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

Authors :
Halliwell, Diane E.
Medeiros-De-morais, Camilo De lelis
Lima, Kássio M. G.
Trevisan, Julio
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
Halliwell, Diane E.
Medeiros-De-morais, Camilo De lelis
Lima, Kássio M. G.
Trevisan, Julio
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
Publication Year :
2017

Abstract

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.

Details

Database :
OAIster
Notes :
application/pdf, application/pdf, application/pdf, application/pdf, application/pdf, English, English, English, English, English
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn982697437
Document Type :
Electronic Resource