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A translational model to determine rodent’s age from human foetal age
To understand the prenatal origin of developmental and psychiatric disorders, studies in laboratory animals are imperative. However, the developmental pace differs between humans and animals; hence, corresponding human ages must be estimated to infer the most vulnerable developmental timings in huma...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722919/ https://www.ncbi.nlm.nih.gov/pubmed/29222462 http://dx.doi.org/10.1038/s41598-017-17571-z |
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author | Ohmura, Yoshiyuki Kuniyoshi, Yasuo |
author_facet | Ohmura, Yoshiyuki Kuniyoshi, Yasuo |
author_sort | Ohmura, Yoshiyuki |
collection | PubMed |
description | To understand the prenatal origin of developmental and psychiatric disorders, studies in laboratory animals are imperative. However, the developmental pace differs between humans and animals; hence, corresponding human ages must be estimated to infer the most vulnerable developmental timings in humans. Because rats and mice are extensively used as models in developmental research, a correspondence between human foetal ages and rodents’ ages must be precisely determined; thus, developing a translational model is of utmost importance. Optimizing a translational model involves classifying the brain regions according to developmental paces, but previous studies have conducted this classification arbitrarily. Here we used a clustering method and showed that the brain regions can be classified into two groups. To quantify the developmental pace, we gathered data for a range of development events in humans and rodents and created a linear mixed model that translates human developmental timings into the corresponding rat timings. We conducted an automatic classification of brain regions using an EM algorithm and obtained a model to translate human foetal age to rat age. Our model could predict rat developmental timings within 2.5 days of root mean squared error. This result provides useful information for designing animal studies and clinical tests. |
format | Online Article Text |
id | pubmed-5722919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57229192017-12-12 A translational model to determine rodent’s age from human foetal age Ohmura, Yoshiyuki Kuniyoshi, Yasuo Sci Rep Article To understand the prenatal origin of developmental and psychiatric disorders, studies in laboratory animals are imperative. However, the developmental pace differs between humans and animals; hence, corresponding human ages must be estimated to infer the most vulnerable developmental timings in humans. Because rats and mice are extensively used as models in developmental research, a correspondence between human foetal ages and rodents’ ages must be precisely determined; thus, developing a translational model is of utmost importance. Optimizing a translational model involves classifying the brain regions according to developmental paces, but previous studies have conducted this classification arbitrarily. Here we used a clustering method and showed that the brain regions can be classified into two groups. To quantify the developmental pace, we gathered data for a range of development events in humans and rodents and created a linear mixed model that translates human developmental timings into the corresponding rat timings. We conducted an automatic classification of brain regions using an EM algorithm and obtained a model to translate human foetal age to rat age. Our model could predict rat developmental timings within 2.5 days of root mean squared error. This result provides useful information for designing animal studies and clinical tests. Nature Publishing Group UK 2017-12-08 /pmc/articles/PMC5722919/ /pubmed/29222462 http://dx.doi.org/10.1038/s41598-017-17571-z Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ohmura, Yoshiyuki Kuniyoshi, Yasuo A translational model to determine rodent’s age from human foetal age |
title | A translational model to determine rodent’s age from human foetal age |
title_full | A translational model to determine rodent’s age from human foetal age |
title_fullStr | A translational model to determine rodent’s age from human foetal age |
title_full_unstemmed | A translational model to determine rodent’s age from human foetal age |
title_short | A translational model to determine rodent’s age from human foetal age |
title_sort | translational model to determine rodent’s age from human foetal age |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722919/ https://www.ncbi.nlm.nih.gov/pubmed/29222462 http://dx.doi.org/10.1038/s41598-017-17571-z |
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