Tackling self-selection into treatment and self-selection into the sample biases in VAA research

Self‐selection into treatment and self‐selection into the sample are major concerns of VAA research and need to be controlled for if the aim is to deduce causal effects from VAA use in observational data. This paper focuses on the methodological aspects of VAA research and outlines omnipresent endogeneity issues, partly imposed through unobserved factors that affect both whether individuals chose to use VAAs and their electoral behavior. We promote using Heckman selection models and apply various versions of the model to data from the Swiss electorate and smartvote users in order to see to what extent selection biases interfere with the estimated effects of interest.

A generalized mechanistic codon model.

Models of codon evolution have attracted particular interest because of their unique capabilities to detect selection forces and their high fit when applied to sequence evolution. We described here a novel approach for modeling codon evolution, which is based on Kronecker product of matrices. The 61 × 61 codon substitution rate matrix is created using Kronecker product of three 4 × 4 nucleotide substitution matrices, the equilibrium frequency of codons, and the selection rate parameter. The entities of the nucleotide substitution matrices and selection rate are considered as parameters of the model, which are optimized by maximum likelihood. Our fully mechanistic model allows the instantaneous substitution matrix between codons to be fully estimated with only 19 parameters instead of 3,721, by using the biological interdependence existing between positions within codons. We illustrate the properties of our models using computer simulations and assessed its relevance by comparing the AICc measures of our model and other models of codon evolution on simulations and a large range of empirical data sets. We show that our model fits most biological data better compared with the current codon models. Furthermore, the parameters in our model can be interpreted in a similar way as the exchangeability rates found in empirical codon models.

The evolution of XY recombination: sexually antagonistic selection versus deleterious mutation load.

Recombination arrest between X and Y chromosomes, driven by sexually antagonistic genes, is expected to induce their progressive differentiation. However, in contrast to birds and mammals (which display the predicted pattern), most cold-blooded vertebrates have homomorphic sex chromosomes. Two main hypotheses have been proposed to account for this, namely high turnover rates of sex-determining systems and occasional XY recombination. Using individual-based simulations, we formalize the evolution of XY recombination (here mediated by sex reversal; the "fountain-of-youth" model) under the contrasting forces of sexually antagonistic selection and deleterious mutations. The shift between the domains of elimination and accumulation occurs at much lower selection coefficients for the Y than for the X. In the absence of dosage compensation, mildly deleterious mutations accumulating on the Y depress male fitness, thereby providing incentives for XY recombination. Under our settings, this occurs via "demasculinization" of the Y, allowing recombination in XY (sex-reversed) females. As we also show, this generates a conflict with the X, which coevolves to oppose sex reversal. The resulting rare events of XY sex reversal are enough to purge the Y from its load of deleterious mutations. Our results support the "fountain of youth" as a plausible mechanism to account for the maintenance of sex-chromosome homomorphy.

Size-dependent predation by Dugesia lugubris (Turbellaria) on Physa acuta (Gastropoda): experiments and model

1. We investigated experimentally predation by the flatworm Dugesia lugubris on the snail Physa acuta in relation to predator body length and to prey morphology [shell length (SL) and aperture width (AW)]. 2. SL and AW correlate strongly in the field, but display significant and independent variance among populations. In the laboratory, predation by Dugesia resulted in large and significant selection differentials on both SL and AW. Analysis of partial effects suggests that selection on AW was indirect, and mediated through its strong correlation with SL. 3. The probability P(ij) for a snail of size category i (SL) to be preyed upon by a flatworm of size category j was fitted with a Poisson-probability distribution, the mean of which increased linearly with predator size (i). Despite the low number of parameters, the fit was excellent (r2 = 0.96). We offer brief biological interpretations of this relationship with reference to optimal foraging theory. 4. The largest size class of Dugesia (>2 cm) did not prey on snails larger than 7 mm shell length. This size threshold might offer Physa a refuge against flatworm predation and thereby allow coexistence in the field. 5. Our results are further discussed with respect to previous field and laboratory observations on P acuta life-history patterns, in particular its phenotypic variance in adult body size.

SlimCodeML: An Optimized Version of CodeML for the Branch-Site Model

CodeML (part of the PAML package) im- plements a maximum likelihood-based approach to de- tect positive selection on a specific branch of a given phylogenetic tree. While CodeML is widely used, it is very compute-intensive. We present SlimCodeML, an optimized version of CodeML for the branch-site model. Our performance analysis shows that SlimCodeML substantially outperforms CodeML (up to 9.38 times faster), especially for large-scale genomic analyses.

Endogenous Credit Cycles and Financial Dampening in an Adverse Selection Economy

We propose an adverse selection framework in which the financial sector has a dual role. It amplifies or dampens exogenous shocks and also generates endogenous fluctuations. We fully characterize constrained optimal contracts in a setting in which entrepreneurs need to borrow and are privately informed about the quality of their projects. Our characterization is novel in analyzing pooling and separating allocations in a context of multi-dimensional screening: specifically, the amounts of investment undertaken and of entrepreneurial net worth are used to screen projects. We then embed these results in a dynamic competitive economy. First, we show how endogenous regime switches in financial contracts may generate fluctuations in an economy that exhibits no dynamics under full information. Unlike previous models of endogenous cycles, our result does not rely on entrepreneurial net worth being counter-cyclical or inconsequential for determining investment. Secondly, the model shows the different implications of adverse selection as opposed to pure moral hazard. In particular, and contrary to standard results in the macroeconomic literature, the financial system may dampen exogenous shocks in the presence of adverse selection.

Cumulative cultural dynamics and the coevolution of cultural innovation and transmission: an ESS model for panmictic and structured populations.

When individuals in a population can acquire traits through learning, each individual may express a certain number of distinct cultural traits. These traits may have been either invented by the individual himself or acquired from others in the population. Here, we develop a game theoretic model for the accumulation of cultural traits through individual and social learning. We explore how the rates of innovation, decay, and transmission of cultural traits affect the evolutionary stable (ES) levels of individual and social learning and the number of cultural traits expressed by an individual when cultural dynamics are at a steady-state. We explore the evolution of these phenotypes in both panmictic and structured population settings. Our results suggest that in panmictic populations, the ES level of learning and number of traits tend to be independent of the social transmission rate of cultural traits and is mainly affected by the innovation and decay rates. By contrast, in structured populations, where interactions occur between relatives, the ES level of learning and the number of traits per individual can be increased (relative to the panmictic case) and may then markedly depend on the transmission rate of cultural traits. This suggests that kin selection may be one additional solution to Rogers's paradox of nonadaptive culture.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Myocardial flow reserve by Rb-82 cardiac PET improves the selection of patients eligible for invasive coronary angiography

Aim: We asked whether myocardial flow reserve (MFR) by Rb-82 cardiac PET improve the selection of patients eligible for invasive coronary angiography (ICA). Material and Methods: We enrolled 26 consecutive patients with suspected or known coronary artery disease who performed dynamic Rb-82 PET/CT and (ICA) within 60 days; 4 patients who underwent revascularization or had any cardiovascular events between PET and ICA were excluded. Myocardial blood flow at rest (rMBF), at stress with adenosine (sMBF) and myocardial flow reserve (MFR=sMBF/rMBF) were estimated using the 1-compartment Lortie model (FlowQuant) for each coronary arteries territories. Stenosis severity was assessed using computer-based automated edge detection (QCA). MFR was divided in 3 groups: G1:MFR<1.5, G2:1.5≤MFR<2 and G3:2≤MFR. Stenosis severity was graded as non-significant (<50% or FFR ≥0.8), intermediate (50%≤stenosis<70%) and severe (≥70%). Correlation between MFR and percentage of stenosis were assessed using a non-parametric Spearman test. Results: In G1 (44 vessels), 17 vessels (39%) had a severe stenosis, 11 (25%) an intermediate one, and 16 (36%) no significant stenosis. In G2 (13 vessels), 2 (15%) vessels presented a severe stenosis, 7 (54%) an intermediate one, and 4 (31%) no significant stenosis. In G3 (9 vessels), 0 vessel presented a severe stenosis, 1 (11%) an intermediate one, and 8 (89%) no significant stenosis. Of note, among 11 patients with 3-vessel low MFR<1.5 (G1), 9/11 (82%) had at least one severe stenosis and 2/11 (18%) had at least one intermediate stenosis. There was a significant inverse correlation between stenosis severity and MFR among all 66 territories analyzed (rho= -0.38, p=0.002). Conclusion: Patients with MFR>2 could avoid ICA. Low MFR (G1, G2) on a vessel-based analysis seems to be a poor predictor of severe stenosis severity. Patients with 3-vessel low MFR would benefit from ICA as they are likely to present a significant stenosis in at least one vessel.

Interviews and adverse selection

Interviewing in professional labor markets is a costly process for firms. Moreover, poor screening can have a persistent negative impact on firms bottom lines and candidates careers. In a simple dynamic model where firms can pay a cost to interview applicants who have private information about their own ability, potentially large inefficiencies arise from information-based unemployment, where able workers are rejected by firms because of their lack of offers in previous interviews. This effect may make the market less efficient than random matching. We show that the first best can be achieved using either a mechanism with transfers or one without transfers.

Hiring and firing costs, adverse selection and long-term unemployment

In this paper, we present a matching model with adverse selection that explains why flows into and out of unemployment are much lower in Europe compared to North America, while employment-to-employment flows are similar in the two continents. In the model,firms use discretion in terms of whom to fire and, thus, low quality workers are more likely to be dismissed than high quality workers. Moreover, as hiring and firing costs increase, firms find it more costly to hire a bad worker and, thus, they prefer to hire out of the pool of employed job seekers rather than out of the pool of the unemployed, who are more likely to turn out to be 'lemons'. We use microdata for Spain and the U.S. and find that the ratio of the job finding probability of the unemployed to the job finding probability of employed job seekers was smaller in Spain than in the U.S. Furthermore, using U.S. data, we find that the discrimination of the unemployed increased over the 1980's in those states that raised firing costs by introducing exceptions to the employment-at-will doctrine.

Signalling, mating success and paternal investment in sticklebacks (Gasterosteus aculeatus): A theoretical model

I present an optimisation model that links paternal investment, male display and female choice. Although deviced for sticklebacks, it readily applies to other fish with male guarding behaviour. It relies on a few basic assumptions on the ways hatching success depends on paternal investment and clutch size, and male survival on paternal investment and signaling. Paternal investment is here a state-dependent decision, and signal a condition-dependent handicap by which males inform females of how much they are willing to invest. Series of predictions are derived on female and male breeding strategies, including optimal levels of signaling and paternal investment as functions of clutch size, own condition, and residual reproductive value, as well as alternative strategies such as egg kleptoparasitism. Some predictions already have empirical support, for which the present model provides new interpretations. Other might readily be tested, e.g. by simple clutch-size manipulations.

Autoreactive T cells that bypass negative selection are not tolerant and respond to self-antigen stimulation during infection

Le répertoire cellulaire Τ a pour but d'être tolérant aux antigènes du soi afin d'éviter l'induction de maladies autoimmunes. C'est pourquoi les lymphocytes Τ autoréactifs sont éliminés dans le thymus lors de leur développement par le processus de sélection négative. La plupart des recherches étudient les lymphocytes Τ de haute avidité. Ces lymphocytes Τ de haute avidité sont très sensibles et réagissent fortement à un antigène du soi. En conséquence, ces cellules induisent le développement de maladies autoimmunes lorsqu'elles ciblent des organes exprimant l'antigène du soi. Plusieurs études ont montré que les lymphocytes Τ qui réagissent faiblement aux antigènes spécifiques à un tissu, nommé lymphocytes Τ de faible avidité, peuvent contourner les mécanismes de tolérance centrale et périphérique. J'ai utilisé des souris Rip-mOva qui expriment l'Ovalbumine comme antigène du soi spécifique à un tissu. Dans ces souris transgéniques Rip-mOva, les lymphocytes Τ de faible avidité survivent à la sélection négative. Une fois stimulés à la périphérie, ces lymphocytes Τ CD8+ de faible avidité ont la capacité d'infiltrer les organes qui expriment l'antigène du soi chez les souris Rip-mOva et peuvent induire une destruction tissulaire. L'objectif principal de mon projet de thèse était de comprendre les caractéristiques phénotypiques et fonctionnelles de ces lymphocytes Τ dans un état d'équilibre et dans un contexte infectieux. Pour étudier ces cellules dans un modèle murin bien défini, nous avons généré des souris exprimant un récepteur de cellule Τ transgénique appelé OT-3. Ces souris transgéniques OT-3 ont des lymphocytes Τ CD8+ de faible avidité spécifiques à l'épitope SIINFEKL de l'antigène Ovalbumine. Nous avons démontré qu'un grand nombre de lymphocytes Τ CD8+ OT-3 ne sont pas éliminés lors de la sélection négative dans le thymus après avoir rencontré l'antigène du soi. Par conséquent, les lymphocytes Τ OT-3 de faible avidité sont présents dans une fenêtre de sélection comprise entre la sélection positive et négative. Cette limite se définie comme le seuil d'affinité et est impliquée dans l'échappement de certains lymphocytes Τ OT- 3 autoréactifs. A la périphérie, ces cellules sont capables d'induire une autoimmunité après stimulation au cours d'une infection, ce qui nous permet de les définir comme étant non tolérante et non dans un état anergique à la périphérie. Nous avons également étudié le seuil d'activation des lymphocytes Τ OT-3 à faible avidité à la périphérie et avons constaté que des ligands peptidiques plus faibles que l'épitope natif SIINFEKL sont capables de les activer au cours d'une infection ainsi que de les différencier en lymphocytes Τ effecteurs et mémoires. Les données illustrent une déficience lors de la sélection négative dans le thymus de lymphocytes Τ CD8+ autoréactifs de faible avidité contre un antigène du soi spécifique à tissu et montrent que ces cellules sont entièrement compétentes lors d'une infection. - The diverse Τ cell repertoire needs to be tolerant to self-antigen to avoid the induction of autoimmunity. This is why autoreactive developing Τ cells are deleted in the thymus. The deletion of self-reactive Τ cells occurs through the process of negative selection. Most studies investigated high avidity Τ cells. These high avidity Τ cells are very sensitive and strongly react to a self-antigen. As a consequence, these cells induce the development of autoimmunity when they target organs which express the self-antigen. High avidity autoreactive CD8+ Τ cells are deleted in the thymus. However, several studies have shown Τ cells that weakly respond to tissue-restricted antigen, referred to as low avidity Τ cells, can bypass central and peripheral tolerance mechanisms. I used Rip-mOva mice that expressed Ovalbumin as a neo self-antigen in a tissue-restricted fashion. In these transgenic Rip-mOva mice low avidity CD8+ Τ cells survive negative selection. Upon stimulation in the periphery, these low avidity CD8+ Τ cells have the ability to infiltrate organs that express the self-antigen in the Rip-mOva mice and can also induce the destruction of the tissue. The major aim of my PhD project was to understand the phenotypic and functionality characteristics of these Τ cells in a steady-state condition and in a context of an infection. To study these cells in a well-defined mouse model, we generated OT-3 Τ cell receptor transgenic mice that express low avidity CD8+ Τ cells that are specific for the SIINFEKL epitope of the Ovalbumin antigen. We have been able to demonstrate that a large number of OT-3 CD8+ Τ cells survive negative selection in the thymus after encountering the self-antigen. Thus, low avidity OT-3 Τ cells are present in a window of selection comprised between positive and negative selection. This boundary defined as the affinity threshold is involved in the escape of some autoreactive low avidity OT-3 Τ cells. Once they circulate in the periphery, they are able to induce autoimmunity after stimulation during an infection, allowing us to allocate these cells as being non-tolerant and not in an anergic state in the periphery. We have also looked at the threshold of activation of low avidity OT-3 CD8+ Τ cells in the periphery and found that peptide ligands that are weaker than the native SIINFEKL epitope are able to activate OT-3 Τ cells during an infection and to differentiate them into effector and memory Τ cells. The data illustrate the impairment of negatively selecting low avidity autoreactive CD8+ Τ cells against a tissue-restricted antigen in the thymus and shows that these cells are fully competent upon an infection.

Defining new criteria for selection of cell-based intestinal models using publicly available databases.

BACKGROUND: The criteria for choosing relevant cell lines among a vast panel of available intestinal-derived lines exhibiting a wide range of functional properties are still ill-defined. The objective of this study was, therefore, to establish objective criteria for choosing relevant cell lines to assess their appropriateness as tumor models as well as for drug absorption studies. RESULTS: We made use of publicly available expression signatures and cell based functional assays to delineate differences between various intestinal colon carcinoma cell lines and normal intestinal epithelium. We have compared a panel of intestinal cell lines with patient-derived normal and tumor epithelium and classified them according to traits relating to oncogenic pathway activity, epithelial-mesenchymal transition (EMT) and stemness, migratory properties, proliferative activity, transporter expression profiles and chemosensitivity. For example, SW480 represent an EMT-high, migratory phenotype and scored highest in terms of signatures associated to worse overall survival and higher risk of recurrence based on patient derived databases. On the other hand, differentiated HT29 and T84 cells showed gene expression patterns closest to tumor bulk derived cells. Regarding drug absorption, we confirmed that differentiated Caco-2 cells are the model of choice for active uptake studies in the small intestine. Regarding chemosensitivity we were unable to confirm a recently proposed association of chemo-resistance with EMT traits. However, a novel signature was identified through mining of NCI60 GI50 values that allowed to rank the panel of intestinal cell lines according to their drug responsiveness to commonly used chemotherapeutics. CONCLUSIONS: This study presents a straightforward strategy to exploit publicly available gene expression data to guide the choice of cell-based models. While this approach does not overcome the major limitations of such models, introducing a rank order of selected features may allow selecting model cell lines that are more adapted and pertinent to the addressed biological question.

Applicability of a distributed watershed pollution model in a data-poor environment in Santa Catarina State, Brazil

Intensification of agricultural production without a sound management and regulations can lead to severe environmental problems, as in Western Santa Catarina State, Brazil, where intensive swine production has caused large accumulations of manure and consequently water pollution. Natural resource scientists are asked by decision-makers for advice on management and regulatory decisions. Distributed environmental models are useful tools, since they can be used to explore consequences of various management practices. However, in many areas of the world, quantitative data for model calibration and validation are lacking. The data-intensive distributed environmental model AgNPS was applied in a data-poor environment, the upper catchment (2,520 ha) of the Ariranhazinho River, near the city of Seara, in Santa Catarina State. Steps included data preparation, cell size selection, sensitivity analysis, model calibration and application to different management scenarios. The model was calibrated based on a best guess for model parameters and on a pragmatic sensitivity analysis. The parameters were adjusted to match model outputs (runoff volume, peak runoff rate and sediment concentration) closely with the sparse observed data. A modelling grid cell resolution of 150 m adduced appropriate and computer-fit results. The rainfall runoff response of the AgNPS model was calibrated using three separate rainfall ranges (< 25, 25-60, > 60 mm). Predicted sediment concentrations were consistently six to ten times higher than observed, probably due to sediment trapping along vegetated channel banks. Predicted N and P concentrations in stream water ranged from just below to well above regulatory norms. Expert knowledge of the area, in addition to experience reported in the literature, was able to compensate in part for limited calibration data. Several scenarios (actual, recommended and excessive manure applications, and point source pollution from swine operations) could be compared by the model, using a relative ranking rather than quantitative predictions.