EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Effect of training-sample size and classification difficulty on the accuracy of genomic predictors.

Introduction: As part of the MicroArray Quality Control (MAQC)-II project, this analysis examines how the choice of univariate feature-selection methods and classification algorithms may influence the performance of genomic predictors under varying degrees of prediction difficulty represented by three clinically relevant endpoints. Methods: We used gene-expression data from 230 breast cancers (grouped into training and independent validation sets), and we examined 40 predictors (five univariate feature-selection methods combined with eight different classifiers) for each of the three endpoints. Their classification performance was estimated on the training set by using two different resampling methods and compared with the accuracy observed in the independent validation set. Results: A ranking of the three classification problems was obtained, and the performance of 120 models was estimated and assessed on an independent validation set. The bootstrapping estimates were closer to the validation performance than were the cross-validation estimates. The required sample size for each endpoint was estimated, and both gene-level and pathway-level analyses were performed on the obtained models. Conclusions: We showed that genomic predictor accuracy is determined largely by an interplay between sample size and classification difficulty. Variations on univariate feature-selection methods and choice of classification algorithm have only a modest impact on predictor performance, and several statistically equally good predictors can be developed for any given classification problem.

On a size-structured two-phase population model with infinite states-at-birth

In this work we introduce and analyze a linear size-structured population model with infinite states-at-birth. We model the dynamics of a population in which individuals have two distinct life-stages: an “active” phase when individuals grow, reproduce and die and a second “resting” phase when individuals only grow. Transition between these two phases depends on individuals’ size. First we show that the problem is governed by a positive quasicontractive semigroup on the biologically relevant state space. Then we investigate, in the framework of the spectral theory of linear operators, the asymptotic behavior of solutions of the model. We prove that the associated semigroup has, under biologically plausible assumptions, the property of asynchronous exponential growth.

Male dominance linked to size and age, but not to 'good genes' in brown trout (Salmo trutta).

BACKGROUND: Males that are successful in intra-sexual competition are often assumed to be of superior quality. In the mating system of most salmonid species, intensive dominance fights are common and the winners monopolise most mates and sire most offspring. We drew a random sample of mature male brown trout (Salmo trutta) from two wild populations and determined their dominance hierarchy or traits linked to dominance. The fish were then stripped and their sperm was used for in vitro fertilisations in two full-factorial breeding designs. We recorded embryo viability until hatching in both experiments, and juvenile survival during 20 months after release into a natural streamlet in the second experiment. Since offspring of brown trout get only genes from their fathers, we used offspring survival as a quality measure to test (i) whether males differ in their genetic quality, and if so, (ii) whether dominance or traits linked to dominance reveal 'good genes'. RESULTS: We found significant additive genetic variance on embryo survival, i.e. males differed in their genetic quality. Older, heavier and larger males were more successful in intra-sexual selection. However, neither dominance nor dominance indicators like body length, weight or age were significantly linked to genetic quality measured as embryo or juvenile survival. CONCLUSION: We found no evidence that females can improve their offspring's genetic viability by mating with large and dominant males. If there still were advantages of mating with dominant males, they may be linked to non-genetic benefits or to genetic advantages that are context dependent and therefore possibly not revealed under our experimental conditions - even if we found significant additive genetic variation for embryo viability under such conditions.

Semigroup analysis of structured populations with distributed states-at-birth arising in mathematical aquaculture

Motivated by the modelling of structured parasite populations in aquaculture we consider a class of physiologically structured population models, where individuals may be recruited into the population at different sizes in general. That is, we consider a size-structured population model with distributed states-at-birth. The mathematical model which describes the evolution of such a population is a first order nonlinear partial integro-differential equation of hyperbolic type. First, we use positive perturbation arguments and utilise results from the spectral theory of semigroups to establish conditions for the existence of a positive equilibrium solution of our model. Then we formulate conditions that guarantee that the linearised system is governed by a positive quasicontraction semigroup on the biologically relevant state space. We also show that the governing linear semigroup is eventually compact, hence growth properties of the semigroup are determined by the spectrum of its generator. In case of a separable fertility function we deduce a characteristic equation and investigate the stability of equilibrium solutions in the general case using positive perturbation arguments.

Revisiting the specificity of the MHC class II transactivator CIITA in vivo.

CIITA is a master regulatory factor for the expression of MHC class II (MHC-II) and accessory genes involved in Ag presentation. It has recently been suggested that CIITA also regulates numerous other genes having diverse functions within and outside the immune system. To determine whether these genes are indeed relevant targets of CIITA in vivo, we studied their expression in CIITA-transgenic and CIITA-deficient mice. In contrast to the decisive control of MHC-II and related genes by CIITA, nine putative non-MHC target genes (Eif3s2, Kpna6, Tap1, Yars, Col1a2, Ctse, Ptprr, Tnfsf6 and Plxna1) were found to be CIITA independent in all cell types examined. Two other target genes, encoding IL-4 and IFN-gamma, were indeed found to be up- and down-regulated, respectively, in CIITA-transgenic CD4(+) T cells. However, there was no correlation between MHC-II expression and this Th2 bias at the level of individual transgenic T cells, indicating an indirect control by CIITA. These results show that MHC-II-restricted Ag presentation, and its indirect influences on T cells, remains the only pathway under direct control by CIITA in vivo. They also imply that precisely regulated MHC-II expression is essential for maintaining a proper Th1-Th2 balance.

Selective abrogation of major histocompatibility complex class II expression on extrahematopoietic cells in mice lacking promoter IV of the class II transactivator gene.

MHC class II (MHCII) molecules play a pivotal role in the induction and regulation of immune responses. The transcriptional coactivator class II transactivator (CIITA) controls MHCII expression. The CIITA gene is regulated by three independent promoters (pI, pIII, pIV). We have generated pIV knockout mice. These mice exhibit selective abrogation of interferon (IFN)-gamma-induced MHCII expression on a wide variety of non-bone marrow-derived cells, including endothelia, epithelia, astrocytes, and fibroblasts. Constitutive MHCII expression on cortical thymic epithelial cells, and thus positive selection of CD4(+) T cells, is also abolished. In contrast, constitutive and inducible MHCII expression is unaffected on professional antigen-presenting cells, including B cells, dendritic cells, and IFN-gamma-activated cells of the macrophage lineage. pIV(-/-) mice have thus allowed precise definition of CIITA pIV usage in vivo. Moreover, they represent a unique animal model for studying the significance and contribution of MHCII-mediated antigen presentation by nonprofessional antigen-presenting cells in health and disease.

Stochastic demography and the neutral substitution rate in class-structured populations.

The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

Deletion, insertion and translocation of DNA sequences contribute to chromosome size polimorphism in Plasmodium berghei

Extensive chromosome size polymorphism in Plasmodium berghei in vivo mitotic multiplication. Size differences between homologous chromosomes mainly involve rearrangements in the subtelomeric regions while internal chromosomal regions are more conserved. Size differences are almost exclusively due to differences in the copy number of a 2.3 kb subtelomeric repeat unit. Not only deletion of 2.3 kb repeats occurs, but addition of new copies of this repeat sometimes results in the formation of enlarged chromosomes. Even chromosomes which originally lack 2.3 kb repeats, can acquire these during mitotic multiplication. In one karyotype mutant, 2.3 kb repeats were inserted within one of the original telomeres of chromosome 4, creating an internal stretch oftelomeric repeats. Chromosome translocation can contribute to chromosome size polymorphism as well We found a karyotype mutant in which chromosome 7 with a size of about 1.4 Mb is translocated to chromosome 13/14 with a size of about 3 Mb, resulting in a rearranged chromosome, which was shown to contain a junction between internal DNA sequences of chromosome 13/14 and subtelomeric 2.3 kb repeats of chromosome 7. In this mutant a new chromosome of 1.4 Mb is present which consists of part of chromosome 13/14.

Immunoglobulin classes in aquatic mammals. Characterization by serologic cross-reactivity, molecular size and binding of human free secretory component.

On the basis of serologic cross-reactivity, three immunoglobulin classes homologous to human IgG, IgM and IgA were identified in two species of acquatic mammal representing the orders Cetacea (dolphin) and Pinnipedea (sea lion). Molecular size was estimated by sucrose density gradient ultracentrifugation and Sephadex G-200 chromatography, indicating a 7S IgG, 19S IgM and heterogeneous serum IgA. Human secretory component was readily bound to the IgM of both species and to an apparently lesser extent to the larger molecular size populations of IgA. No binding was observed with IgG. Several antisera specific for human γ-chains gave a single precipitin line with the sea lion IgG but when made to react with dolphin serum produced two lines, suggesting the presence of two different subclasses of IgG in this species.

Mini-review: Specificity and expression of CIITA, the master regulator of MHC class II genes.

The class II transactivator (CIITA) has been referred to as the "master control factor" for the expression of MHC class II (MHCII) genes. As our knowledge on the specificity and function of CIITA grows, it is becoming increasingly evident that this sobriquet is entirely justified. First, despite extensive investigations, the major target genes of CIITA remain those implicated in the presentation of antigenic peptides by MHCII molecules. Although other putative target genes have been reported, the contribution of CIITA to their expression remains indirect, controversial or comparatively minor relative to its decisive role as a regulator of MHCII and related genes. Second, the most important parameter dictating MHCII expression is by far the expression pattern of the gene encoding CIITA (MHC2TA). The vast majority of signals that activate or repress MHCII expression under physiological and pathological situations converge on one or more of the three alternative promoters that drive transcription of the MHC2TA gene. In short, with respect to its specificity and its exquisitely controlled pattern of expression, CIITA is by a long stretch the single most important transcription factor for the regulation of genes required for MHCII-restricted antigen-presentation.