Prevalence of chronic fatigue syndrome in metropolitan, urban, and rural Georgia

© 2007 Reeves et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Bayesian calibration, validation and uncertainty quantification for predictive modelling of tumour growth: a tutorial

In this work we present a pedagogical tumour growth example, in which we apply calibration and validation techniques to an uncertain, Gompertzian model of tumour spheroid growth. The key contribution of this article is the discussion and application of these methods (that are not commonly employed in the field of cancer modelling) in the context of a simple model, whose deterministic analogue is widely known within the community. In the course of the example we calibrate the model against experimental data that is subject to measurement errors, and then validate the resulting uncertain model predictions. We then analyse the sensitivity of the model predictions to the underlying measurement model. Finally, we propose an elementary learning approach for tuning a threshold parameter in the validation procedure in order to maximize predictive accuracy of our validated model

Integrative inference of gene-regulatory networks in Escherichia coli using information theoretic concepts and sequence analysis

<p>Abstract</p> <p>Background</p> <p>Although <it>Escherichia coli </it>is one of the best studied model organisms, a comprehensive understanding of its gene regulation is not yet achieved. There exist many approaches to reconstruct regulatory interaction networks from gene expression experiments. Mutual information based approaches are most useful for large-scale network inference.</p> <p>Results</p> <p>We used a three-step approach in which we combined gene regulatory network inference based on directed information (DTI) and sequence analysis. DTI values were calculated on a set of gene expression profiles from 19 time course experiments extracted from the Many Microbes Microarray Database. Focusing on influences between pairs of genes in which one partner encodes a transcription factor (TF) we derived a network which contains 878 TF - gene interactions of which 166 are known according to RegulonDB. Afterward, we selected a subset of 109 interactions that could be confirmed by the presence of a phylogenetically conserved binding site of the respective regulator. By this second step, the fraction of known interactions increased from 19% to 60%. In the last step, we checked the 44 of the 109 interactions not yet included in RegulonDB for functional relationships between the regulator and the target and, thus, obtained ten TF - target gene interactions. Five of them concern the regulator LexA and have already been reported in the literature. The remaining five influences describe regulations by Fis (with two novel targets), PhdR, PhoP, and KdgR. For the validation of our approach, one of them, the regulation of lipoate synthase (LipA) by the pyruvate-sensing pyruvate dehydrogenate repressor (PdhR), was experimentally checked and confirmed.</p> <p>Conclusions</p> <p>We predicted a set of five novel TF - target gene interactions in <it>E. coli</it>. One of them, the regulation of <it>lipA </it>by the transcriptional regulator PdhR was validated experimentally. Furthermore, we developed DTInfer, a new R-package for the inference of gene-regulatory networks from microarrays using directed information.</p

Infection of Cultured Human Endothelial Cells by Legionella pneumophila

Legionella pneumophila is a gram-negative pathogen that causes a severe pneumonia known as Legionnaires' disease. Here, we demonstrate for the first time that L. pneumophila infects and grows within cultured human endothelial cells. Endothelial infection may contribute to lung damage observed during Legionnaires' disease and to systemic spread of this organism

Latent Factor Analysis to Discover Pathway-Associated Putative Segmental Aneuploidies in Human Cancers

Tumor microenvironmental stresses, such as hypoxia and lactic acidosis, play important roles in tumor progression. Although gene signatures reflecting the influence of these stresses are powerful approaches to link expression with phenotypes, they do not fully reflect the complexity of human cancers. Here, we describe the use of latent factor models to further dissect the stress gene signatures in a breast cancer expression dataset. The genes in these latent factors are coordinately expressed in tumors and depict distinct, interacting components of the biological processes. The genes in several latent factors are highly enriched in chromosomal locations. When these factors are analyzed in independent datasets with gene expression and array CGH data, the expression values of these factors are highly correlated with copy number alterations (CNAs) of the corresponding BAC clones in both the cell lines and tumors. Therefore, variation in the expression of these pathway-associated factors is at least partially caused by variation in gene dosage and CNAs among breast cancers. We have also found the expression of two latent factors without any chromosomal enrichment is highly associated with 12q CNA, likely an instance of “trans”-variations in which CNA leads to the variations in gene expression outside of the CNA region. In addition, we have found that factor 26 (1q CNA) is negatively correlated with HIF-1α protein and hypoxia pathways in breast tumors and cell lines. This agrees with, and for the first time links, known good prognosis associated with both a low hypoxia signature and the presence of CNA in this region. Taken together, these results suggest the possibility that tumor segmental aneuploidy makes significant contributions to variation in the lactic acidosis/hypoxia gene signatures in human cancers and demonstrate that latent factor analysis is a powerful means to uncover such a linkage

Was Wright Right? The Canonical Genetic Code is an Empirical Example of an Adaptive Peak in Nature; Deviant Genetic Codes Evolved Using Adaptive Bridges

The canonical genetic code is on a sub-optimal adaptive peak with respect to its ability to minimize errors, and is close to, but not quite, optimal. This is demonstrated by the near-total adjacency of synonymous codons, the similarity of adjacent codons, and comparisons of frequency of amino acid usage with number of codons in the code for each amino acid. As a rare empirical example of an adaptive peak in nature, it shows adaptive peaks are real, not merely theoretical. The evolution of deviant genetic codes illustrates how populations move from a lower to a higher adaptive peak. This is done by the use of “adaptive bridges,” neutral pathways that cross over maladaptive valleys by virtue of masking of the phenotypic expression of some maladaptive aspects in the genotype. This appears to be the general mechanism by which populations travel from one adaptive peak to another. There are multiple routes a population can follow to cross from one adaptive peak to another. These routes vary in the probability that they will be used, and this probability is determined by the number and nature of the mutations that happen along each of the routes. A modification of the depiction of adaptive landscapes showing genetic distances and probabilities of travel along their multiple possible routes would throw light on this important concept

Affine differential geometry analysis of human arm movements

Humans interact with their environment through sensory information and motor actions. These interactions may be understood via the underlying geometry of both perception and action. While the motor space is typically considered by default to be Euclidean, persistent behavioral observations point to a different underlying geometric structure. These observed regularities include the “two-thirds power law” which connects path curvature with velocity, and “local isochrony” which prescribes the relation between movement time and its extent. Starting with these empirical observations, we have developed a mathematical framework based on differential geometry, Lie group theory and Cartan’s moving frame method for the analysis of human hand trajectories. We also use this method to identify possible motion primitives, i.e., elementary building blocks from which more complicated movements are constructed. We show that a natural geometric description of continuous repetitive hand trajectories is not Euclidean but equi-affine. Specifically, equi-affine velocity is piecewise constant along movement segments, and movement execution time for a given segment is proportional to its equi-affine arc-length. Using this mathematical framework, we then analyze experimentally recorded drawing movements. To examine movement segmentation and classification, the two fundamental equi-affine differential invariants—equi-affine arc-length and curvature are calculated for the recorded movements. We also discuss the possible role of conic sections, i.e., curves with constant equi-affine curvature, as motor primitives and focus in more detail on parabolas, the equi-affine geodesics. Finally, we explore possible schemes for the internal neural coding of motor commands by showing that the equi-affine framework is compatible with the common model of population coding of the hand velocity vector when combined with a simple assumption on its dynamics. We then discuss several alternative explanations for the role that the equi-affine metric may play in internal representations of motion perception and production

Supernovae from massive stars

Massive stars, by which we mean those stars exploding as core collapse supernovae, play a pivotal role in the evolution of the Universe. Therefore, the understanding of their evolution and explosion is fundamental in many branches of physics and astrophysics, among which, galaxy evolution, nucleosynthesis, supernovae, neutron stars and pulsars, black holes, neutrinos and gravitational waves. In this chapter, the author presents an overview of the presupernova evolution of stars in the range between 13 and 120 $\rm M_\odot$, with initial metallicities between [Fe/H]=-3 and [Fe/H]=0 and initial rotation velocities $\rm v=0,~150,~300~km/s$. Emphasis is placed upon those evolutionary properties that determine the final fate of the star with special attention to the interplay among mass loss, mixing and rotation. A general picture of the evolution and outcome of a generation of massive stars, as a function of the initial mass, metallicity and rotation velocity, is finally outlined.Comment: Author version of a chapter for 'Handbook of Supernovae,' edited by A. Alsabti and P. Murdin, Springer. 59 pages, 27 figure

Beyond the ‘Migrant Network’? Exploring assistance received in the migration of brazilians to Portugal and the Netherlands

This paper explores the tenability of three important critiques to the ‘migrant network’ approach in migration studies: (1) the narrow focus on kin and community members, which connect prospective migrants in origin countries with immigrants in the destination areas, failing to take due account of sources of assistance beyond the ‘migrant network’ like institutional or online sources; (2) that it is misleading to assume a general pattern in the role of migrant networks in migration, regardless of contexts of arrival or departure, including the scale and history of migration or the immigration regime; and (3) that ‘migrant networks’ are not equally relevant to all migrants, and that important differences may exist between labour migrants and other types of migrants like family migrants or students. Drawing on survey data on the migration of Brazilians to Portugal and the Netherlands we find support for these critiques but also reaffirm the relevance of ‘migrant networks’.info:eu-repo/semantics/publishedVersio

Goal setting and self-efficacy among delinquent, at-risk and not at-risk adolescents

Setting clear achievable goals that enhance self-efficacy and reputational status directs the energies of adolescents into socially conforming or non-conforming activities. This present study investigates the characteristics and relationships between goal setting and self-efficacy among a matched sample of 88 delinquent (18 % female), 97 at-risk (20 % female), and 95 not at-risk adolescents (20 % female). Four hypotheses related to this were tested. Findings revealed that delinquent adolescents reported fewest goals, set fewer challenging goals, had a lower commitment to their goals, and reported lower levels of academic and self-regulatory efficacy than those in the at-risk and not at-risk groups. Discriminant function analysis indicated that adolescents who reported high delinquency goals and low educational and interpersonal goals were likely to belong to the delinquent group, while adolescents who reported high educational and interpersonal goals and low delinquency goals were likely to belong to the not at-risk group. The at-risk and not at-risk groups could not be differentiated. A multinomial logistic regression also revealed that adolescents were more likely to belong to the delinquent group if they reported lower self-regulatory efficacy and lower goal commitment. These findings have important implications for the development of prevention and intervention programs, particularly for those on a trajectory to delinquency. Specifically, programs should focus on assisting adolescents to develop clear self-set achievable goals and support them through the process of attaining them, particularly if the trajectory towards delinquency is to be addressed