Evidence map›Paper›PMID 23246232›Full record

ReviewCurrent opinion in biotechnology2013

Progress toward single cell metabolomics.

Stanislav S Rubakhin, Eric J Lanni, Jonathan V Sweedler

Abstract readReview
In one paragraph

Review in Current opinion in biotechnology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing 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

66 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Metabolomics: A useful tool for ischemic stroke research.Journal of pharmaceutical analysis · 2023
    Review
  10. Article
  11. Article
  12. Article
  13. The limitless applications of single-cell metabolomics.Current opinion in biotechnology · 2021
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  20. Article

6 more citing papers are in PubMed but not listed here.

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

3 authors.

Stanislav S RubakhinDepartment of Chemistry and the Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. roubakhi@illinois.edu
Eric J Lanni
Jonathan V Sweedler

Funding

The UIUC Neuroproteomics Center on Cell-Cell SignalingP30DA018310 · NIDA · UNIVERSITY OF ILLINOIS URBANA-CHAMPAIGN · PI Elena V Romanova · 2004 to 2026
$24.9M
NIDA NIH HHS P30 DA018310
6 · The paper itself

Abstract

The metabolome refers to the entire set of small molecules, or metabolites, within a biological sample. These molecules are involved in many fundamental intracellular functions and reflect the cell's physiological condition. The ability to detect and identify metabolites and determine and monitor their amounts at the single cell level enables an exciting range of studies of biological variation and functional heterogeneity between cells, even within a presumably homogenous cell population. Significant progress has been made in the development and application of bioanalytical tools for single cell metabolomics based on mass spectrometry, microfluidics, and capillary separations. Remarkable improvements in the sensitivity, specificity, and throughput of these approaches enable investigation of multiple metabolites simultaneously in a range of individual cell samples.

Indexed as

MetabolomeAnimalsBacteriaFungiHumansMass SpectrometryMetabolomicsMicrofluidicsPlant CellsSingle-Cell Analysis

Identifiers

PMID23246232
PMCPMC3545069

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.