Theoretical modeling of pre and postnatal growth

Area of Science:

• Comparative animal physiology
• Mathematical biology
• Growth modeling

Background:

• Accurate modeling of animal growth is crucial for understanding developmental biology.
• The von Bertalanffy (VB) model is a common tool for growth analysis.
• Integrating prenatal and postnatal data presents unique challenges.

Purpose of the Study:

• To analyze pre and postnatal growth data for diverse animal species using a generalized VB model.
• To assess the VB model's descriptive and retro-predictive power for animal development.
• To identify factors affecting the stability of VB model fits.

Main Methods:

• Simultaneous analysis of pre and postnatal growth data from five species (zebra, rat, guinea pig, chicken, tilapia).
• Application of the generalized von Bertalanffy (VB) model, incorporating gestation/incubation period as a fitted parameter.
• Evaluation of model performance using goodness-of-fit metrics and biologically meaningful parameters.

Main Results:

• The generalized VB model demonstrated strong descriptive power for both pre and postnatal growth across species.
• Constraining one VB parameter to the gestation/incubation period allowed accurate prediction of prenatal growth.
• The VB model exhibits both descriptive and retro-predictive capabilities for animal development.

Conclusions:

• The generalized VB model is a robust tool for analyzing and predicting animal growth, including prenatal stages.
• The model's ability to incorporate gestation/incubation periods enhances its applicability.
• Understanding VB model fit stability issues, related to the n-exponent, is important for reliable analysis.