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His and her mathematical models of physiological systems
1Departments of Applied Mathematics and Biology, Cheriton School of Computer Science, and School of Pharmacology, University of Waterloo, Waterloo, Ontario, Canada, N2L 3G1.
Mathematical Biosciences
|June 13, 2021
Summary
Mathematical models reveal significant sex differences across human organ systems, crucial for developing targeted therapies. This review explores these models to advance understanding of sex-based health and disease.
Area of Science:
- Physiology
- Biomedical Engineering
- Computational Biology
Background:
- Men and women display significant physiological differences beyond reproduction, affecting brain anatomy, stress and immune system activity, and metabolic and cardiovascular functions.
- Understanding these sex differences is vital for developing effective, sex-based medical therapies.
- Mathematical modeling offers a powerful approach to analyze and understand these complex biological variations.
Purpose of the Study:
- To survey existing sex-specific mathematical models of human physiological systems.
- To describe key insights gained from these modeling studies regarding sex differences.
- To discuss future research opportunities in sex-based mathematical modeling.
Main Methods:
- Literature review of published mathematical models focusing on sex-specific physiological systems.
- Analysis of insights derived from computational simulations and theoretical frameworks.
- Identification of trends and potential advancements in the field.
Main Results:
- A growing body of mathematical models addresses sex differences in various physiological domains.
- Modeling studies have illuminated specific sex-based variations in areas like cardiovascular function and immune response.
- These models provide a quantitative basis for understanding the impact of sex on health and disease.
Conclusions:
- Mathematical modeling is a valuable tool for dissecting complex sex differences in human physiology.
- Further development and application of sex-specific models can significantly enhance our understanding of health and disease.
- Future research should focus on integrating multi-system models and validating them with experimental data.
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