Evidence map›Paper›PMID 29531352›Full record

ArticleScientific reports2018

Simultaneous Multiparameter Cellular Energy Metabolism Profiling of Small Populations of Cells.

Laimonas Kelbauskas, Shashaanka P Ashili, Kristen B Lee, Haixin Zhu, Yanqing Tian, Deirdre R Meldrum

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

0 citing papers in PubMed, 4 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Laimonas KelbauskasCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA. lkelbaus@asu.edu.
Shashaanka P AshiliCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Kristen B LeeCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Haixin ZhuCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Yanqing TianCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA.
Deirdre R MeldrumCenter for Biosignatures Discovery Automation, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave., Tempe, AZ, 85287, USA. deirdre.meldrum@asu.edu.
Arizona State University · US

Funding

CEGSTech: Integrated Biologically-Active MicrosystemsP50HG002360 · NHGRI · UNIVERSITY OF WASHINGTON · PI MELDRUM, DEIRDRE R. · 2001 to 2012
$37.8M
NHGRI NIH HHS P50 HG002360
6 · The paper itself

Abstract

Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)-a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)-a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.

Indexed as

Cell CommunicationEnergy MetabolismSingle-Cell AnalysisAnimalsBiomedical TechnologyCell LineEpithelial CellsEquipment DesignEsophagusHumansMembrane Potential, MitochondrialOxygen ConsumptionSample Size

Identifiers

PMID29531352
PMCPMC5847514
OpenAlexW2805515354

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.