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An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser

Using a scanning near-field optical microscope coupled to an infrared free electron laser (SNOM-IR-FEL) in low-resolution transmission mode, we collected chemical data from whole cervical cells obtained from 5 pre-menopausal, non-pregnant women of reproductive age, and cytologically classified as no...

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Autores principales: Halliwell, Diane E., Morais, Camilo L.M., Lima, Kássio M.G., Trevisan, Júlio, Siggel-King, Michele R.F., Craig, Tim, Ingham, James, Martin, David S., Heys, Kelly, Kyrgiou, Maria, Mitra, Anita, Paraskevaidis, Evangelos, Theophilou, Georgios, Martin-Hirsch, Pierre L., Cricenti, Antonio, Luce, Marco, Weightman, Peter, Martin, Francis L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505104/
https://www.ncbi.nlm.nih.gov/pubmed/28696426
http://dx.doi.org/10.1038/sdata.2017.84
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author Halliwell, Diane E.
Morais, Camilo L.M.
Lima, Kássio M.G.
Trevisan, Júlio
Siggel-King, Michele R.F.
Craig, Tim
Ingham, James
Martin, David S.
Heys, Kelly
Kyrgiou, Maria
Mitra, Anita
Paraskevaidis, Evangelos
Theophilou, Georgios
Martin-Hirsch, Pierre L.
Cricenti, Antonio
Luce, Marco
Weightman, Peter
Martin, Francis L.
author_facet Halliwell, Diane E.
Morais, Camilo L.M.
Lima, Kássio M.G.
Trevisan, Júlio
Siggel-King, Michele R.F.
Craig, Tim
Ingham, James
Martin, David S.
Heys, Kelly
Kyrgiou, Maria
Mitra, Anita
Paraskevaidis, Evangelos
Theophilou, Georgios
Martin-Hirsch, Pierre L.
Cricenti, Antonio
Luce, Marco
Weightman, Peter
Martin, Francis L.
author_sort Halliwell, Diane E.
collection PubMed
description Using a scanning near-field optical microscope coupled to an infrared free electron laser (SNOM-IR-FEL) in low-resolution transmission mode, we collected chemical data from whole cervical cells obtained from 5 pre-menopausal, non-pregnant women of reproductive age, and cytologically classified as normal or with different grades of cervical cell dyskaryosis. Imaging data are complemented by demography. All samples were collected before any treatment. Spectra were also collected using attenuated total reflection, Fourier-transform (ATR-FTIR) spectroscopy, to investigate the differences between the two techniques. Results of this pilot study suggests SNOM-IR-FEL may be able to distinguish cervical abnormalities based upon changes in the chemical profiles for each grade of dyskaryosis at designated wavelengths associated with DNA, Amide I/II, and lipids. The novel data sets are the first collected using SNOM-IR-FEL in transmission mode at the ALICE facility (UK), and obtained using whole cells as opposed to tissue sections, thus providing an ‘intact’ chemical profile. These data sets are suited to complementing future work on image analysis, and/or applying the newly developed algorithm to other datasets collected using the SNOM-IR-FEL approach.
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spelling pubmed-55051042017-07-12 An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser Halliwell, Diane E. Morais, Camilo L.M. Lima, Kássio M.G. Trevisan, Júlio Siggel-King, Michele R.F. Craig, Tim Ingham, James Martin, David S. Heys, Kelly Kyrgiou, Maria Mitra, Anita Paraskevaidis, Evangelos Theophilou, Georgios Martin-Hirsch, Pierre L. Cricenti, Antonio Luce, Marco Weightman, Peter Martin, Francis L. Sci Data Data Descriptor Using a scanning near-field optical microscope coupled to an infrared free electron laser (SNOM-IR-FEL) in low-resolution transmission mode, we collected chemical data from whole cervical cells obtained from 5 pre-menopausal, non-pregnant women of reproductive age, and cytologically classified as normal or with different grades of cervical cell dyskaryosis. Imaging data are complemented by demography. All samples were collected before any treatment. Spectra were also collected using attenuated total reflection, Fourier-transform (ATR-FTIR) spectroscopy, to investigate the differences between the two techniques. Results of this pilot study suggests SNOM-IR-FEL may be able to distinguish cervical abnormalities based upon changes in the chemical profiles for each grade of dyskaryosis at designated wavelengths associated with DNA, Amide I/II, and lipids. The novel data sets are the first collected using SNOM-IR-FEL in transmission mode at the ALICE facility (UK), and obtained using whole cells as opposed to tissue sections, thus providing an ‘intact’ chemical profile. These data sets are suited to complementing future work on image analysis, and/or applying the newly developed algorithm to other datasets collected using the SNOM-IR-FEL approach. Nature Publishing Group 2017-07-11 /pmc/articles/PMC5505104/ /pubmed/28696426 http://dx.doi.org/10.1038/sdata.2017.84 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ 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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Halliwell, Diane E.
Morais, Camilo L.M.
Lima, Kássio M.G.
Trevisan, Júlio
Siggel-King, Michele R.F.
Craig, Tim
Ingham, James
Martin, David S.
Heys, Kelly
Kyrgiou, Maria
Mitra, Anita
Paraskevaidis, Evangelos
Theophilou, Georgios
Martin-Hirsch, Pierre L.
Cricenti, Antonio
Luce, Marco
Weightman, Peter
Martin, Francis L.
An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title_full An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title_fullStr An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title_full_unstemmed An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title_short An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
title_sort imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505104/
https://www.ncbi.nlm.nih.gov/pubmed/28696426
http://dx.doi.org/10.1038/sdata.2017.84
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