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    • WP1 / Progression of obesity and related complications: role of gut microbiota?
    • WP2 / Intestine as a key player in metabolic disorders
    • WP3 / Adipose tissue Remodeling
    • WP4 / Systems’ biology and data integration (transversal WP)
    • WP5 / Translating our fundamental research for the benefit of patients
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    • WP1 / Progression of obesity and related complications: role of gut microbiota?
    • WP2 / Intestine as a key player in metabolic disorders
    • WP3 / Adipose tissue Remodeling
    • WP4 / Systems’ biology and data integration (transversal WP)
    • WP5 / Translating our fundamental research for the benefit of patients
  • Team
    • Members
    • Workflow
    • History
  • Collabs
  • Cohorts
  • Tools
  • Publications
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Research 2017-09-28T12:34:20+00:00

TOPIC 1

Progression of obesity and related complications: role of gut microbiota?

TOPIC 2

Intestine as a key player in metabolic disorders

TOPIC 3

Adipose tissue Remodeling

TOPIC 4

Systems’ biology and data integration (transversal WP)

TOPIC 5

Translating our fundamental research for the benefit of patients.

  • Define gut microbiota signature in CMD and evaluate the impact of environment (diet and drugs)
  • Demonstrate causality of CMD microbial signature in the development of CMD or its resolution:
    • in human interventions: Metacardis follow-up (development), diet or bariatric surgery (reversal)
    • in mice: gut microbiota transfer experiments (induce CMD or its reversal)

The intestine is a target for changes in external (food, microbiota) and internal (immune system) environment. Gut adaptation has in turn consequences on gut immunity, epithelial cells homeostasis and key organs for energy balance.

  • Understand WAT fibrosis : role of progenitors:
  • Characterize WAT senescence :
    • Evaluate inappropriate turnover of subcellular components (Lysosomal degradation)
    • Examine PG as gut-derived signaling modulators in AT remodeling

We will develop innovative tools for data analysis, physiological status prediction, and visualisation in metabolic diseases. Convergence of techniques include statistical inferences, machine learning, and mechanistic approach using dynamical systems. This WP is  strongly integrated with the other WPs which produce large-scale data.

Two main axes

  1. Develop innovative diagnosis and predictive factors/tools:
  2. Develop novel approaches for therapy with personalized medicine
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