Evidence map›Paper›PMID 18682362›Full record

ReviewJournal of the Royal Society, Interface2008

Microfluidic single-cell analysis of intracellular compounds.

Tzu-Chiao Chao, Alexandra Ros

Abstract readReview
In one paragraph

Review in Journal of the Royal Society, Interface, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Modular microfluidics for life sciences.Journal of nanobiotechnology · 2023
    Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. Article
  10. Article
  11. Investigation of nerve injury through microfluidic devices.Journal of the Royal Society, Interface · 2014
    Review
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. Chemical analysis of single cells.Analytical chemistry · 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.

Tzu-Chiao ChaoDepartment of Chemistry and Biochemistry, Arizona State University, Box 871604, Tempe, AZ 85287-1604, USA.
Alexandra Ros

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological analyses traditionally probe cell ensembles in the range of 103-106 cells, thereby completely averaging over relevant individual cell responses, such as differences in cell proliferation, responses to external stimuli or disease onset. In past years, this fact has been realized and increasing interest has evolved for single-cell analytical methods, which could give exciting new insights into genomics, proteomics, transcriptomics and systems biology. Microfluidic or lab-on-a-chip devices are the method of choice for single-cell analytical tools as they allow the integration of a variety of necessary process steps involved in single-cell analysis, such as selection, navigation, positioning or lysis of single cells as well as separation and detection of cellular analytes. Along with this advantageous integration, microfluidic devices confine single cells in compartments near their intrinsic volume, thus minimizing dilution effects and increasing detection sensitivity. This review overviews the developments and achievements of microfluidic single-cell analysis of intracellular compounds in the past few years, from proof-of-principle devices to applications demonstrating a high biological relevance.

Indexed as

Cell SeparationMicrofluidic Analytical TechniquesAmino AcidsCell FractionationCellsDNAElectric ImpedanceElectroporationFluorescent DyesProteinsRNAAmino AcidsDNAFluorescent DyesProteinsRNA

Identifiers

PMID18682362
PMCPMC2706030

What OpenQuestion holds

Textmetadata
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.