Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

Triatominae as a model of morphological plasticity under ecological pressure

The use of biochemical and genetic characters to explore species or population relationships has been applied to taxonomic questions since the 60s. In responding to the central question of the evolutionary history of Triatominae, i.e. their monophyletic or polyphyletic origin, two important questions arise (i) to what extent is the morphologically-based classification valid for assessing phylogenetic relationships? and (ii) what are the main mechanisms underlying speciation in Triatominae? Phenetic and genetic studies so far developed suggest that speciation in Triatominae may be a rapid process mainly driven by ecological factors.

Credit risk contributions under the Vasicek one-factor model: a fast wavelet expansion approximation

To measure the contribution of individual transactions inside the total risk of a credit portfolio is a major issue in financial institutions. VaR Contributions (VaRC) and Expected Shortfall Contributions (ESC) have become two popular ways of quantifying the risks. However, the usual Monte Carlo (MC) approach is known to be a very time consuming method for computing these risk contributions. In this paper we consider the Wavelet Approximation (WA) method for Value at Risk (VaR) computation presented in [Mas10] in order to calculate the Expected Shortfall (ES) and the risk contributions under the Vasicek one-factor model framework. We decompose the VaR and the ES as a sum of sensitivities representing the marginal impact on the total portfolio risk. Moreover, we present technical improvements in the Wavelet Approximation (WA) that considerably reduce the computational effort in the approximation while, at the same time, the accuracy increases.

Inducible gene expression in fetal thymic epithelium: A new BAC transgenic model.

The thymus is the site of T cell development. Several stromal and hematopoietic cell types are necessary for the proper function of thymic selection and eventually peripheral immunity. Thymic epithelial cells (TECs) are essential for T cell lineage commitment, expansion, and maturation in the thymus. We were interested in developing an in vivo model in which exogenous gene expression could be transiently induced in embryonic TEC (Tet-On system). To this end, we have generated a bacterial artificial chromosome (BAC) transgenic mouse line in which the reverse tetracycline-dependent transactivator (rtTA) is expressed under the control of the Foxn1 promoter, a transcriptional factor indispensable for TEC development. To analyze the expression pattern and efficiency of this novel mouse model, we crossed the Foxn1-rtTA founder with a Tet-Responsive Element (TRE)-LacZ GFP mouse reporter to obtain a double transgenic mouse. In the presence of doxycycline, rtTA can interact with TRE and induce the expression of GFP and LacZ. In this double transgenic mouse, we observed that GFP expression was high, inducible and limited to TEC in fetal thymus. In contrast, in adult thymus, when TEC development and maturation is completed, GFP was barely detectable. Therefore, Foxn1-rtTA represents a new and efficient transgenic mouse model to induce genes of interest specifically in fetal thymic epithelium. genesis 51:717-724. © 2013 Wiley Periodicals, Inc.

The robustness of the weak selection approximation for the evolution of altruism against strong selection.

The weak selection approximation of population genetics has made possible the analysis of social evolution under a considerable variety of biological scenarios. Despite its extensive usage, the accuracy of weak selection in predicting the emergence of altruism under limited dispersal when selection intensity increases remains unclear. Here, we derive the condition for the spread of an altruistic mutant in the infinite island model of dispersal under a Moran reproductive process and arbitrary strength of selection. The simplicity of the model allows us to compare weak and strong selection regimes analytically. Our results demonstrate that the weak selection approximation is robust to moderate increases in selection intensity and therefore provides a good approximation to understand the invasion of altruism in spatially structured population. In particular, we find that the weak selection approximation is excellent even if selection is very strong, when either migration is much stronger than selection or when patches are large. Importantly, we emphasize that the weak selection approximation provides the ideal condition for the invasion of altruism, and increasing selection intensity will impede the emergence of altruism. We discuss that this should also hold for more complicated life cycles and for culturally transmitted altruism. Using the weak selection approximation is therefore unlikely to miss out on any demographic scenario that lead to the evolution of altruism under limited dispersal.

Population pharmacokinetics of imatinib in CML and GIST patients under long-term treatment

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumour (GIST). However, the treatment must be taken indefinitely and is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occurs in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene), and is also bound to the alpha1-acid glycoprotein (AAG) in plasma. Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations were measured in 59 patients receiving Glivec® at diverse dosage regimens, using a validated chromatographic method developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one-compartment model with first-order absorption described the data appropriately, with an average apparent clearance of 12.4 l/h, a volume of distribution of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T and the AAG phenotype appears to modulate the disposition of imatinib. Large inter-individual variability (CV %) remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen. This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help in individualising the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Adverse selection, moral hazard, and outlier payment policy

In this article, we analyze the rationale for introducing outlier payments into a prospective payment system for hospitals under adverse selection and moral hazard. The payer has only two instruments: a fixed price for patients whose treatment cost is below a threshold and a cost-sharing rule for outlier patients. We show that a fixed-price policy is optimal when the hospital is sufficiently benevolent. When the hospital is weakly benevolent, a mixed policy solving a trade-off between rent extraction, efficiency, and dumping deterrence must be preferred. We show how the optimal combination of fixed price and partially cost-based payment depends on the degree of benevolence of the hospital, the social cost of public funds, and the distribution of patients severity. [Authors]

Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

Electoral competition through issue selection

Politics must tackle multiple issues at once. In a first-best world, political competition constrains parties to prioritize issues according to the voters' true concerns. In the real world, the opposite also happens: parties manipulate voter priorities by emphasizing issues selectively during the political campaign. This phenomenon, known as priming, should allow parties to pay less attention to the issues that they intend to mute. We develop a model of endogenous issue ownership in which two vote-seeking parties (i) invest to attract voters with "better" policy proposals and (ii) choose a communication campaign to focus voter attention on specific issues. We identify novel feedbacks between communication and investment. In particular, we find that stronger priming effects can backfire by constraining parties to invest more resources in all issues, including the ones they would otherwise intend to mute. We also identify under which conditions parties prefer to focus on their "historical issues" or to engage in issue stealing. Typically, the latter happens when priming effects are strong, and historical reputations differentiates parties less.

A metapopulation model for the introgression from genetically modified plants into their wild relatives

Most models on introgression from genetically modified (GM) plants have focused on small spatial scales, modelling gene flow from a field containing GM plants into a single adjacent population of a wild relative. Here, we present a model to study the effect of introgression from multiple plantations into the whole metapopulation of the wild relative. The most important result of the model is that even very low levels of introgression and selection can lead to a high probability that the transgene goes to fixation in the metapopulation. Furthermore, the overall frequency of the transgene in the metapopulation, after a certain number of generations of introgression, depends on the population dynamics. If there is a high rate of migration or a high rate of population turnover, the overall transgene frequency is much higher than with lower rates. However, under an island model of population structure, this increased frequency has only a very small effect on the probability of fixation of the transgene. Considering these results, studies on the potential ecological risks of introgression from GM plants should look not only at the rate of introgression and selection acting on the transgene, but also at the metapopulation dynamics of the wild relative.

Population pharmacokinetics of imatinib in CML and GIST patients under long-term treatment

Imatinib (Glivec®) has transformed the treatment and short-term prognosis of chronic myeloid leukaemia (CML) and gastro-intestinal stromal tumour (GIST). However, the treatment must be taken indefinitely, it is not devoid of inconvenience and toxicity. Moreover, resistance or escape from disease control occur in a significant number of patients. Imatinib is a substrate of the cytochromes P450 CYP3A4/5 and of the multidrug transporter P glycoprotein (product of the MDR1 gene). Considering the large inter-individual differences in the expression and function of those systems, the disposition and clinical activity of imatinib can be expected to vary widely among patients, calling for dosage individualisation. The aim of this exploratory study was to determine the average pharmacokinetic parameters characterizing the disposition of imatinib in the target population, to assess their inter-individual variability, and to identify influential factors affecting them. A total of 321 plasma concentrations, taken at various sampling times after latest dose, were measured in 59 patients receiving Glivec® at diverse regimens, using a validated chromatographic method (HPLC-UV) developed for this study. The results were analysed by non-linear mixed effect modelling (NONMEM). A one- compartment model with first-order absorption appeared appropriate to describe the data, with an average apparent clearance of 12.4 l/h, a distribution volume of 268 l and an absorption constant of 0.47 h-1. The clearance was affected by body weight, age and sex. No influences of interacting drugs were found. DNA samples were used for pharmacogenetic explorations. The MDR1 polymorphism 3435C>T appears to affect the disposition of imatinib. Large inter-individual variability remained unexplained by the demographic covariates considered, both on clearance (40%) and distribution volume (71%). Together with intra-patient variability (34%), this translates into an 8-fold width of the 90%-prediction interval of plasma concentrations expected under a fixed dosing regimen ! This is a strong argument to further investigate the possible usefulness of a therapeutic drug monitoring programme for imatinib. It may help to individualise the dosing regimen before overt disease progression or observation of treatment toxicity, thus improving both the long-term therapeutic effectiveness and tolerability of this drug.

Duplication and concerted evolution in a master sex determiner under balancing selection.

The transformer (tra) gene is a key regulator in the signalling hierarchy controlling all aspects of somatic sexual differentiation in Drosophila and other insects. Here, we show that six of the seven sequenced ants have two copies of tra. Surprisingly, the two paralogues are always more similar within species than among species. Comparative sequence analyses indicate that this pattern is owing to the ongoing concerted evolution after an ancestral duplication rather than independent duplications in each of the six species. In particular, there was strong support for inter-locus recombination between the paralogues of the ant Atta cephalotes. In the five species where the location of paralogues is known, they are adjacent to each other in four cases and separated by only few genes in the fifth case. Because there have been extensive genomic rearrangements in these lineages, this suggests selection acting to conserve their synteny. In three species, we also find a signature of positive selection in one of the paralogues. In three bee species where information is available, the tra gene is also duplicated, the copies are adjacent and in at least one species there was recombination between paralogues. These results suggest that concerted evolution plays an adaptive role in the evolution of this gene family.

An adult thymic stromal-cell suspension model for in vitro positive selection.

Presented here is a cell-suspension model for positive selection using thymocytes from alphabeta-TCR (H-2Db-restricted) transgenic mice specific to the lymphocytic choriomeningitis virus (LCMV) on a nonselecting MHC background (H-2d or TAP-1 -/-), cocultured with freshly isolated adult thymus stromal cells of the selecting MHC type. The thymic stromal cells alone induced positive selection of functional CD4- CD8+ cells whose kinetics and efficiency were enhanced by nominal peptide. Fibroblasts expressing the selecting MHC alone did not induce positive selection; however, together with nonselecting stroma and nominal peptide, there was inefficient positive. These results suggest multiple signaling in positive selection with selection events able to occur on multiple-cell types. The ease with which this model can be manipulated should greatly facilitate the resolution of the mechanisms of positive selection in normal and pathological states.