A quasispecies approach to the evolution of sexual replication in unicellular organisms

This study develops a simplified model describing the evolutionary dynamics of a population composed of obligate sexually and asexually reproducing, unicellular organisms. The model assumes that the organisms have diploid genomes consisting of two chromosomes, and that the sexual organisms replicate by first dividing into haploid intermediates, which then combine with other haploids, followed by the normal mitotic division of the resulting diploid into two new daughter cells. We assume that the fitness landscape of the diploids is analogous to the single-fitness-peak approach often used in single-chromosome studies. That is, we assume a master chromosome that becomes defective with just one point mutation. The diploid fitness then depends on whether the genome has zero, one, or two copies of the master chromosome. We also assume that only pairs of haploids with a master chromosome are capable of combining so as to produce sexual diploid cells, and that this process is described by second-order kinetics. We find that, in a range of intermediate values of the replication fidelity, sexually reproducing cells can outcompete asexual ones, provided the initial abundance of sexual cells is above some threshold value. The range of values where sexual reproduction outcompetes asexual reproduction increases with decreasing replication rate and increasing population density. We critically evaluate a common approach, based on a group selection perspective, used to study the competition between populations and show its flaws in addressing the evolution of sex problem.

Recording from Two Neurons: Second-Order Stimulus Reconstruction from Spike Trains and Population Coding

We study the reconstruction of visual stimuli from spike trains, representing the reconstructed stimulus by a Volterra series up to second order. We illustrate this procedure in a prominent example of spiking neurons, recording simultaneously from the two H1 neurons located in the lobula plate of the fly Chrysomya megacephala. The fly views two types of stimuli, corresponding to rotational and translational displacements. Second-order reconstructions require the manipulation of potentially very large matrices, which obstructs the use of this approach when there are many neurons. We avoid the computation and inversion of these matrices using a convenient set of basis functions to expand our variables in. This requires approximating the spike train four-point functions by combinations of two-point functions similar to relations, which would be true for gaussian stochastic processes. In our test case, this approximation does not reduce the quality of the reconstruction. The overall contribution to stimulus reconstruction of the second-order kernels, measured by the mean squared error, is only about 5% of the first-order contribution. Yet at specific stimulus-dependent instants, the addition of second-order kernels represents up to 100% improvement, but only for rotational stimuli. We present a perturbative scheme to facilitate the application of our method to weakly correlated neurons.

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.

A Serious Gaming Approach For Serious Stakeholder Participation

Serious games are a category of games which are designed for a specific purpose other than for pure entertainment. It is not a new concept but serious games using real data, coupled with real time modelling and combining model results with social and economic factors opens up a new paradigm for active stakeholder participation. DHI and UNEP-DHI Centre initiated a project called Aqua Republica where a virtual world is developed which allows participants to develop a river basin and visualise the consequences of their decisions. The aim of this project is to raise awareness of the interconnectivity of water and educate on integrated water resources management. Aqua Republica combines a game layer with a water allocation model, MIKE BASIN, to create an interactive, realistic virtual environment where players play the role of a catchment manager of an undeveloped river catchment. Their main objective is to develop the river catchment to be as prosperous as it can be. To achieve that, they will need to generate a good economy in the catchment to provide the funds needed for development, have a steady food supply for their population and enough energy and water for the catchment. Through these actions by the player, a meaningful play is established to engage players and to educate them about the complex relationships between developmental actions in a river basin and the natural environment as well as their consequences. The game layer also consists of a reward system to encourage learning. People can play and replay the game, get rewarded from performing the right principles and penalised from failures in the game. This abstract will explain the concept of the game and how it has been used in a stakeholder participation environment.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Comparison of selective genotyping strategies for prediction of breeding values in a population undergoing selection

Genomewide marker information can improve the reliability of breeding value predictions for young selection candidates in genomic selection. However, the cost of genotyping limits its use to elite animals, and how such selective genotyping affects predictive ability of genomic selection models is an open question. We performed a simulation study to evaluate the quality of breeding value predictions for selection candidates based on different selective genotyping strategies in a population undergoing selection. The genome consisted of 10 chromosomes of 100 cM each. After 5,000 generations of random mating with a population size of 100 (50 males and 50 females), generation G(0) (reference population) was produced via a full factorial mating between the 50 males and 50 females from generation 5,000. Different levels of selection intensities (animals with the largest yield deviation value) in G(0) or random sampling (no selection) were used to produce offspring of G(0) generation (G(1)). Five genotyping strategies were used to choose 500 animals in G(0) to be genotyped: 1) Random: randomly selected animals, 2) Top: animals with largest yield deviation values, 3) Bottom: animals with lowest yield deviations values, 4) Extreme: animals with the 250 largest and the 250 lowest yield deviations values, and 5) Less Related: less genetically related animals. The number of individuals in G(0) and G(1) was fixed at 2,500 each, and different levels of heritability were considered (0.10, 0.25, and 0.50). Additionally, all 5 selective genotyping strategies (Random, Top, Bottom, Extreme, and Less Related) were applied to an indicator trait in generation G(0), and the results were evaluated for the target trait in generation G(1), with the genetic correlation between the 2 traits set to 0.50. The 5 genotyping strategies applied to individuals in G(0) (reference population) were compared in terms of their ability to predict the genetic values of the animals in G(1) (selection candidates). Lower correlations between genomic-based estimates of breeding values (GEBV) and true breeding values (TBV) were obtained when using the Bottom strategy. For Random, Extreme, and Less Related strategies, the correlation between GEBV and TBV became slightly larger as selection intensity decreased and was largest when no selection occurred. These 3 strategies were better than the Top approach. In addition, the Extreme, Random, and Less Related strategies had smaller predictive mean squared errors (PMSE) followed by the Top and Bottom methods. Overall, the Extreme genotyping strategy led to the best predictive ability of breeding values, indicating that animals with extreme yield deviations values in a reference population are the most informative when training genomic selection models.

Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Pharmaceutical emulsions: a new approach for gene therapy

The concept of gene therapy involves the experimental transfer of a therapeutic gene into an individual's cells and tissues to replace an abnormal gene aiming to treat a disease, or to use the gene to treat a disease just like a medicine, improving the clinical status of a patient. The achievement of a foreigner nucleic acid into a population of cells requires its transfer to the target. Therefore, it is essential to create carriers (vectors) that transfer and protect the nucleic acid until it reaches the target. The obvious disadvantages of the use of viral vectors have directed the research for the development of a nonviral organized system such as emulsions. In fact, recently, there has been an increase of interest in its use in biotechnology as a nonviral vector for gene therapy. This review focuses on the progress of cationic emulsions and the improvement of the formulations, as a potential delivery system for gene therapy.

The sugarcane borer Diatraea saccharalis (Fabr.) (Lep., Crambidae) and its parasitoids: a synchrony approach to spatial and temporal dynamics

A data set on Diatraea saccharalis and its parasitoids, Cotesia flavipes and tachinid flies, was analysed at five spatial scales-sugarcane mill, region, intermediary, farm and zone-to determine the role of spatial scale in synchrony patterns, and on temporal population variability. To analyse synchrony patterns, only the three highest spatial scales were considered, but for temporal population variability, all spatial scales were adopted. The synchrony-distance relationship revealed complex spatial structures depending on both species and spatial scale. Temporal population variability [SD log(x+1)] levels were highest at the smallest spatial scales although, in the majority of the cases, temporal variability was inversely dependent on sample size. All the species studied, with a few exceptions, presented spatial synchrony independent of spatial scale. The tachinid flies exhibited stronger synchrony dynamics than D. saccharalis and C. flavipes in all spatial scales with the latter displaying the weakest synchrony levels, except when mill spatial scales were compared. In some cases spatial synchrony may at first decay and then increase with distance, but the presence of such patterns can change depending on the spatial scale adopted.

How the interplay between individual spatial memory and landscape persistence can generate population distribution patterns

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Correlation between the mobility of spin-labeled peptide chains and resin solvation: An approach to optimize the synthesis of aggregating sequences

Resin solvation properties affect the efficiency of the coupling reactions in solid-phase peptide synthesis. Here we report a novel approach to evaluate resin solvation properties, making use of spin label electron paramagnetic resonance (EPR) spectroscopy. The aggregating VVLGAAIV and ING sequences were assembled in benzhydrylamine-resin with different amino group contents (up to 2.6 mmol/g) to examine the extent of chain association within the beads. These model peptidyl-resins were first labeled at their N-terminus with the amino acid spin label 2,2,6,6-tetramethylpiperidine-N-oxyl-4-amino-4-carboxylic acid (Toac). Their solvation properties in different solvents were estimated, either by bead swelling measurement or by assessing the dynamics of their polymeric matrixes through the analysis of Toac EPR spectra, and were correlated with the yield of the acylation reaction. In most cases the coupling rate was found to depend on bead swelling. Comparatively, the EPR approach was more effective. Line shape analysis allowed the detection of more than one peptide chain population, which influenced the reaction. The results demonstrated the unique potential of EPR spectroscopy not only for improving the yield of peptide synthesis, even in challenging conditions, but also for other relevant polymer-supported methodologies in chemistry and biology.

Pb1-xCaxTiO3 solid solution (x=0.0, 0.25, 0.50, and 0.75): A theoretical and experimental approach

In this paper we report an experimental and theoretical study based on a periodic density functional investigation into selected compositions of Pb1-xCaxTiO3 (x=0.0, 0.25, 0.50, and 0.75). Based on our findings, we propose that the pseudocubic structure of these perovskites presents a long-range tendency for cubic symmetry, while the short-range displacements bring the solid solution to a tetragonal symmetry. The results are discussed in terms of x-ray diffraction, structural optimized parameters, Raman spectroscopy, band structure, density of states, Mulliken charge, and overlap population.

Population genetic structure and dispersal in white-lipped peccaries (Tayassu pecari) from the Brazilian Pantanal

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Inclusive Social Protection in Latin America: a comprehensive, rights-based approach

Incluye Bibliografía