The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research

Detalhes bibliográficos
Autor(a) principal: Castro, AR
Data de Publicação: 2022
Outros Autores: Portinha, C, Logarinho, E
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/146526
Resumo: Different animal models have been used for hair research and regeneration studies based on the similarities between animal and human skins. Primary knowledge on hair follicle (HF) biology has arisen from research using mouse models baring spontaneous or genetically engineered mutations. These studies have been crucial for the discovery of genes underlying human hair cycle control and hair loss disorders. Yet, researchers have become increasingly aware that there are distinct architectural and cellular features between the mouse and human HFs, which might limit the translation of findings in the mouse models. Thus, it is enticing to reason that the spotlight on mouse models and the unwillingness to adapt to the human archetype have been hampering the emergence of the long-awaited human hair loss cure. Here, we provide an overview of the major limitations of the mainstream mouse models for human hair loss research, and we underpin a future course of action using human cell bioengineered models and the emergent artificial intelligence.
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spelling The Emergent Power of Human Cellular vs Mouse Models in Translational Hair ResearchHair folliclesHair lossHuman modelsMouse modelsTranslational researchDifferent animal models have been used for hair research and regeneration studies based on the similarities between animal and human skins. Primary knowledge on hair follicle (HF) biology has arisen from research using mouse models baring spontaneous or genetically engineered mutations. These studies have been crucial for the discovery of genes underlying human hair cycle control and hair loss disorders. Yet, researchers have become increasingly aware that there are distinct architectural and cellular features between the mouse and human HFs, which might limit the translation of findings in the mouse models. Thus, it is enticing to reason that the spotlight on mouse models and the unwillingness to adapt to the human archetype have been hampering the emergence of the long-awaited human hair loss cure. Here, we provide an overview of the major limitations of the mainstream mouse models for human hair loss research, and we underpin a future course of action using human cell bioengineered models and the emergent artificial intelligence.Oxford University Press20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/146526eng2157-656410.1093/stcltm/szac059Castro, ARPortinha, CLogarinho, Einfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:28:37Zoai:repositorio-aberto.up.pt:10216/146526Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:02:07.026375Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
title The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
spellingShingle The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
Castro, AR
Hair follicles
Hair loss
Human models
Mouse models
Translational research
title_short The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
title_full The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
title_fullStr The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
title_full_unstemmed The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
title_sort The Emergent Power of Human Cellular vs Mouse Models in Translational Hair Research
author Castro, AR
author_facet Castro, AR
Portinha, C
Logarinho, E
author_role author
author2 Portinha, C
Logarinho, E
author2_role author
author
dc.contributor.author.fl_str_mv Castro, AR
Portinha, C
Logarinho, E
dc.subject.por.fl_str_mv Hair follicles
Hair loss
Human models
Mouse models
Translational research
topic Hair follicles
Hair loss
Human models
Mouse models
Translational research
description Different animal models have been used for hair research and regeneration studies based on the similarities between animal and human skins. Primary knowledge on hair follicle (HF) biology has arisen from research using mouse models baring spontaneous or genetically engineered mutations. These studies have been crucial for the discovery of genes underlying human hair cycle control and hair loss disorders. Yet, researchers have become increasingly aware that there are distinct architectural and cellular features between the mouse and human HFs, which might limit the translation of findings in the mouse models. Thus, it is enticing to reason that the spotlight on mouse models and the unwillingness to adapt to the human archetype have been hampering the emergence of the long-awaited human hair loss cure. Here, we provide an overview of the major limitations of the mainstream mouse models for human hair loss research, and we underpin a future course of action using human cell bioengineered models and the emergent artificial intelligence.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv https://hdl.handle.net/10216/146526
url https://hdl.handle.net/10216/146526
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2157-6564
10.1093/stcltm/szac059
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dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
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