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Of Mice, Dirty Mice, and Men: Using Mice To Understand Human Immunology

descriptionPublicationkeyboard_double_arrow_right Article 01 Jul 2017 English Publisher:Oxford University Press (OUP)Journal:The Journal of Immunology, volume 199, pages 383-388 (issn: 0022-1767, eissn: 1550-6606,

Authors: Stephen C. Jameson; David Masopust; Christine P. Sivula;

doi: 10.4049/jimmunol.1700453

pmid: 28696328

pmc: PMC5512602

Of Mice, Dirty Mice, and Men: Using Mice To Understand Human Immunology

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Abstract

Abstract Mouse models have enabled breakthroughs in our understanding of the immune system, but it has become increasingly popular to emphasize their shortcomings when translating observations to humans. This review provides a brief summary of mouse natural history, husbandry, and the pros and cons of pursuing basic research in mice versus humans. Opportunities are discussed for extending the predictive translational value of mouse research, with an emphasis on exploitation of a “dirty” mouse model that better mimics the diverse infectious history that is typical of most humans.

Related Organizations

University of Minnesota Morris
United States

Keywords

Male, Biomedical Research, Communicable Diseases, Autoimmune Diseases, Disease Models, Animal, Mice, Animals, Laboratory, Immune System, Models, Animal, Animals, Humans

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	242
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 1%