Evidence map›Paper›PMID 23931308›Full record

ArticleBiophysical journal2013

Quantitative imaging of protein secretions from single cells in real time.

Marc P Raphael, Joseph A Christodoulides, James B Delehanty, James P Long, Jeff M Byers

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

12 citing papers in PubMed, 44 citations in OpenAlex.

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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.

Marc P RaphaelMaterials Science and Technology Division, Naval Research Laboratory, Washington DC, USA. marc.raphael@nrl.navy.mil
Joseph A Christodoulides
James B Delehanty
James P Long
Jeff M Byers
United States Naval Research Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein secretions from individual cells create spatially and temporally varying concentration profiles in the extracellular environment, which guide a wide range of biological processes such as wound healing and angiogenesis. Fluorescent and colorimetric probes for the detection of single cell secretions have time resolutions that range from hours to days, and as a result, little is known about how individual cells may alter their protein secretion rates on the timescale of minutes or seconds. Here, we present a label-free technique based upon nanoplasmonic imaging, which enabled the measurement of individual cell secretions in real time. When applied to the detection of antibody secretions from single hybridoma cells, the enhanced time resolution revealed two modes of secretion: one in which the cell secreted continuously and another in which antibodies were released in concentrated bursts that coincided with minute-long morphological contractions of the cell. From the continuous secretion measurements we determined the local concentration of antibodies at the sensing array closest to the cell and from the bursts we estimated the diffusion constant of the secreted antibodies through the extracellular media. The design also incorporates transmitted light and fluorescence microscopy capabilities for monitoring cellular morphological changes and intracellular fluorescent labels. We anticipate that this technique can be adapted as a general tool for the quantitative study of paracrine signaling in both adherent and nonadherent cell lines.

Indexed as

Cell MembraneHumansHybridomasMetal NanoparticlesMicroscopy, FluorescenceMolecular ImagingProteinsSurface Plasmon ResonanceProteins

Identifiers

PMID23931308
PMCPMC3736659
OpenAlexW2139174650

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.