ArticleScientific data2017
An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser.
Article in Scientific data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Infrared Free-Electron Laser: A Versatile Molecular Cutter for Analyzing Solid-State Biomacromolecules.ACS omega · 2025Article
- Disassembly of Amyloid Fibril with Infrared Free Electron Laser.International journal of molecular sciences · 2023Review
- Application study of infrared free-electron lasers towards the development of amyloidosis therapy.Journal of synchrotron radiation · 2022Article
- Vibrational Biospectroscopy: An Alternative Approach to Endometrial Cancer Diagnosis and Screening.International journal of molecular sciences · 2022Review
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Authors and funding
18 authors at 10 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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