the transformational potential of health promotion

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Self-organized Vortex State in Two-dimensional Dictyostelium Dynamics

We present results of experiments on the dynamics of Dictyostelium discoideum in a novel set-up which constraints cell motion to a plane. After aggregation, the amoebae collect into round ''pancake" structures in which the cells rotate around the center of the pancake. This vortex state persists for many hours and we have explicitly verified that the motion is not due to rotating waves of cAMP. To provide an alternative mechanism for the self-organization of the Dictyostelium cells, we have developed a new model of the dynamics of self-propelled deformable objects. In this model, we show that cohesive energy between the cells, together with a coupling between the self-generated propulsive force and the cell's configuration produces a self-organized vortex state. The angular velocity profiles of the experiment and of the model are qualitatively similar. The mechanism for self-organization reported here can possibly explain similar vortex states in other biological systems.Comment: submitted to PRL; revised version dated 3/8/9

De-Novo Discovery of Differentially Abundant Transcription Factor Binding Sites Including Their Positional Preference

Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom

Gis1 and Rph1 Regulate Glycerol and Acetate Metabolism in Glucose Depleted Yeast Cells

Aging in organisms as diverse as yeast, nematodes, and mammals is delayed by caloric restriction, an effect mediated by the nutrient sensing TOR, RAS/cAMP, and AKT/Sch9 pathways. The transcription factor Gis1 functions downstream of these pathways in extending the lifespan of nutrient restricted yeast cells, but the mechanisms involved are still poorly understood. We have used gene expression microarrays to study the targets of Gis1 and the related protein Rph1 in different growth phases. Our results show that Gis1 and Rph1 act both as repressors and activators, on overlapping sets of genes as well as on distinct targets. Interestingly, both the activities and the target specificities of Gis1 and Rph1 depend on the growth phase. Thus, both proteins are associated with repression during exponential growth, targeting genes with STRE or PDS motifs in their promoters. After the diauxic shift, both become involved in activation, with Gis1 acting primarily on genes with PDS motifs, and Rph1 on genes with STRE motifs. Significantly, Gis1 and Rph1 control a number of genes involved in acetate and glycerol formation, metabolites that have been implicated in aging. Furthermore, several genes involved in acetyl-CoA metabolism are downregulated by Gis1

Iets over het landbezit van den inlander in Nederlandsch Indie

"Proefschrift."Thesis--Rijks-Universiteit Leiden.Mode of access: Internet

Health Behavior Interventions Among People With Lower Socio-Economic Status: A Scoping Review of Behavior Change Techniques and Effectiveness

Background. Behavior change interventions can unintendedly widen existing socio-economic disparities in health. Understanding why interventions are (in)effective among people with lower socio-economic status (SES) is essential. Therefore, this scoping review aims to describe what is reported about the behavior change techniques (BCTs) applied within interventions and their effectiveness in reducing physical inactivity, unhealthy eating, smoking and alcohol consumption according to SES. Methods. A systematic search was conducted in 12 electronic databases, and 151 studies meeting the eligibility criteria were included and coded for health behavioral outcomes, SES-operationalization, BCTs (type and number) and effectiveness. Results. Findings suggest that approaches for measuring, defining and substantiating lower SES vary. Current studies of behavior change interventions for people of different SES do not systematically identify specific BCTs, making systematic evaluation of BCT effectiveness impossible. The effectiveness of interventions is mainly evaluated by overall intervention outcomes and SES-moderation effects are mostly not assessed. Conclusion. Using different SES-operationalizations and not specifying BCTs hampers systematic evidence accumulation regarding effective (combinations of) BCTs for the low SES population. To learn which BCTs effectively improve health behaviors among people with lower SES, future intervention developers should justify how SES is operationalized and must systematically describe and examine BCTs

A multi-scale analysis of the effect of complex viscoelastic models on Listeria dynamics and adaptation in co-culture systems

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