Evidence map›Paper›PMID 28256551›Full record

ArticleScientific reports2017

Multimodal discrimination of immune cells using a combination of Raman spectroscopy and digital holographic microscopy.

Naomi McReynolds, Fiona G M Cooke, Mingzhou Chen, Simon J Powis, Kishan Dholakia

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
4.8field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 52 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Investigation of refractive index dynamics duringBiomedical optics express · 2023
    Article
  7. In vivo optical molecular imaging of inflammation and immunity.Journal of molecular medicine (Berlin, Germany) · 2021
    Review
  8. Decoding Optical Data with Machine Learning.Laser & photonics reviews · 2021
    Article
  9. Review
  10. Article
  11. Article
  12. Noninvasive detection of macrophage activation with single-cell resolution through machine learning.Proceedings of the National Academy of Sciences of the United States of America · 2018
    Article
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Naomi McReynoldsSUPA, School of Physics and Astronomy, University of St Andrews, Fife, KY16 9SS, United Kingdom.
Fiona G M CookeSchool of Medicine, University of St Andrews, Fife, KY16 9TF, United Kingdom.
Mingzhou ChenSUPA, School of Physics and Astronomy, University of St Andrews, Fife, KY16 9SS, United Kingdom.
Simon J PowisSchool of Medicine, University of St Andrews, Fife, KY16 9TF, United Kingdom.
Kishan DholakiaSUPA, School of Physics and Astronomy, University of St Andrews, Fife, KY16 9SS, United Kingdom.
University of St Andrews · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to identify and characterise individual cells of the immune system under label-free conditions would be a significant advantage in biomedical and clinical studies where untouched and unmodified cells are required. We present a multi-modal system capable of simultaneously acquiring both single point Raman spectra and digital holographic images of single cells. We use this combined approach to identify and discriminate between immune cell populations CD4+ T cells, B cells and monocytes. We investigate several approaches to interpret the phase images including signal intensity histograms and texture analysis. Both modalities are independently able to discriminate between cell subsets and dual-modality may therefore be used a means for validation. We demonstrate here sensitivities achieved in the range of 86.8% to 100%, and specificities in the range of 85.4% to 100%. Additionally each modality provides information not available from the other providing both a molecular and a morphological signature of each cell.

Indexed as

HolographyMicroscopyMultimodal ImagingSpectrum Analysis, RamanBiomarkersB-LymphocytesFlow CytometryHumansImmune SystemImmunophenotypingMonocytesSensitivity and SpecificityT-LymphocytesBiomarkers

Identifiers

PMID28256551
PMCPMC5335250
OpenAlexW2594570200

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.