Evidence map›Paper›PMID 21704852›Full record

ArticleMethods in cell biology2011

Surface-enhanced Raman scattering (SERS) cytometry.

John P Nolan, David S Sebba

Abstract read
In one paragraph

Article in Methods in cell biology, 2011. 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
–field-weighted citation impact
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.

  1. Article
  2. PLGA-Based Composites for Various Biomedical Applications.International journal of molecular sciences · 2022
    Review
  3. Review
  4. Materials (Basel, Switzerland) · 2019
    Article
  5. Article
  6. PhotoacousticPhotoacoustics · 2017
    Article
  7. Article
  8. Generalized unmixing model for multispectral flow cytometry utilizing nonsquare compensation matrices.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2013
    Article
  9. Visible and near infrared fluorescence spectral flow cytometry.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2013
    Article
  10. Article
  11. Spectral flow cytometry.Current protocols in cytometry · 2013
    Review
  12. Review
  13. In vivo flow cytometry: a horizon of opportunities.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2011
    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

2 authors.

John P NolanLa Jolla Bioengineering Institute, La Jolla, California, USA.
David S Sebba

Funding

Raman Flow Cytometry for Diagnostics and Drug DiscoveryR01EB003824 · NIBIB · SCINTILLON INSTITUTE FOR PHOTOBIOLOGY · PI NOLAN, JOHN P · 2004 to 2014
$12.2M
NIBIB NIH HHS R01 EB003824
6 · The paper itself

Abstract

Significant advances have been made in the preparation and applications of surface-enhanced Raman scattering (SERS)-active materials for biomolecular analysis. Bright signals, photostability, and narrow spectral features of SERS-active materials offer attractive advantages for cytometric analyses. However, SERS cytometry is still in an early stage of development, and advances in both instrumentation and reagents will be necessary to realize its full potential. In this chapter, we discuss the challenges of expanding the numbers of fluorescent labels that can be measured in cytometry, and introduce SERS tags with extremely narrow spectral peaks as an approach to make more efficient use of the optical spectrum and increase the number of parameters in cytometry.

Indexed as

Flow CytometryMetal NanoparticlesMultivariate AnalysisPrincipal Component AnalysisReference StandardsSpectrum Analysis, Raman

Identifiers

PMID21704852
PMCPMC3128434

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.