The Causes of Using Animal Model to Understand Human Metabolism
Research Article
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The Causes of Using Animal Model to Understand Human Metabolism

Yanming Guo 1*
1 Malvern College Qingdao
*Corresponding author: 3468326897@qq.com
Published on 28 October 2025
Journal Cover
TNS Vol.149
ISSN (Print): 2753-8826
ISSN (Online): 2753-8818
ISBN (Print): 978-1-80590-501-1
ISBN (Online): 978-1-80590-502-8
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Abstract

It is ethically impermissible to conduct continuous interventions on humans from birth to old age for the purpose of studying the long-term side effects of a new drug or the function of a gene. Animal models offer us a controllable and operable platform for studying complex metabolic processes in a complete life system, which is impossible to achieve in human research. This paper delves into the rationale, methodologies, and implications of using animal models to understand human metabolism. It explores the theoretical bases, presents experimental cases like the Diet-Induced Obesity (DIO) mouse model, and assesses the value and limitations. By examining the biological similarity, controllability, and translational potential, this paper indicates that animal models are crucial tools; the causes for their uses are rooted in a combination of ethical necessity, biological similarity, and practical experimental advantages, but they cannot perfectly replicate the complex metabolism of humans. The insights gained can be used for future metabolism research, such as obesity and diabetes.

Keywords:

animal model, metabolism, obesity, medical ethics

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Guo,Y. (2025). The Causes of Using Animal Model to Understand Human Metabolism. Theoretical and Natural Science,149,1-6.

References

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Cite this article

Guo,Y. (2025). The Causes of Using Animal Model to Understand Human Metabolism. Theoretical and Natural Science,149,1-6.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICMMGH 2026 Symposium: Environmental Engineering and Climate Change

ISBN: 978-1-80590-501-1(Print) / 978-1-80590-502-8(Online)
Editor: Alan Wang, Sheiladevi Sukumaran
Conference date: 16 January 2026
Series: Theoretical and Natural Science
Volume number: Vol.149
ISSN: 2753-8818(Print) / 2753-8826(Online)