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Multivariate data validation for investigating primary HCMV infection in pregnancy
We reported data concerning the Gas Chromatography–Mass Spectrometry (GC–MS) based metabolomic analysis of amniotic fluid (AF) samples obtained from pregnant women infected with Human Cytomegalovirus (HCMV). These data support the publication “Primary HCMV Infection in Pregnancy from Classic Data to...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021794/ https://www.ncbi.nlm.nih.gov/pubmed/27656676 http://dx.doi.org/10.1016/j.dib.2016.08.050 |
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author | Barberini, Luigi Noto, Antonio Saba, Luca Palmas, Francesco Fanos, Vassilios Dessì, Angelica Zavattoni, Maurizio Fattuoni, Claudia Mussap, Michele |
author_facet | Barberini, Luigi Noto, Antonio Saba, Luca Palmas, Francesco Fanos, Vassilios Dessì, Angelica Zavattoni, Maurizio Fattuoni, Claudia Mussap, Michele |
author_sort | Barberini, Luigi |
collection | PubMed |
description | We reported data concerning the Gas Chromatography–Mass Spectrometry (GC–MS) based metabolomic analysis of amniotic fluid (AF) samples obtained from pregnant women infected with Human Cytomegalovirus (HCMV). These data support the publication “Primary HCMV Infection in Pregnancy from Classic Data towards Metabolomics: an Exploratory analysis” (C. Fattuoni, F. Palmas, A. Noto, L. Barberini, M. Mussap, et al., 2016) [2]. GC–MS and Multivariate analysis allow to recognize the molecular phenotype of HCMV infected fetuses (transmitters) and that of HCMV non-infected fetuses (non-transmitters); moreover, GC–MS and multivariate analysis allow to distinguish and to compare the molecular phenotype of these two groups with a control group consisting of AF samples obtained in HCMV non-infected pregnant women. The obtained data discriminate controls from transmitters as well as from non-transmitters; no statistically significant difference was found between transmitters and non-transmitters. |
format | Online Article Text |
id | pubmed-5021794 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-50217942016-09-21 Multivariate data validation for investigating primary HCMV infection in pregnancy Barberini, Luigi Noto, Antonio Saba, Luca Palmas, Francesco Fanos, Vassilios Dessì, Angelica Zavattoni, Maurizio Fattuoni, Claudia Mussap, Michele Data Brief Data Article We reported data concerning the Gas Chromatography–Mass Spectrometry (GC–MS) based metabolomic analysis of amniotic fluid (AF) samples obtained from pregnant women infected with Human Cytomegalovirus (HCMV). These data support the publication “Primary HCMV Infection in Pregnancy from Classic Data towards Metabolomics: an Exploratory analysis” (C. Fattuoni, F. Palmas, A. Noto, L. Barberini, M. Mussap, et al., 2016) [2]. GC–MS and Multivariate analysis allow to recognize the molecular phenotype of HCMV infected fetuses (transmitters) and that of HCMV non-infected fetuses (non-transmitters); moreover, GC–MS and multivariate analysis allow to distinguish and to compare the molecular phenotype of these two groups with a control group consisting of AF samples obtained in HCMV non-infected pregnant women. The obtained data discriminate controls from transmitters as well as from non-transmitters; no statistically significant difference was found between transmitters and non-transmitters. Elsevier 2016-08-31 /pmc/articles/PMC5021794/ /pubmed/27656676 http://dx.doi.org/10.1016/j.dib.2016.08.050 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Barberini, Luigi Noto, Antonio Saba, Luca Palmas, Francesco Fanos, Vassilios Dessì, Angelica Zavattoni, Maurizio Fattuoni, Claudia Mussap, Michele Multivariate data validation for investigating primary HCMV infection in pregnancy |
title | Multivariate data validation for investigating primary HCMV infection in pregnancy |
title_full | Multivariate data validation for investigating primary HCMV infection in pregnancy |
title_fullStr | Multivariate data validation for investigating primary HCMV infection in pregnancy |
title_full_unstemmed | Multivariate data validation for investigating primary HCMV infection in pregnancy |
title_short | Multivariate data validation for investigating primary HCMV infection in pregnancy |
title_sort | multivariate data validation for investigating primary hcmv infection in pregnancy |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5021794/ https://www.ncbi.nlm.nih.gov/pubmed/27656676 http://dx.doi.org/10.1016/j.dib.2016.08.050 |
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