Biomedical subjects

J Chadoeuf

Publications and source records attributed to J Chadoeuf.

5 recordsLinked to original sources

PubMed2003

Constraints on adaptive mutations in the codling moth Cydia pomonella (L.): measuring fitness trade-offs and natural selection.

Adaptive changes in populations encountering a new environment are often constrained by deleterious pleiotropic interactions with ancestral physiological functions. Evolutionary responses of populations can thus be limited by natural selection under fluctuating environmental conditions, if the adaptive mutations are associated with pleiotropic fitness costs. In this context, we have followed the evolution of the frequencies of insecticide-resistant mutants of Cydia pomonella when reintroduced into an untreated environment. The novel set of selective forces after removal of insecticide pressure led to the decline of the frequencies of resistant phenotypes over time, suggesting that the insecticide-adapted genetic variants were selected against the absence of insecticide (with a selective coefficient estimated at 0.11). The selective coefficients were also estimated for both the major cytochrome P450-dependent monooxygenase (MFO) and the minor glutathione S-transferase (GST) systems (0.17 and negligible, respectively), which have been previously shown to be involved in resistance. The involvement of metabolic systems acting both through xenobiotic detoxification and biosynthetic pathways of endogenous compounds may be central to explaining the deleterious physiological consequences resulting from pleiotropy of adaptive changes. The estimation of the magnitude of the fitness cost associated with insecticide resistance in C. pomonella suggests that resistance management strategies exclusively based on insecticide alternations would be unlikely to delay such a selection process.

Animals↗

PubMed2002

A point pattern model of the spread of foot-and-mouth disease.

The spatial spread of foot-and-mouth disease (FMD) is influenced by several sources of spatial heterogeneity: heterogeneity of the exposure to the virus, heterogeneity of the animal density and heterogeneity of the networks formed by the contacts between farms. A discrete space model assuming that farms can be reduced to points is proposed to handle these different factors. The farm-to-farm process of transmission of the infection is studied using point-pattern methodology. Farm management, commercial exchanges, possible airborne transmission, etc. cannot be explicitly taken into account because of lack of data. These latter factors are introduced via surrogate variables such as herd size and distance between farms. The model is built on the calculation of an infectious potential for each farm. This method has been applied to the study of the 1967-1968 FMD epidemic in UK and allowed us to evaluate the spatial variation of the probability of infection during this epidemic. Maximum likelihood estimation has been conducted conditional on the absence of data concerning the farms which were not infected during the epidemic. Model parameters have then been tested using an approximated conditional-likelihood ratio test. In this case study, results and validation are limited by the lack of data, but this model can easily be extended to include other information such as the effect of wind direction and velocity on airborne spread of the virus or the complex interactions between the locations of farms and the herd size. It can also be applied to other diseases where point approximation is convenient. In the context of an increase of animal density in some areas, the model explicitly incorporates the density and known epidemiological characteristics (e.g. incubation period) in the calculation of the probability of FMD infection. Control measures such as vaccination or slaughter can be simply introduced, respectively, as a reduction of the susceptible population or as a reduction of the source of infection.

Animal Husbandry↗

PubMed2002

A stochastic flowering model describing an asynchronically flowering set of trees.

A general stochastic model is presented that simulates the time course of flowering of individual trees and populations, integrating the synchronization of flowering both between and within trees. Making some hypotheses, a simplified expression of the model, called the 'shoot' model, is proposed, in which the synchronization of flowering both between and within trees is characterized by specific parameters. Two derived models, the 'tree' model and the 'population' model, are presented. They neglect the asynchrony of flowering, respectively, within trees, and between and within trees. Models were fitted and tested using data on flowering of Psidium cattleianum observed at study sites at elevations of 200, 520 and 890 m in Reunion Island. The 'shoot' model fitted the data best and reproduced the strong irregularities in flowering shown by empirical data. The asynchrony of flowering in P. cattleianum was more pronounced within than between trees. Simulations showed that various flowering patterns can be reproduced by the 'shoot' model. The use of different levels of organization of the general model is discussed.

Computer Simulation↗

PubMed2001

Testing local independence between two point processes.

Dependencies between two types of points in a spatial point process can be due either to a real dependence between the two types or to the dependence on common underlying variables. We propose a global test for dependence between two point processes that is valid for a wide range of models. In contrast with previously proposed methods, it is based on a number of local test statistics, which makes it possible to map the local association between the two processes. The behavior of the test is evaluated by a simulation study. It is then applied to a vegetation pattern data set from Burkina Faso.

Burkina Faso↗

PubMed2000

Testing local dependence of spatial structures on images

Associations between two spatial processes can be due to a real dependence between the two processes or to the dependence on common underlying variables. We propose to test the existence of a real dependence by use of local tests, leading to a global test of real dependence and a map of local interactions. We present first how classical interaction tests based on random rotations between completely observed processes such as those developed by Berman (Berman. Appl. Statist. (1986) 35, 54-62), can be integrated in local analyses. For this purpose, tests are first performed locally, and the distribution of their p-values is then compared to the corresponding value under the null hypothesis. A similar approach is proposed to test non-stationarity of a point pattern by using distance statistics popularized by Diggle (Diggle. Statistical Analysis of Spatial Point Patterns. (1983) Academic Press, New York). The problem of testing the interaction between a random field and a censoring area pattern process is discussed and an approach similar to the preceding ones is then proposed. The methods are mainly applied to agricultural examples but they can be applied to any microscopical images for which one wishes to analyse the spatial structure.

Journal Article↗