Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Atrial septal pacing for the termination of atrial fibrillation: study in a biophysical model of human atria.

AIMS: While successful termination by pacing of organized atrial tachycardias has been observed in patients, single site rapid pacing has not yet led to conclusive results for the termination of atrial fibrillation (AF). The purpose of this study was to evaluate a novel atrial septal pacing algorithm for the termination of AF in a biophysical model of the human atria. METHODS AND RESULTS: Sustained AF was generated in a model based on human magnetic resonance images and membrane kinetics. Rapid pacing was applied from the septal area following a dual-stage scheme: (i) rapid pacing for 10-30 s at pacing intervals 62-70% of AF cycle length (AFCL), (ii) slow pacing for 1.5 s at 180% AFCL, initiated by a single stimulus at 130% AFCL. Atrial fibrillation termination success rates were computed. A mean success rate for AF termination of 10.2% was obtained for rapid septal pacing only. The addition of the slow pacing phase increased this rate to 20.2%. At an optimal pacing cycle length (64% AFCL) up to 29% of AF termination was observed. CONCLUSION: The proposed septal pacing algorithm could suppress AF reentries in a more robust way than classical single site rapid pacing. Experimental studies are now needed to determine whether similar termination mechanisms and rates can be observed in animals or humans, and in which types of AF this pacing strategy might be most effective.

A wearable system for multi-segment foot kinetics measurement.

This study aims to design a wearable system for kinetics measurement of multi-segment foot joints in long-distance walking and to investigate its suitability for clinical evaluations. The wearable system consisted of inertial sensors (3D gyroscopes and 3D accelerometers) on toes, forefoot, hindfoot, and shank, and a plantar pressure insole. After calibration in a laboratory, 10 healthy elderly subjects and 12 patients with ankle osteoarthritis walked 50m twice wearing this system. Using inverse dynamics, 3D forces, moments, and power were calculated in the joint sections among toes, forefoot, hindfoot, and shank. Compared to those we previously estimated for a one-segment foot model, the sagittal and transverse moments and power in the ankle joint, as measured via multi-segment foot model, showed a normalized RMS difference of less than 11%, 14%, and 13%, respectively, for healthy subjects, and 13%, 15%, and 14%, for patients. Similar to our previous study, the coronal moments were not analyzed. Maxima-minima values of anterior-posterior and vertical force, sagittal moment, and power in shank-hindfoot and hindfoot-forefoot joints were significantly different between patients and healthy subjects. Except for power, the inter-subject repeatability of these parameters was CMC>0.90 for healthy subjects and CMC>0.70 for patients. Repeatability of these parameters was lower for the forefoot-toes joint. The proposed measurement system estimated multi-segment foot joints kinetics with acceptable repeatability but showed difference, compared to those previously estimated for the one-segment foot model. These parameters also could distinguish patients from healthy subjects. Thus, this system is suggested for outcome evaluations of foot treatments.

A joint back calculation model for the imputation of the date of HIV infection in a prevalent cohort.

In studies of the natural history of HIV-1 infection, the time scale of primary interest is the time since infection. Unfortunately, this time is very often unknown for HIV infection and using the follow-up time instead of the time since infection is likely to provide biased results because of onset confounding. Laboratory markers such as the CD4 T-cell count carry important information concerning disease progression and can be used to predict the unknown date of infection. Previous work on this topic has made use of only one CD4 measurement or based the imputation on incident patients only. However, because of considerable intrinsic variability in CD4 levels and because incident cases are different from prevalent cases, back calculation based on only one CD4 determination per person or on characteristics of the incident sub-cohort may provide unreliable results. Therefore, we propose a methodology based on the repeated individual CD4 T-cells marker measurements that use both incident and prevalent cases to impute the unknown date of infection. Our approach uses joint modelling of the time since infection, the CD4 time path and the drop-out process. This methodology has been applied to estimate the CD4 slope and impute the unknown date of infection in HIV patients from the Swiss HIV Cohort Study. A procedure based on the comparison of different slope estimates is proposed to assess the goodness of fit of the imputation. Results of simulation studies indicated that the imputation procedure worked well, despite the intrinsic high volatility of the CD4 marker.

Essays on the measurement of school efficiency

Measuring school efficiency is a challenging task. First, a performance measurement technique has to be selected. Within Data Envelopment Analysis (DEA), one such technique, alternative models have been developed in order to deal with environmental variables. The majority of these models lead to diverging results. Second, the choice of input and output variables to be included in the efficiency analysis is often dictated by data availability. The choice of the variables remains an issue even when data is available. As a result, the choice of technique, model and variables is probably, and ultimately, a political judgement. Multi-criteria decision analysis methods can help the decision makers to select the most suitable model. The number of selection criteria should remain parsimonious and not be oriented towards the results of the models in order to avoid opportunistic behaviour. The selection criteria should also be backed by the literature or by an expert group. Once the most suitable model is identified, the principle of permanence of methods should be applied in order to avoid a change of practices over time. Within DEA, the two-stage model developed by Ray (1991) is the most convincing model which allows for an environmental adjustment. In this model, an efficiency analysis is conducted with DEA followed by an econometric analysis to explain the efficiency scores. An environmental variable of particular interest, tested in this thesis, consists of the fact that operations are held, for certain schools, on multiple sites. Results show that the fact of being located on more than one site has a negative influence on efficiency. A likely way to solve this negative influence would consist of improving the use of ICT in school management and teaching. Planning new schools should also consider the advantages of being located on a unique site, which allows reaching a critical size in terms of pupils and teachers. The fact that underprivileged pupils perform worse than privileged pupils has been public knowledge since Coleman et al. (1966). As a result, underprivileged pupils have a negative influence on school efficiency. This is confirmed by this thesis for the first time in Switzerland. Several countries have developed priority education policies in order to compensate for the negative impact of disadvantaged socioeconomic status on school performance. These policies have failed. As a result, other actions need to be taken. In order to define these actions, one has to identify the social-class differences which explain why disadvantaged children underperform. Childrearing and literary practices, health characteristics, housing stability and economic security influence pupil achievement. Rather than allocating more resources to schools, policymakers should therefore focus on related social policies. For instance, they could define pre-school, family, health, housing and benefits policies in order to improve the conditions for disadvantaged children.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Reliability of methods used for the risk assessment of mixture of micropollutants in aquatic enviromments : from theoretical concepts to field observations

Ces dernières années, de nombreuses recherches ont mis en évidence les effets toxiques des micropolluants organiques pour les espèces de nos lacs et rivières. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, alors que les organismes sont exposés tous les jours à des milliers de substances en mélange. Or les effets de ces cocktails ne sont pas négligeables. Cette thèse de doctorat s'est ainsi intéressée aux modèles permettant de prédire le risque environnemental de ces cocktails pour le milieu aquatique. Le principal objectif a été d'évaluer le risque écologique des mélanges de substances chimiques mesurées dans le Léman, mais aussi d'apporter un regard critique sur les méthodologies utilisées afin de proposer certaines adaptations pour une meilleure estimation du risque. Dans la première partie de ce travail, le risque des mélanges de pesticides et médicaments pour le Rhône et pour le Léman a été établi en utilisant des approches envisagées notamment dans la législation européenne. Il s'agit d'approches de « screening », c'est-à-dire permettant une évaluation générale du risque des mélanges. Une telle approche permet de mettre en évidence les substances les plus problématiques, c'est-à-dire contribuant le plus à la toxicité du mélange. Dans notre cas, il s'agit essentiellement de 4 pesticides. L'étude met également en évidence que toutes les substances, même en trace infime, contribuent à l'effet du mélange. Cette constatation a des implications en terme de gestion de l'environnement. En effet, ceci implique qu'il faut réduire toutes les sources de polluants, et pas seulement les plus problématiques. Mais l'approche proposée présente également un biais important au niveau conceptuel, ce qui rend son utilisation discutable, en dehors d'un screening, et nécessiterait une adaptation au niveau des facteurs de sécurité employés. Dans une deuxième partie, l'étude s'est portée sur l'utilisation des modèles de mélanges dans le calcul de risque environnemental. En effet, les modèles de mélanges ont été développés et validés espèce par espèce, et non pour une évaluation sur l'écosystème en entier. Leur utilisation devrait donc passer par un calcul par espèce, ce qui est rarement fait dû au manque de données écotoxicologiques à disposition. Le but a été donc de comparer, avec des valeurs générées aléatoirement, le calcul de risque effectué selon une méthode rigoureuse, espèce par espèce, avec celui effectué classiquement où les modèles sont appliqués sur l'ensemble de la communauté sans tenir compte des variations inter-espèces. Les résultats sont dans la majorité des cas similaires, ce qui valide l'approche utilisée traditionnellement. En revanche, ce travail a permis de déterminer certains cas où l'application classique peut conduire à une sous- ou sur-estimation du risque. Enfin, une dernière partie de cette thèse s'est intéressée à l'influence que les cocktails de micropolluants ont pu avoir sur les communautés in situ. Pour ce faire, une approche en deux temps a été adoptée. Tout d'abord la toxicité de quatorze herbicides détectés dans le Léman a été déterminée. Sur la période étudiée, de 2004 à 2009, cette toxicité due aux herbicides a diminué, passant de 4% d'espèces affectées à moins de 1%. Ensuite, la question était de savoir si cette diminution de toxicité avait un impact sur le développement de certaines espèces au sein de la communauté des algues. Pour ce faire, l'utilisation statistique a permis d'isoler d'autres facteurs pouvant avoir une influence sur la flore, comme la température de l'eau ou la présence de phosphates, et ainsi de constater quelles espèces se sont révélées avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps. Fait intéressant, une partie d'entre-elles avait déjà montré des comportements similaires dans des études en mésocosmes. En conclusion, ce travail montre qu'il existe des modèles robustes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques, et qu'ils peuvent être utilisés pour expliquer le rôle des substances dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application. - Depuis plusieurs années, les risques que posent les micropolluants organiques pour le milieu aquatique préoccupent grandement les scientifiques ainsi que notre société. En effet, de nombreuses recherches ont mis en évidence les effets toxiques que peuvent avoir ces substances chimiques sur les espèces de nos lacs et rivières, quand elles se retrouvent exposées à des concentrations aiguës ou chroniques. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, c'est à dire considérées séparément. Actuellement, il en est de même dans les procédures de régulation européennes, concernant la partie évaluation du risque pour l'environnement d'une substance. Or, les organismes sont exposés tous les jours à des milliers de substances en mélange, et les effets de ces "cocktails" ne sont pas négligeables. L'évaluation du risque écologique que pose ces mélanges de substances doit donc être abordé par de la manière la plus appropriée et la plus fiable possible. Dans la première partie de cette thèse, nous nous sommes intéressés aux méthodes actuellement envisagées à être intégrées dans les législations européennes pour l'évaluation du risque des mélanges pour le milieu aquatique. Ces méthodes sont basées sur le modèle d'addition des concentrations, avec l'utilisation des valeurs de concentrations des substances estimées sans effet dans le milieu (PNEC), ou à partir des valeurs des concentrations d'effet (CE50) sur certaines espèces d'un niveau trophique avec la prise en compte de facteurs de sécurité. Nous avons appliqué ces méthodes à deux cas spécifiques, le lac Léman et le Rhône situés en Suisse, et discuté les résultats de ces applications. Ces premières étapes d'évaluation ont montré que le risque des mélanges pour ces cas d'étude atteint rapidement une valeur au dessus d'un seuil critique. Cette valeur atteinte est généralement due à deux ou trois substances principales. Les procédures proposées permettent donc d'identifier les substances les plus problématiques pour lesquelles des mesures de gestion, telles que la réduction de leur entrée dans le milieu aquatique, devraient être envisagées. Cependant, nous avons également constaté que le niveau de risque associé à ces mélanges de substances n'est pas négligeable, même sans tenir compte de ces substances principales. En effet, l'accumulation des substances, même en traces infimes, atteint un seuil critique, ce qui devient plus difficile en terme de gestion du risque. En outre, nous avons souligné un manque de fiabilité dans ces procédures, qui peuvent conduire à des résultats contradictoires en terme de risque. Ceci est lié à l'incompatibilité des facteurs de sécurité utilisés dans les différentes méthodes. Dans la deuxième partie de la thèse, nous avons étudié la fiabilité de méthodes plus avancées dans la prédiction de l'effet des mélanges pour les communautés évoluant dans le système aquatique. Ces méthodes reposent sur le modèle d'addition des concentrations (CA) ou d'addition des réponses (RA) appliqués sur les courbes de distribution de la sensibilité des espèces (SSD) aux substances. En effet, les modèles de mélanges ont été développés et validés pour être appliqués espèce par espèce, et non pas sur plusieurs espèces agrégées simultanément dans les courbes SSD. Nous avons ainsi proposé une procédure plus rigoureuse, pour l'évaluation du risque d'un mélange, qui serait d'appliquer d'abord les modèles CA ou RA à chaque espèce séparément, et, dans une deuxième étape, combiner les résultats afin d'établir une courbe SSD du mélange. Malheureusement, cette méthode n'est pas applicable dans la plupart des cas, car elle nécessite trop de données généralement indisponibles. Par conséquent, nous avons comparé, avec des valeurs générées aléatoirement, le calcul de risque effectué selon cette méthode plus rigoureuse, avec celle effectuée traditionnellement, afin de caractériser la robustesse de cette approche qui consiste à appliquer les modèles de mélange sur les courbes SSD. Nos résultats ont montré que l'utilisation de CA directement sur les SSDs peut conduire à une sous-estimation de la concentration du mélange affectant 5 % ou 50% des espèces, en particulier lorsque les substances présentent un grand écart- type dans leur distribution de la sensibilité des espèces. L'application du modèle RA peut quant à lui conduire à une sur- ou sous-estimations, principalement en fonction de la pente des courbes dose- réponse de chaque espèce composant les SSDs. La sous-estimation avec RA devient potentiellement importante lorsque le rapport entre la EC50 et la EC10 de la courbe dose-réponse des espèces est plus petit que 100. Toutefois, la plupart des substances, selon des cas réels, présentent des données d' écotoxicité qui font que le risque du mélange calculé par la méthode des modèles appliqués directement sur les SSDs reste cohérent et surestimerait plutôt légèrement le risque. Ces résultats valident ainsi l'approche utilisée traditionnellement. Néanmoins, il faut garder à l'esprit cette source d'erreur lorsqu'on procède à une évaluation du risque d'un mélange avec cette méthode traditionnelle, en particulier quand les SSD présentent une distribution des données en dehors des limites déterminées dans cette étude. Enfin, dans la dernière partie de cette thèse, nous avons confronté des prédictions de l'effet de mélange avec des changements biologiques observés dans l'environnement. Dans cette étude, nous avons utilisé des données venant d'un suivi à long terme d'un grand lac européen, le lac Léman, ce qui offrait la possibilité d'évaluer dans quelle mesure la prédiction de la toxicité des mélanges d'herbicide expliquait les changements dans la composition de la communauté phytoplanctonique. Ceci à côté d'autres paramètres classiques de limnologie tels que les nutriments. Pour atteindre cet objectif, nous avons déterminé la toxicité des mélanges sur plusieurs années de 14 herbicides régulièrement détectés dans le lac, en utilisant les modèles CA et RA avec les courbes de distribution de la sensibilité des espèces. Un gradient temporel de toxicité décroissant a pu être constaté de 2004 à 2009. Une analyse de redondance et de redondance partielle, a montré que ce gradient explique une partie significative de la variation de la composition de la communauté phytoplanctonique, même après avoir enlevé l'effet de toutes les autres co-variables. De plus, certaines espèces révélées pour avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps, ont montré des comportements similaires dans des études en mésocosmes. On peut en conclure que la toxicité du mélange herbicide est l'un des paramètres clés pour expliquer les changements de phytoplancton dans le lac Léman. En conclusion, il existe diverses méthodes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques et celui-ci peut jouer un rôle dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application, avant d'utiliser leurs résultats pour la gestion des risques environnementaux. - For several years now, the scientists as well as the society is concerned by the aquatic risk organic micropollutants may pose. Indeed, several researches have shown the toxic effects these substances may induce on organisms living in our lakes or rivers, especially when they are exposed to acute or chronic concentrations. However, most of the studies focused on the toxicity of single compounds, i.e. considered individually. The same also goes in the current European regulations concerning the risk assessment procedures for the environment of these substances. But aquatic organisms are typically exposed every day simultaneously to thousands of organic compounds. The toxic effects resulting of these "cocktails" cannot be neglected. The ecological risk assessment of mixtures of such compounds has therefore to be addressed by scientists in the most reliable and appropriate way. In the first part of this thesis, the procedures currently envisioned for the aquatic mixture risk assessment in European legislations are described. These methodologies are based on the mixture model of concentration addition and the use of the predicted no effect concentrations (PNEC) or effect concentrations (EC50) with assessment factors. These principal approaches were applied to two specific case studies, Lake Geneva and the River Rhône in Switzerland, including a discussion of the outcomes of such applications. These first level assessments showed that the mixture risks for these studied cases exceeded rapidly the critical value. This exceeding is generally due to two or three main substances. The proposed procedures allow therefore the identification of the most problematic substances for which management measures, such as a reduction of the entrance to the aquatic environment, should be envisioned. However, it was also showed that the risk levels associated with mixtures of compounds are not negligible, even without considering these main substances. Indeed, it is the sum of the substances that is problematic, which is more challenging in term of risk management. Moreover, a lack of reliability in the procedures was highlighted, which can lead to contradictory results in terms of risk. This result is linked to the inconsistency in the assessment factors applied in the different methods. In the second part of the thesis, the reliability of the more advanced procedures to predict the mixture effect to communities in the aquatic system were investigated. These established methodologies combine the model of concentration addition (CA) or response addition (RA) with species sensitivity distribution curves (SSD). Indeed, the mixture effect predictions were shown to be consistent only when the mixture models are applied on a single species, and not on several species simultaneously aggregated to SSDs. Hence, A more stringent procedure for mixture risk assessment is proposed, that would be to apply first the CA or RA models to each species separately and, in a second step, to combine the results to build an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases, because it requires large data sets usually not available. Therefore, the differences between the two methodologies were studied with datasets created artificially to characterize the robustness of the traditional approach applying models on species sensitivity distribution. The results showed that the use of CA on SSD directly might lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation of the distribution from the sensitivity of the species. The application of RA can lead to over- or underestimates, depending mainly on the slope of the dose-response curves of the individual species. The potential underestimation with RA becomes important when the ratio between the EC50 and the EC10 for the dose-response curve of the species composing the SSD are smaller than 100. However, considering common real cases of ecotoxicity data for substances, the mixture risk calculated by the methodology applying mixture models directly on SSDs remains consistent and would rather slightly overestimate the risk. These results can be used as a theoretical validation of the currently applied methodology. Nevertheless, when assessing the risk of mixtures, one has to keep in mind this source of error with this classical methodology, especially when SSDs present a distribution of the data outside the range determined in this study Finally, in the last part of this thesis, we confronted the mixture effect predictions with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated, using concentration addition and response addition models. A decreasing temporal gradient of toxicity was observed from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition, even when having removed the effect of all other co-variables. Moreover, some species that were revealed to be influenced positively or negatively, by the decrease of toxicity in the lake over time, showed similar behaviors in mesocosms studies. It could be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva. To conclude, different methods exist to predict the risk of mixture in the ecosystems. But their reliability varies depending on the underlying hypotheses. One should therefore carefully consider these hypotheses, as well as the limits of the approaches, before using the results for environmental risk management

Monte Carlo simulation of a whole-body counter using IGOR phantoms.

Whole-body counting is a technique of choice for assessing the intake of gamma-emitting radionuclides. An appropriate calibration is necessary, which is done either by experimental measurement or by Monte Carlo (MC) calculation. The aim of this work was to validate a MC model for calibrating whole-body counters (WBCs) by comparing the results of computations with measurements performed on an anthropomorphic phantom and to investigate the effect of a change in phantom's position on the WBC counting sensitivity. GEANT MC code was used for the calculations, and an IGOR phantom loaded with several types of radionuclides was used for the experimental measurements. The results show a reasonable agreement between measurements and MC computation. A 1-cm error in phantom positioning changes the activity estimation by >2%. Considering that a 5-cm deviation of the positioning of the phantom may occur in a realistic counting scenario, this implies that the uncertainty of the activity measured by a WBC is ∼10-20%.

The handaxe and the microscope: individual and social learning in a multidimensional model of adaptation

When individuals learn by trial-and-error, they perform randomly chosen actions and then reinforce those actions that led to a high payoff. However, individuals do not always have to physically perform an action in order to evaluate its consequences. Rather, they may be able to mentally simulate actions and their consequences without actually performing them. Such fictitious learners can select actions with high payoffs without making long chains of trial-and-error learning. Here, we analyze the evolution of an n-dimensional cultural trait (or artifact) by learning, in a payoff landscape with a single optimum. We derive the stochastic learning dynamics of the distance to the optimum in trait space when choice between alternative artifacts follows the standard logit choice rule. We show that for both trial-and-error and fictitious learners, the learning dynamics stabilize at an approximate distance of root n/(2 lambda(e)) away from the optimum, where lambda(e) is an effective learning performance parameter depending on the learning rule under scrutiny. Individual learners are thus unlikely to reach the optimum when traits are complex (n large), and so face a barrier to further improvement of the artifact. We show, however, that this barrier can be significantly reduced in a large population of learners performing payoff-biased social learning, in which case lambda(e) becomes proportional to population size. Overall, our results illustrate the effects of errors in learning, levels of cognition, and population size for the evolution of complex cultural traits. (C) 2013 Elsevier Inc. All rights reserved.

Characterization of cerebral glucose dynamics in vivo with a four-state conformational model of transport at the blood-brain barrier.

Determination of brain glucose transport kinetics in vivo at steady-state typically does not allow distinguishing apparent maximum transport rate (T(max)) from cerebral consumption rate. Using a four-state conformational model of glucose transport, we show that simultaneous dynamic measurement of brain and plasma glucose concentrations provide enough information for independent and reliable determination of the two rates. In addition, although dynamic glucose homeostasis can be described with a reversible Michaelis-Menten model, which is implicit to the large iso-inhibition constant (K(ii)) relative to physiological brain glucose content, we found that the apparent affinity constant (K(t)) was better determined with the four-state conformational model of glucose transport than with any of the other models tested. Furthermore, we confirmed the utility of the present method to determine glucose transport and consumption by analysing the modulation of both glucose transport and consumption by anaesthesia conditions that modify cerebral activity. In particular, deep thiopental anaesthesia caused a significant reduction of both T(max) and cerebral metabolic rate for glucose consumption. In conclusion, dynamic measurement of brain glucose in vivo in function of plasma glucose allows robust determination of both glucose uptake and consumption kinetics.

Computer Aided Detection and measurement of peripheral artery disease.

Computer-Aided Tomography Angiography (CTA) images are the standard for assessing Peripheral artery disease (PAD). This paper presents a Computer Aided Detection (CAD) and Computer Aided Measurement (CAM) system for PAD. The CAD stage detects the arterial network using a 3D region growing method and a fast 3D morphology operation. The CAM stage aims to accurately measure the artery diameters from the detected vessel centerline, compensating for the partial volume effect using Expectation Maximization (EM) and a Markov Random field (MRF). The system has been evaluated on phantom data and also applied to fifteen (15) CTA datasets, where the detection accuracy of stenosis was 88% and the measurement accuracy was with an 8% error.

Selective inhibition of JNK with a peptide inhibitor attenuates pain hypersensitivity and tumor growth in a mouse skin cancer pain model.

Cancer pain significantly affects the quality of cancer patients, and current treatments for this pain are limited. C-Jun N-terminal kinase (JNK) has been implicated in tumor growth and neuropathic pain sensitization. We investigated the role of JNK in cancer pain and tumor growth in a skin cancer pain model. Injection of luciferase-transfected B16-Fluc melanoma cells into a hindpaw of mouse induced robust tumor growth, as indicated by increase in paw volume and fluorescence intensity. Pain hypersensitivity in this model developed rapidly (<5 days) and reached a peak in 2 weeks, and was characterized by mechanical allodynia and heat hyperalgesia. Tumor growth was associated with JNK activation in tumor mass, dorsal root ganglion (DRG), and spinal cord and a peripheral neuropathy, such as loss of nerve fibers in the hindpaw skin and induction of ATF-3 expression in DRG neurons. Repeated systemic injections of D-JNKI-1 (6 mg/kg, i.p.), a selective and cell-permeable peptide inhibitor of JNK, produced an accumulative inhibition of mechanical allodynia and heat hyperalgesia. A bolus spinal injection of D-JNKI-1 also inhibited mechanical allodynia. Further, JNK inhibition suppressed tumor growth in vivo and melanoma cell proliferation in vitro. In contrast, repeated injections of morphine (5 mg/kg), a commonly used analgesic for terminal cancer, produced analgesic tolerance after 1 day and did not inhibit tumor growth. Our data reveal a marked peripheral neuropathy in this skin cancer model and important roles of the JNK pathway in cancer pain development and tumor growth. JNK inhibitors such as D-JNKI-1 may be used to treat cancer pain.

A numeric model to simulate solar individual ultraviolet exposure.

Exposure to solar ultraviolet (UV) light is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors. Individual exposure data remain scarce and development of alternative assessment methods is greatly needed. We developed a model simulating human exposure to solar UV. The model predicts the dose and distribution of UV exposure received on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop a rendering engine that estimates the solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by each triangle was calculated, taking into account reflected, direct and diffuse radiation, and shading from other body parts. Dosimetric measurements (n = 54) were conducted in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model provides a tool to assess outdoor occupational and recreational UV exposures, without necessitating time-consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research.

Silene as a model system in ecology and evolution.

The genus Silene, studied by Darwin, Mendel and other early scientists, is re-emerging as a system for studying interrelated questions in ecology, evolution and developmental biology. These questions include sex chromosome evolution, epigenetic control of sex expression, genomic conflict and speciation. Its well-studied interactions with the pathogen Microbotryum has made Silene a model for the evolution and dynamics of disease in natural systems, and its interactions with herbivores have increased our understanding of multi-trophic ecological processes and the evolution of invasiveness. Molecular tools are now providing new approaches to many of these classical yet unresolved problems, and new progress is being made through combining phylogenetic, genomic and molecular evolutionary studies with ecological and phenotypic data.

Textural controls on induced polarization and permeability in granular media

The spatial resolution visualized with hydrological models and the conceptualized images of subsurface hydrological processes often exceed resolution of the data collected with classical instrumentation at the field scale. In recent years it was possible to increasingly diminish the inherent gap to information from point like field data through the application of hydrogeophysical methods at field-scale. With regards to all common geophysical exploration techniques, electric and electromagnetic methods have arguably to greatest sensitivity to hydrologically relevant parameters. Of particular interest in this context are induced polarisation (IP) measurements, which essentially constrain the capacity of a probed subsurface region to store an electrical charge. In the absence of metallic conductors the IP- response is largely driven by current conduction along the grain surfaces. This offers the perspective to link such measurements to the characteristics of the solid-fluid-interface and thus, at least in unconsolidated sediments, should allow for first-order estimates of the permeability structure.¦While the IP-effect is well explored through laboratory experiments and in part verified through field data for clay-rich environments, the applicability of IP-based characterizations to clay-poor aquifers is not clear. For example, polarization mechanisms like membrane polarization are not applicable in the rather wide pore-systems of clay free sands, and the direct transposition of Schwarz' theory relating polarization of spheres to the relaxation mechanism of polarized cells to complex natural sediments yields ambiguous results.¦In order to improve our understanding of the structural origins of IP-signals in such environments as well as their correlation with pertinent hydrological parameters, various laboratory measurements have been conducted. We consider saturated quartz samples with a grain size spectrum varying from fine sand to fine gravel, that is grain diameters between 0,09 and 5,6 mm, as well as corresponding pertinent mixtures which can be regarded as proxies for widespread alluvial deposits. The pore space characteristics are altered by changing (i) the grain size spectra, (ii) the degree of compaction, and (iii) the level of sorting. We then examined how these changes affect the SIP response, the hydraulic conductivity, and the specific surface area of the considered samples, while keeping any electrochemical variability during the measurements as small as possible. The results do not follow simple assumptions on relationships to single parameters such as grain size. It was found that the complexity of natural occurring media is not yet sufficiently represented when modelling IP. At the same time simple correlation to permeability was found to be strong and consistent. Hence, adaptations with the aim of better representing the geo-structure of natural porous media were applied to the simplified model space used in Schwarz' IP-effect-theory. The resulting semi- empiric relationship was found to more accurately predict the IP-effect and its relation to the parameters grain size and permeability. If combined with recent findings about the effect of pore fluid electrochemistry together with advanced complex resistivity tomography, these results will allow us to picture diverse aspects of the subsurface with relative certainty. Within the framework of single measurement campaigns, hydrologiste can than collect data with information about the geo-structure and geo-chemistry of the subsurface. However, additional research efforts will be necessary to further improve the understanding of the physical origins of IP-effect and minimize the potential for false interpretations.¦-¦Dans l'étude des processus et caractéristiques hydrologiques des subsurfaces, la résolution spatiale donnée par les modèles hydrologiques dépasse souvent la résolution des données du terrain récoltées avec des méthodes classiques d'hydrologie. Récemment il est possible de réduire de plus en plus cet divergence spatiale entre modèles numériques et données du terrain par l'utilisation de méthodes géophysiques, notamment celles géoélectriques. Parmi les méthodes électriques, la polarisation provoquée (PP) permet de représenter la capacité des roches poreuses et des sols à stocker une charge électrique. En l'absence des métaux dans le sous-sol, cet effet est largement influencé par des caractéristiques de surface des matériaux. En conséquence les mesures PP offrent une information des interfaces entre solides et fluides dans les matériaux poreux que nous pouvons lier à la perméabilité également dirigée par ces mêmes paramètres. L'effet de la polarisation provoquée à été étudié dans différentes études de laboratoire, ainsi que sur le terrain. A cause d'une faible capacité de polarisation des matériaux sableux, comparé aux argiles, leur caractérisation par l'effet-PP reste difficile a interpréter d'une manière cohérente pour les environnements hétérogènes.¦Pour améliorer les connaissances sur l'importance de la structure du sous-sol sableux envers l'effet PP et des paramètres hydrologiques, nous avons fait des mesures de laboratoire variées. En détail, nous avons considéré des échantillons sableux de quartz avec des distributions de taille de grain entre sables fins et graviers fins, en diamètre cela fait entre 0,09 et 5,6 mm. Les caractéristiques de l'espace poreux sont changées en modifiant (i) la distribution de taille des grains, (ii) le degré de compaction, et (iii) le niveau d'hétérogénéité dans la distribution de taille de grains. En suite nous étudions comment ces changements influencent l'effet-PP, la perméabilité et la surface spécifique des échantillons. Les paramètres électrochimiques sont gardés à un minimum pendant les mesures. Les résultats ne montrent pas de relation simple entre les paramètres pétro-physiques comme par exemples la taille des grains. La complexité des media naturels n'est pas encore suffisamment représenté par les modèles des processus PP. Néanmoins, la simple corrélation entre effet PP et perméabilité est fort et consistant. En conséquence la théorie de Schwarz sur l'effet-PP a été adapté de manière semi-empirique pour mieux pouvoir estimer la relation entre les résultats de l'effet-PP et les paramètres taille de graines et perméabilité. Nos résultats concernant l'influence de la texture des matériaux et celles de l'effet de l'électrochimie des fluides dans les pores, permettront de visualiser des divers aspects du sous-sol. Avec des telles mesures géo-électriques, les hydrologues peuvent collectionner des données contenant des informations sur la structure et la chimie des fluides des sous-sols. Néanmoins, plus de recherches sur les origines physiques de l'effet-PP sont nécessaires afin de minimiser le risque potentiel d'une mauvaise interprétation des données.