Intitulé du projet
TRout adipose tissues Imaging and Dynamics: Analysis and Numerical approaches
Nature du financement
PEPR
État du projet
Soumis
Année de soumission
2026
Programme / appel + année
PEPR MathVives AAP 2026
Equipe(s) impliquée(s) dans le projet
Dynenvie
Coordinateur·trice (nom et prénom)
Audebert Chloé et Bugeon Jérôme
Rôle de MaIAGE dans le projet
Responsable de Work Package
Nom(s) du(des) participant(s) - MaIAGE
L. Sala
Nom(s) du(des) partenaire(s) (nom, labo et localisation) - Hors MaIAGE
C. Audebert, H. Soula - Sorbonne Université; M. Ribot - Université d'Orleans; J. Bugeon, I. Hue, A. Brathonne, M. Thomas - LPGP - INRAE Rennes; R. Yvinec - BIOS - INRAE Nouzilly
Date de début du projet
Date de fin du projet
Résumé
The TRIDAN project explores the dynamics and regulation of white adipose tissues in female trout, focusing on how subcutaneous and visceral fat depots evolve over time and present an important plasticity. White adipose tissues are responsible of energy storage, and the interplay between adipocyte hypertrophy (cell enlargement) and hyperplasia (cell proliferation), as well as their impact on metabolic function, remain unclear.
By leveraging the trout model, a species that exhibits changes in body composition, especially adipose tissue, during spawning, the project is based on an original physiological model. The project integrates in vivo experimentation, advanced 3D imaging, and mathematical modeling (using size-structured partial differential equations) to analyze adipocyte size distributions, which reflect physiological and environmental influences.
The approach combines longitudinal tracking of white adipose tissues before, during, and after spawning with analysis of white adipose tissues 3D structure. Mathematical models based on size-structured partial differential equations will be developed to reproduce the measurements.
Parameter inference techniques, including Physics-Informed Neural Networks, will bridge experimental data and model predictions, enabling the identification of regulatory mechanisms.
Ultimately, TRIDAN seeks to unravel the complex regulation of white adipose tissues, providing new insights into fat depot function and metabolic status, with implications for both aquaculture and broader obesity research. The TRIDAN consortium is multi-disciplinary and composed of applied mathematicians, computational biologists and experimental biologists.
By leveraging the trout model, a species that exhibits changes in body composition, especially adipose tissue, during spawning, the project is based on an original physiological model. The project integrates in vivo experimentation, advanced 3D imaging, and mathematical modeling (using size-structured partial differential equations) to analyze adipocyte size distributions, which reflect physiological and environmental influences.
The approach combines longitudinal tracking of white adipose tissues before, during, and after spawning with analysis of white adipose tissues 3D structure. Mathematical models based on size-structured partial differential equations will be developed to reproduce the measurements.
Parameter inference techniques, including Physics-Informed Neural Networks, will bridge experimental data and model predictions, enabling the identification of regulatory mechanisms.
Ultimately, TRIDAN seeks to unravel the complex regulation of white adipose tissues, providing new insights into fat depot function and metabolic status, with implications for both aquaculture and broader obesity research. The TRIDAN consortium is multi-disciplinary and composed of applied mathematicians, computational biologists and experimental biologists.
Grand objectif concerné - principal - (MathNum)
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