. With non-scale models, the longrun equilibrium growth rate is determined by technological parameters and it is independent of macroeconomic policy instruments. However, this fact does not imply that fiscal policy is unimportant for long-run economic performance. It indeed has important effects on the different levels of key economic variables such as per capita stock of capital and output. Hence, although the economy grows at the same rate across steady states, the bases for economic growth may be different.The model has three essential features. First, we explicitly model skill accumulation, second, we introduce government finance into the production function, and we introduce an income tax to mirror the fiscal events of the 1980¿s and 1990¿s in the US. The fact that the non-scale model is associated with higher order dynamics enables it to replicate the distinctly non-linear nature of inequality in the US with relative ease. The results derived in this paper attract attention to the fact that the non-scale growth model does not only fit the US data well for the long-run (Jones, 1995b) but also that it possesses unique abilities in explaining short term fluctuations of the economy. It is shown that during transition the response of the relative simulated wage to changes in the tax code is rather non-monotonic, quite in accordance to the US inequality pattern in the 1980¿s and early 1990¿s.More specifically, we have analyzed in detail the dynamics following the simulation of an isolated tax decrease and an isolated tax increase. So, after a tax decrease the skill premium follows a lower trajectory than the one it would follow without a tax decrease. Hence we are able to reduce inequality for several periods after the fiscal shock. On the contrary, following a tax increase, the evolution of the skill premium remains above the trajectory carried on by the skill premium under a situation with no tax increase. Consequently, a tax increase would imply a higher level of inequality in the economy

Development of an Fn14 agonistic antibody as an anti-tumor agent.

TWEAK, a TNF family ligand with pleiotropic cellular functions, was originally described as capable of inducing tumor cell death in vitro. TWEAK functions by binding its receptor, Fn14, which is up-regulated on many human solid tumors. Herein, we show that intratumoral administration of TWEAK, delivered either by an adenoviral vector or in an immunoglobulin Fc-fusion form, results in significant inhibition of tumor growth in a breast xenograft model. To exploit the TWEAK-Fn14 pathway as a therapeutic target in oncology, we developed an anti-Fn14 agonistic antibody, BIIB036. Studies described herein show that BIIB036 binds specifically to Fn14 but not other members of the TNF receptor family, induces Fn14 signaling, and promotes tumor cell apoptosis in vitro. In vivo, BIIB036 effectively inhibits growth of tumors in multiple xenograft models, including colon (WiDr), breast (MDA-MB-231), and gastric (NCI-N87) tumors, regardless of tumor cell growth inhibition response observed to BIIB036 in vitro. The anti-tumor activity in these cell lines is not TNF-dependent. Increasing the antigen-binding valency of BIB036 significantly enhances its anti-tumor effect, suggesting the contribution of higher order cross-linking of the Fn14 receptor. Full Fc effector function is required for maximal activity of BIIB036 in vivo, likely due to the cross-linking effect and/or ADCC mediated tumor killing activity. Taken together, the anti-tumor properties of BIIB036 validate Fn14 as a promising target in oncology and demonstrate its potential therapeutic utility in multiple solid tumor indications.

Signatures of CP violation in the presence of multiple b-pair production at hadron colliders

We calculate the production of two b-quark pairs in hadron collisions. Sources of multiple pairs are multiple interactions and higher order perturbative QCD mechanisms. We subsequently investigate the competing effects of multiple b-pair production on measurements of CP violation: (i) the increase in event rate with multiple b-pair cross sections which may reach values of the order of 1 b in the presence of multiple interactions and (ii) the dilution of b versus b tagging efficiency because of the presence of events with four B mesons. The impact of multiple B-meson production is small unless the cross section for producing a single pair exceeds 1 mb. We show that even for larger values of the cross section the competing effects (i) and (ii) roughly compensate so that there is no loss in the precision with which CP-violating CKM angles can be determined.

MSSM Higgs boson decays to bottom quark pairs reexamined

We present an update of neutral Higgs boson decays into bottom quark pairs in the minimal supersymmetric extension of the standard model. In particular the resummation of potentially large higher-order corrections due to the soft supersymmetry (SUSY) breaking parameters Ab and is extended. The remaining theoretical uncertainties due to unknown higher-order SUSY-QCD corrections are analyzed quantitatively.

The ability model of emotional intelligence: Searching for valid measures

Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.

On the relationship between connections and the asymptotic properties of predictive distributions

In a recent paper, Komaki studied the second-order asymptotic properties of predictive distributions, using the Kullback-Leibler divergence as a loss function. He showed that estimative distributions with asymptotically efficient estimators can be improved by predictive distributions that do not belong to the model. The model is assumed to be a multidimensional curved exponential family. In this paper we generalize the result assuming as a loss function any f divergence. A relationship arises between alpha connections and optimal predictive distributions. In particular, using an alpha divergence to measure the goodness of a predictive distribution, the optimal shift of the estimate distribution is related to alpha-covariant derivatives. The expression that we obtain for the asymptotic risk is also useful to study the higher-order asymptotic properties of an estimator, in the mentioned class of loss functions.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

The novel proteins Rng8 and Rng9 regulate the myosin-V Myo51 during fission yeast cytokinesis.

The myosin-V family of molecular motors is known to be under sophisticated regulation, but our knowledge of the roles and regulation of myosin-Vs in cytokinesis is limited. Here, we report that the myosin-V Myo51 affects contractile ring assembly and stability during fission yeast cytokinesis, and is regulated by two novel coiled-coil proteins, Rng8 and Rng9. Both rng8Δ and rng9Δ cells display similar defects as myo51Δ in cytokinesis. Rng8 and Rng9 are required for Myo51's localizations to cytoplasmic puncta, actin cables, and the contractile ring. Myo51 puncta contain multiple Myo51 molecules and walk continuously on actin filaments in rng8(+) cells, whereas Myo51 forms speckles containing only one dimer and does not move efficiently on actin tracks in rng8Δ. Consistently, Myo51 transports artificial cargos efficiently in vivo, and this activity is regulated by Rng8. Purified Rng8 and Rng9 form stable higher-order complexes. Collectively, we propose that Rng8 and Rng9 form oligomers and cluster multiple Myo51 dimers to regulate Myo51 localization and functions.

Why should we care about soil fauna?

The reasons why we care about soil fauna are related to their intrinsic, utilitarian and functional values. The intrinsic values embrace aesthetic or moral reasons for conserving below-ground biodiversity. Unfortunately, the protection of soil invertebrates has rarely been a criterion for avoiding changes in land use and management. Utilitarian, or direct use values, have been investigated more extensively for fungi, bacteria and marine invertebrates than for soil fauna. However, some traditional remedies, novel enzymes and pharmaceutical compounds have been derived from earthworms, termites and other groups, and gut symbionts may provide microbial strains with interesting properties for biotechnology. The functional importance of soil invertebrates in ecosystem processes has been a major focus of research in recent decades. It is suggested herein that it is rarely possible to identify the role of soil invertebrates as rate determinants of soil processes at plot and ecosystem scales of hectares and above because other biophysical controls override their effects. There are situations, however, where the activities of functional groups of soil animals, even of species, are synchronised in space or time by plant events, resource inputs, seasonality or other perturbations to the system, and their emergent effects are detectable as higher order controls.