Mathematical modeling of intestinal iron absorption using genetic programming
| Autor: | J. Cristian Salgado, Andrea Colins, Marco T. Núñez, Ziomara P. Gerdtzen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Cell Lines Evolutionary algorithm lcsh:Medicine Genetic programming Physical Chemistry Mathematical and Statistical Techniques 0302 clinical medicine Medicine and Health Sciences Intestinal Mucosa lcsh:Science Mathematics Multidisciplinary Mathematical model Mathematical Models Simulation and Modeling Applied Mathematics Chemistry 030220 oncology & carcinogenesis Physical Sciences Sorption Biological Cultures Anatomy Biological system Jackknife resampling Algorithms Research Article Chemical Elements Iron Complex system Research and Analysis Methods Models Biological Absorption 03 medical and health sciences Cell Line Tumor Component (UML) Computational Techniques Animals Humans Models Genetic Mechanism (biology) lcsh:R Reproducibility of Results Biology and Life Sciences Biological Transport Function (mathematics) Models Theoretical Gastrointestinal Tract Kinetics 030104 developmental biology Gastrointestinal Absorption lcsh:Q Evolutionary Algorithms Caco-2 Cells Evolutionary Computation Digestive System |
| Zdroj: | Colins, A, Gerdtzen, Z P, Nuñez, M T & Salgado, J C 2017, ' Mathematical modeling of intestinal iron absorption using genetic programming ', PLoS ONE . https://doi.org/10.1371/journal.pone.0169601 PLoS ONE, Vol 12, Iss 1, p e0169601 (2017) PLoS ONE |
| Popis: | Iron is a trace metal, key for the development of living organisms. Its absorption process is complex and highly regulated at the transcriptional, translational and systemic levels. Recently, the internalization of the DMT1 transporter has been proposed as an additional regulatory mechanism at the intestinal level, associated to the mucosal block phenomenon. The short-term effect of iron exposure in apical uptake and initial absorption rates was studied in Caco-2 cells at different apical iron concentrations, using both an experimental approach and a mathematical modeling framework. This is the first report of short-term studies for this system. A non-linear behavior in the apical uptake dynamics was observed, which does not follow the classic saturation dynamics of traditional biochemical models. We propose a method for developing mathematical models for complex systems, based on a genetic programming algorithm. The algorithm is aimed at obtaining models with a high predictive capacity, and considers an additional parameter fitting stage and an additional Jackknife stage for estimating the generalization error. We developed a model for the iron uptake system with a higher predictive capacity than classic biochemical models. This was observed both with the apical uptake dataset used for generating the model and with an independent initial rates dataset used to test the predictive capacity of the model. The model obtained is a function of time and the initial apical iron concentration, with a linear component that captures the global tendency of the system, and a non-linear component that can be associated to the movement of DMT1 transporters. The model presented in this paper allows the detailed analysis, interpretation of experimental data, and identification of key relevant components for this complex biological process. This general method holds great potential for application to the elucidation of biological mechanisms and their key components in other complex systems. |
| Databáze: | OpenAIRE |
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