Genetic clusters and sex-biased gene flow in a unicolonial Formica ant.

BACKGROUND: Animal societies are diverse, ranging from small family-based groups to extraordinarily large social networks in which many unrelated individuals interact. At the extreme of this continuum, some ant species form unicolonial populations in which workers and queens can move among multiple interconnected nests without eliciting aggression. Although unicoloniality has been mostly studied in invasive ants, it also occurs in some native non-invasive species. Unicoloniality is commonly associated with very high queen number, which may result in levels of relatedness among nestmates being so low as to raise the question of the maintenance of altruism by kin selection in such systems. However, the actual relatedness among cooperating individuals critically depends on effective dispersal and the ensuing pattern of genetic structuring. In order to better understand the evolution of unicoloniality in native non-invasive ants, we investigated the fine-scale population genetic structure and gene flow in three unicolonial populations of the wood ant F. paralugubris. RESULTS: The analysis of geo-referenced microsatellite genotypes and mitochondrial haplotypes revealed the presence of cryptic clusters of genetically-differentiated nests in the three populations of F. paralugubris. Because of this spatial genetic heterogeneity, members of the same clusters were moderately but significantly related. The comparison of nuclear (microsatellite) and mitochondrial differentiation indicated that effective gene flow was male-biased in all populations. CONCLUSION: The three unicolonial populations exhibited male-biased and mostly local gene flow. The high number of queens per nest, exchanges among neighbouring nests and restricted long-distance gene flow resulted in large clusters of genetically similar nests. The positive relatedness among clustermates suggests that kin selection may still contribute to the maintenance of altruism in unicolonial populations if competition occurs among clusters.

Characterization of Human Late Outgrowth Endothelial Progenitor-Derived Cells under Various Flow Conditions.

Background: Endothelial progenitor-derived cells (EPC) are a cell therapy tool in peripheral arterial disease and for re-endothelialization of bypasses and stents. Objective: To assess EPC behavior under flow conditions normally found in vivo. Results: EPC were isolated from human cord blood, cultured on compliant tubes and exposed in an in vitro flow system mimicking hemodynamic environments normally found in medium and large arteries. EPC exposed for 24 h to unidirectional (0.3 ± 0.1 or 6 ± 3 dynes/cm(2)) shear stress oriented along flow direction, while those exposed to bidirectional shear stress (0.3 ± 3 dynes/cm(2)) or static conditions had random orientation. Under bidirectional flow, tissue factor (TF) activity and mRNA expression were significantly increased (2.5- and 7.0-fold) compared to static conditions. Under low shear unidirectional flow TF mRNA increased 4.9 ± 0.5-fold. Similar flow-induced increases were observed for TF in mature umbilical vein-derived endothelial cells. Expression of tissue-type plasminogen activator (t-PA), urokinase (u-PA) and monocyte chemotactic protein 1 (MCP1) were reduced by 40-60% in late outgrowth endothelial progenitor-derived cells (LO-EPC) exposed to any flow environment, while MCP1, but not t-PA or u-PA, was decreased in HUVEC. Conclusions: Flow, in particular bidirectional, modifies the hemostatic balance in LO-EPC with increased TF and decreased plasminogen activator expression.

Numerical analysis of wave-induced fluid flow effects on seismic data: Application to monitoring of CO2 storage at the Sleipner Field

In this work we analyze how patchy distributions of CO2 and brine within sand reservoirs may lead to significant attenuation and velocity dispersion effects, which in turn may have a profound impact on surface seismic data. The ultimate goal of this paper is to contribute to the understanding of these processes within the framework of the seismic monitoring of CO2 sequestration, a key strategy to mitigate global warming. We first carry out a Monte Carlo analysis to study the statistical behavior of attenuation and velocity dispersion of compressional waves traveling through rocks with properties similar to those at the Utsira Sand, Sleipner field, containing quasi-fractal patchy distributions of CO2 and brine. These results show that the mean patch size and CO2 saturation play key roles in the observed wave-induced fluid flow effects. The latter can be remarkably important when CO2 concentrations are low and mean patch sizes are relatively large. To analyze these effects on the corresponding surface seismic data, we perform numerical simulations of wave propagation considering reservoir models and CO2 accumulation patterns similar to the CO2 injection site in the Sleipner field. These numerical experiments suggest that wave-induced fluid flow effects may produce changes in the reservoir's seismic response, modifying significantly the main seismic attributes usually employed in the characterization of these environments. Consequently, the determination of the nature of the fluid distributions as well as the proper modeling of the seismic data constitute important aspects that should not be ignored in the seismic monitoring of CO2 sequestration problems.

Genetic evidence for female-biased dispersal and gene flow in a polygynous primate.

Many models of sex-biased dispersal predict that the direction of sex-bias depends upon a species' mating system. In agreement with this, almost all polygynous mammals show male-biased dispersal whereas largely monogamous birds show female-biased dispersal (FBD). The hamadryas baboon (Papio hamadryas hamadryas) is polygynous and so dispersal is predicted to be male biased, as is found in all other baboon subspecies, but there are conflicting field data showing both female and male dispersal. Using 19 autosomal genetic markers genotyped in baboons from four Saudi Arabian populations, we found strong evidence for FBD in post-dispersal adults but not, as expected, in pre-dispersal infants and young juveniles, when we compared male and female: population structure (F(st)), inbreeding (F(is)), relatedness (r), and the mean assignment index (mAIc). Furthermore, we found evidence for female-biased gene flow as population genetic structure (F(st)), was about four times higher for the paternally inherited Y, than for either autosomal markers or for maternally inherited mtDNA. These results contradict the direction of sex-bias predicted by the mating system and show that FBD has evolved recently from an ancestral state of male-biased dispersal. We suggest that the cost-benefit balance of dispersal to males and females is tightly linked to the unique hierarchical social structure of hamadryas baboons and that dispersal and social organization have coevolved.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Extension of Murray's law using a non-Newtonian model of blood flow.

BACKGROUND: So far, none of the existing methods on Murray's law deal with the non-Newtonian behavior of blood flow although the non-Newtonian approach for blood flow modelling looks more accurate. MODELING: In the present paper, Murray's law which is applicable to an arterial bifurcation, is generalized to a non-Newtonian blood flow model (power-law model). When the vessel size reaches the capillary limitation, blood can be modeled using a non-Newtonian constitutive equation. It is assumed two different constraints in addition to the pumping power: the volume constraint or the surface constraint (related to the internal surface of the vessel). For a seek of generality, the relationships are given for an arbitrary number of daughter vessels. It is shown that for a cost function including the volume constraint, classical Murray's law remains valid (i.e. SigmaR(c) = cste with c = 3 is verified and is independent of n, the dimensionless index in the viscosity equation; R being the radius of the vessel). On the contrary, for a cost function including the surface constraint, different values of c may be calculated depending on the value of n. RESULTS: We find that c varies for blood from 2.42 to 3 depending on the constraint and the fluid properties. For the Newtonian model, the surface constraint leads to c = 2.5. The cost function (based on the surface constraint) can be related to entropy generation, by dividing it by the temperature. CONCLUSION: It is demonstrated that the entropy generated in all the daughter vessels is greater than the entropy generated in the parent vessel. Furthermore, it is shown that the difference of entropy generation between the parent and daughter vessels is smaller for a non-Newtonian fluid than for a Newtonian fluid.

The effect of learning on the evolution of new courtship behavior: a simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.