Multi-scale modeling of the follicle selection process in the ovary

Echenim, Nki; Monniaux, Danielle; Sorine, Michel; Clément, Frédérique

doi:10.1016/j.mbs.2005.05.003

Cited by 34 publications

(56 citation statements)

References 38 publications

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“…Following [2], cells are characterized by their positions within or outside the cell cycle and by their sensitivities to FSH. This leads to distinguish 3 cellular phases within the granulosa cell population.…”

Section: Follicle Selection Model 21 Controlled Conservation Laws Fomentioning

confidence: 99%

“…Following the subsequent fall in plasmatic FSH levels, most of the follicles undergo atresia and only the ovulatory ones survive in the FSH-poor environment. We have proposed a mathematical model, using both multi-scale modeling and control theory concepts, to describe the follicle selection process [2]. For each follicle, the cell population dynamics is ruled by a conservation law with variable coefficients, which describes the changes in age and maturity of the granulosa cell density.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiscale Modeling of Follicular Ovulation as a Reachability Problem

Echenim¹,

Clément²,

Sorine³

2007

Multiscale Model. Simul.

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During each ovarian cycle, only a definite number of follicles ovulate, while the others undergo a degeneration process called atresia. We have designed a multi-scale mathematical model where ovulation and atresia result from a hormonal controlled selection process. A 2D-conservation law describes the age and maturity structuration of the follicular cell population. In this paper, we focus on the operating mode of the control, through the study of the characteristics associated with the conservation law. We describe in particular the set of microscopic initial conditions leading to the macroscopic phenomenon of either ovulation or atresia, in the framework of backwards reachable sets theory.

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Section: Follicle Selection Model 21 Controlled Conservation Laws Fomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Multiscale Modeling of Follicular Ovulation as a Reachability Problem

Echenim¹,

Clément²,

Sorine³

2007

Multiscale Model. Simul.

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“…The specific application we have in mind is the numerical calibration of terminal follicular development modeled in [9]. Realistic simulations involve solving simultaneously about twenty coupled PDEs in two space dimensions.…”

Section: Introductionmentioning

confidence: 99%

Adaptive mesh refinement strategy for a non conservative transport problem

2014

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ABSTRACT. In the framework of transport equations it is usual to need long time simulations, and therefore large physical domains to cover a phenomenon. On the other hand it can happen that only a small time varying portion of the domain is interesting. This motivates the use of adaptivity for the spatial discretization. Biological models involving cell development are often nonconservative to account for cell division. In that case the threshold controlling the spatial adaptivity may have to be time-dependent in order to keep up with the progression of the solution. In this article we tackle the difficulties arising when applying a Multiresolution method to a transport equation with discontinuous fluxes modeling localized mitosis. The analysis of the numerical method is performed on a simplified model and numerical scheme. An original threshold strategy is proposed and validated thanks to extensive numerical tests. It is then applied to a biological model in both cases of distributed and localized mitosis.

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“…Modelling and simulation of diffusion process in tissue spheroids CFD [14] Agent-based virtual tissue simulations CC3D [17] Cell compressibility, motility and contact inhibition on the growth of tumor cell clusters CC3D [18] Multiscale modeling of the early CD8 T cell immune response in lymph nodes CC3D [19] Multi-scale knowledge on cardiac development CC3D [20] The cell behavior ontology CC3D [21] Cell differentiation in the transition to multicellularity CC3D [22] Dynamics of cell aggregates fusion CC3D [36] A multi-cell model of tumor evolution CC3D [37] Virtual tissues MAS [38] Disruption of blood vessel development CC3D [39] Tumor growth and angiogenesis CC3D [40] Agent-oriented in silico liver (ILS) MAS [41] Model of thrombus development MAS (TS) [42] Three-dimensional multi-scale tumor model MAS [43] A multi-scale model of dendritic cell education and trafficking in the lung CM [44] Multi-scale model of follicular development CM [45] Multi-scale in silico leukocytes model MAS [46] Multi-scale model of organogenesis CM [47] Limitations of spheroids under inappropriate conditions FE [48] Finite lower levels occur at multiple time scales influencing the behavior of the organ. Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes.…”

Section: Strategy Referencesmentioning

confidence: 99%

“…Multi-scale models are usually based on the continuum modeling and/or MAS approaches which can be decomposed into N single-scale mathematical models and several physical processes. Various works have already been done which apply many multi-scale methods in several biological systems [14,[17][18][19][20][21][22][36][37][38][39][40][41][42][43][44][45][46][47][48][49]: a good review is proposed in Table 1.…”

Section: Strategy Referencesmentioning

confidence: 99%

BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs

Dernowsek¹,

Ra²,

Silva³

2017

J Tissue Sci Eng

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Next sessions we expose a new approach, based on Information *Corresponding author: Janaina de Andrea Dernowsek, Center for information technology Renato Archer (CTI), 3D Technologies Research Group (NT3D), Campinas, Brazil, AbstractBiofabrication as an interdisciplinary area is fostering new knowledge and integration of areas like nanotechnology, chemistry, biology, physics, materials science, control systems, among many others, necessary to accomplish the challenge of bioengineering functional complex tissues. The emergence of integrated platforms and systems biology to understand complex biological systems in multiscale levels will enable the prediction and creation of biofabricated biological structures. This systematic analysis (meta-analysis) or integrated platforms for estimating biological process have been named as BioCAE, which will become the key for important steps of the biofabrication processes. Biological Computational Aided Engineering (BioCAE) is a new computational approach to understanding and bioengineer complex tissues (biofabrication) using a combination of different methods as multiscale modelling, computer simulations, data mining and systems biology. In addition, multi-agent systems (MAS), which are composed of different interacting computing entities called agents, also provide an interesting way to design and implement simulations of biological systems, integrating them with all steps of the BioCAE. MAS as a part of computational science have become a growing area to manipulate and solve complex problems. This paper presents an approach that will allow predicting the development and behavior of different biological processes such as molecular networks, gene interactions, cells, tissues and organs due to its flexibility, beyond to provide a new outlook in the biofabrication of tissues and organs.

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Multi-scale modeling of the follicle selection process in the ovary

Cited by 34 publications

References 38 publications

Multiscale Modeling of Follicular Ovulation as a Reachability Problem

Multiscale Modeling of Follicular Ovulation as a Reachability Problem

Adaptive mesh refinement strategy for a non conservative transport problem

BioCAE: A New Strategy of Complex Biological Systems for Biofabrication of Tissues and Organs

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