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Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools
Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety mar...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800680/ https://www.ncbi.nlm.nih.gov/pubmed/29408882 http://dx.doi.org/10.1371/journal.pone.0191896 |
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author | Sasaki, Eita Momose, Haruka Hiradate, Yuki Furuhata, Keiko Takai, Mamiko Asanuma, Hideki Ishii, Ken J. Mizukami, Takuo Hamaguchi, Isao |
author_facet | Sasaki, Eita Momose, Haruka Hiradate, Yuki Furuhata, Keiko Takai, Mamiko Asanuma, Hideki Ishii, Ken J. Mizukami, Takuo Hamaguchi, Isao |
author_sort | Sasaki, Eita |
collection | PubMed |
description | Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development. |
format | Online Article Text |
id | pubmed-5800680 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-58006802018-02-23 Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools Sasaki, Eita Momose, Haruka Hiradate, Yuki Furuhata, Keiko Takai, Mamiko Asanuma, Hideki Ishii, Ken J. Mizukami, Takuo Hamaguchi, Isao PLoS One Research Article Historically, vaccine safety assessments have been conducted by animal testing (e.g., quality control tests and adjuvant development). However, classical evaluation methods do not provide sufficient information to make treatment decisions. We previously identified biomarker genes as novel safety markers. Here, we developed a practical safety assessment system used to evaluate the intramuscular, intraperitoneal, and nasal inoculation routes to provide robust and comprehensive safety data. Influenza vaccines were used as model vaccines. A toxicity reference vaccine (RE) and poly I:C-adjuvanted hemagglutinin split vaccine were used as toxicity controls, while a non-adjuvanted hemagglutinin split vaccine and AddaVax (squalene-based oil-in-water nano-emulsion with a formulation similar to MF59)-adjuvanted hemagglutinin split vaccine were used as safety controls. Body weight changes, number of white blood cells, and lung biomarker gene expression profiles were determined in mice. In addition, vaccines were inoculated into mice by three different administration routes. Logistic regression analyses were carried out to determine the expression changes of each biomarker. The results showed that the regression equations clearly classified each vaccine according to its toxic potential and inoculation amount by biomarker expression levels. Interestingly, lung biomarker expression was nearly equivalent for the various inoculation routes. The results of the present safety evaluation were confirmed by the approximation rate for the toxicity control. This method may contribute to toxicity evaluation such as quality control tests and adjuvant development. Public Library of Science 2018-02-06 /pmc/articles/PMC5800680/ /pubmed/29408882 http://dx.doi.org/10.1371/journal.pone.0191896 Text en © 2018 Sasaki et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Sasaki, Eita Momose, Haruka Hiradate, Yuki Furuhata, Keiko Takai, Mamiko Asanuma, Hideki Ishii, Ken J. Mizukami, Takuo Hamaguchi, Isao Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title | Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title_full | Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title_fullStr | Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title_full_unstemmed | Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title_short | Modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
title_sort | modeling for influenza vaccines and adjuvants profile for safety prediction system using gene expression profiling and statistical tools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800680/ https://www.ncbi.nlm.nih.gov/pubmed/29408882 http://dx.doi.org/10.1371/journal.pone.0191896 |
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