Chapman College Child Study Center play area, Orange, California

Chapman College Child Study Center play area, Orange, California

Professor Fred Smoller, Child Study Center, Chapman College, Orange, California

Professor Fred Smoller, Child Study Center, Chapman College, Orange, California, June, 1990.

Child Study Center, Chapman College, Orange, California

Professor Fred Smoller, Child Study Center, Chapman College, Orange, California, June, 1990.

Application of agent-based modeling to the study of gender stereotypes

Gender stereotypes are sets of characteristics that people believe to be typically true of a man or woman. We report an agent-based model (ABM) that simulates how stereotypes disseminate in a group through associative mechanisms. The model consists of agents that carry one of several different versions of a stereotype, which share part of their conceptual content. When an agent acts according to his/her stereotype, and that stereotype is shared by an observer, then the latter’s stereotype strengthens. Contrarily, if the agent does not act according to his/ her stereotype, then the observer’s stereotype weakens. In successive interactions, agents develop preferences, such that there will be a higher probability of interaction with agents that confirm their stereotypes. Depending on the proportion of shared conceptual content in the stereotype’s different versions, three dynamics emerge: all stereotypes in the population strengthen, all weaken, or a bifurcation occurs, i.e., some strengthen and some weaken. Additionally, we discuss the use of agent-based modeling to study social phenomena and the practical consequences that the model’s results might have on stereotype research and their effects on a community

Intestinal microbiology in Crohn's disease: a study of Escherichia coli as a potential etiologic agent

La malaltia de Crohn és una malaltia inflamatòria intestinal crònica d'etiologia encara desconeguda. Actualment es pensa que hi participen factors genètics i immunològics que confereixen una susceptibilitat a l'hoste, i factors externs o ambientals, com serien els microorganismes i/o l'estil de vida. L'objectiu principal d'aquest treball ha estat descriure les poblacions bacterianes associades especialment als malalts de Crohn, amb la intenció d'identificar possibles agents etiològics. Els resultats d'aquest treball coincideixen amb investigacions prèvies que descriuen l'alteració bacteriana present en els malalts de Crohn (disbiosi) i recolzen la hipòtesi que implica el recentment descrit patovar "Adherent- Invasive Escherichia coli" (AIEC) en l'etiologia d'aquesta malaltia inflamatòria intestinal. A més, contribuïm a la descripció de les poblacions d'E. coli associades a la mucosa intestinal aportant dades sobre aspectes ecològics i patogènics. Finalment, descrivim nous aspectes fenotípics d'AIEC que podrien estar relacionats amb la seva patogènia, com seria la capacitat de formar biofilms.

Implementation of a Bayesian design in a dose-escalation study of an experimental agent in healthy volunteers

Bayesian decision procedures have recently been developed for dose escalation in phase I clinical trials concerning pharmacokinetic responses observed in healthy volunteers. This article describes how that general methodology was extended and evaluated for implementation in a specific phase I trial of a novel compound. At the time of writing, the study is ongoing, and it will be some time before the sponsor will wish to put the results into the public domain. This article is an account of how the study was designed in a way that should prove to be safe, accurate, and efficient whatever the true nature of the compound. The study involves the observation of two pharmacokinetic endpoints relating to the plasma concentration of the compound itself and of a metabolite as well as a safety endpoint relating to the occurrence of adverse events. Construction of the design and its evaluation via simulation are presented.

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species.