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Dive into the research topics where André Kobilinsky is active.

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Featured researches published by André Kobilinsky.


Applied and Environmental Microbiology | 2006

Construction and analysis of fractional multifactorial designs to study attachment strength and transfer of Listeria monocytogenes from pure or mixed biofilms after contact with a solid model food.

Graziella Midelet; André Kobilinsky; Brigitte Carpentier

ABSTRACT The aim of this study was to establish which of seven factors influence the adhesion strength and hence bacterial transfer between biofilms containing Listeria monocytogenes (pure and two-species biofilms) and tryptone soya agar (TSA) as a solid organic surface. The two-species biofilms were made of L. monocytogenes and one of the following species of bacteria: the nonpathogenic organisms Kocuria varians, Pseudomonas fluorescens, and Staphylococcus sciuri and CCL 63, an unidentified gram-negative bacterium isolated from the processing plant environment. We used biofilms prepared under conditions simulating open surfaces in meat-processing sites. The biofilms adhesion strength and population were evaluated by making 12 contacts on a given whole biofilm (4.5 cm2), using a new slice of a sterilized TSA cylinder for each contact, and plotting the logarithm CFU · cm−2 detached by each contact against the contact number. Three types of detachment kinetics were observed: biphasic kinetics, where the first slope may be either positive or negative, and monophasic kinetics. The bacteria that resisted a chlorinated alkaline product and a glutaraldehyde- and quaternary ammonium-based disinfectant had greater adhesion strengths than those determined for untreated biofilms. One of the four non-Listeria strains studied, Kocuria varians CCL 56, favored both the attachment and detachment of L. monocytogenes. The stainless steel had smaller bacterial populations than polymer materials, and non-Listeria bacteria adhered to it less strongly. Our results helped to evaluate measures aimed at controlling the immediate risk, linked to the presence of a large number of CFU in a foodstuff, and the delayed risk, linked to the persistence of L. monocytogenes and the occurrence of slightly contaminated foods that may become dangerous if L. monocytogenes multiplies during storage. Cleaning and disinfection reduce the immediate risk, while reducing the delayed risk should be achieved by lowering the adhesion strength, which the sanitizers used here cannot do at low concentrations.


Analytical Biochemistry | 2008

Detection of nonauthorized genetically modified organisms using differential quantitative polymerase chain reaction: application to 35S in maize

Katarina Cankar; Valérie Chauvensy-Ancel; Marie-Noelle Fortabat; Kristina Gruden; André Kobilinsky; Jana Žel; Yves Bertheau

Detection of nonauthorized genetically modified organisms (GMOs) has always presented an analytical challenge because the complete sequence data needed to detect them are generally unavailable although sequence similarity to known GMOs can be expected. A new approach, differential quantitative polymerase chain reaction (PCR), for detection of nonauthorized GMOs is presented here. This method is based on the presence of several common elements (e.g., promoter, genes of interest) in different GMOs. A statistical model was developed to study the difference between the number of molecules of such a common sequence and the number of molecules identifying the approved GMO (as determined by border-fragment-based PCR) and the donor organism of the common sequence. When this difference differs statistically from zero, the presence of a nonauthorized GMO can be inferred. The interest and scope of such an approach were tested on a case study of different proportions of genetically modified maize events, with the P35S promoter as the Cauliflower Mosaic Virus common sequence. The presence of a nonauthorized GMO was successfully detected in the mixtures analyzed and in the presence of (donor organism of P35S promoter). This method could be easily transposed to other common GMO sequences and other species and is applicable to other detection areas such as microbiology.


Computational Statistics & Data Analysis | 2005

Model-robust and model-sensitive designs

Peter Goos; André Kobilinsky; Timothy E. O'Brien; Martina Vandebroek

The main drawback of the optimal design approach is that it assumes the statistical model is known. To overcome this problem, a new approach to reduce the dependency on the assumed model is proposed. The approach takes into account the model uncertainty by incorporating the bias in the design criterion and the ability to test for lack-of-fit. Several new designs are derived and compared to the alternatives available from the literature.


Linear Algebra and its Applications | 1985

Confounding in relation to duality of finite abelian groups

André Kobilinsky

Abstract Using the duality in the theory of finite abelian groups, we give a precise description of confounded effects in fractional factorial design, when the fraction is a subgroup or a coset of a subgroup. The result works for a confounded block design, considered here as a fraction of a bigger design with complete blocks.


Linear Algebra and its Applications | 1990

Complex linear models and cyclic designs

André Kobilinsky

Abstract Many orthogonal factorial designs can be defined by abelian group morphisms. By juxtaposition of such designs, useful nonorthogonal designs can also be obtained, including the classical generalized cyclic designs, as well as a new kind of one replicate factorial block designs. Their efficiencies are easily computed by means of a complex reparametrization based on the irreducible characters of the groups involved. The theory extends to the “group generated” designs defined by Bailey and Rowley, in which the group is not necessarily abelian. In some cases, we give explicit formulas for the efficiencies of these latter designs.


Linear Algebra and its Applications | 2000

Reparametrisation of interest in non-uniform factorial designs

André Kobilinsky

Abstract A definition of factorial effects relying on the treatment structure defined by the hierarchies is proposed. It applies to a non-uniform situation, where the number of levels of a nested factor within the classes defined by each set of levels of its nesting factors may vary. A reparametrisation whose parameters belongs to these factorial effects is obtained. The development is based on the notion of reference treatment design, a conceptual design that can be used as a basis of comparison to assess the properties of any factorial design.


Trends in Food Science and Technology | 2007

Trends in analytical methodology in food safety and quality: monitoring microorganisms and genetically modified organisms

David Rodríguez-Lázaro; Bertrand Lombard; Huw Smith; Artur Rzeżutka; Martin D'Agostino; Reiner Helmuth; Andreas Schroeter; Burkhard Malorny; Angelika Miko; Beatriz Guerra; John Davison; André Kobilinsky; Marta Hernández; Yves Bertheau; Nigel Cook


Journal of AOAC International | 2002

Detection Methods and Performance Criteria for Genetically Modified Organisms

Yves Bertheau; Annick Diolez; André Kobilinsky; Kimberly Magin


Aquaculture | 2007

Simultaneous effects of nutritional and environmental factors on growth and flesh quality of Perca fluviatilis using a fractional factorial design study

Jean-Noël Gardeur; Nicolas Mathis; André Kobilinsky; Jean Brun-Bellut


Journal of AOAC International | 2005

Detection of genetically modified corn (Bt176) in spiked cow blood samples by polymerase chain reaction and immunoassay methods

Laetitia Petit; Fabienne Baraige; Yves Bertheau; Philippe Brunschwig; Annick Diolez; Koenraad Duhem; Marie-Noëlle Duplan; Patrick Fach; André Kobilinsky; Stephen Lamart; Alexandra Schattner; Patrice Martin

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Yves Bertheau

Institut national de la recherche agronomique

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John Davison

Institut national de la recherche agronomique

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Martina Vandebroek

Katholieke Universiteit Leuven

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Colette Audeon

Institut national de la recherche agronomique

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Dominique Brunel

Institut national de la recherche agronomique

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Gianni Bellocchi

Institut national de la recherche agronomique

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Graziella Midelet

Institut national de la recherche agronomique

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