Evidence map›Paper›PMID 21156146›Full record

ArticleBiophysical journal2010

Real-time monitoring of epithelial cell-cell and cell-substrate interactions by infrared surface plasmon spectroscopy.

Victor Yashunsky, Vladislav Lirtsman, Michael Golosovsky, Dan Davidov, Benjamin Aroeti

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 64 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.

Victor YashunskyThe Racah Institute of Physics, Department of Cell and Developmental Biology, The Hebrew University of Jerusalem, Jerusalem, Israel. victor.yashunsky@mail.huji.ac.il
Vladislav Lirtsman
Michael Golosovsky
Dan Davidov
Benjamin Aroeti
Hebrew University of Jerusalem · IL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of novel technologies capable of monitoring the dynamics of cell-cell and cell-substrate interactions in real time and a label-free manner is vital for gaining deeper insights into these most fundamental cellular processes. However, the label-free technologies available today provide only limited information on these processes. Here, we report a new (to our knowledge) infrared surface plasmon resonance (SPR)-based methodology that can resolve distinct phases of cell-cell and cell-substrate adhesion of polarized Madin Darby canine kidney epithelial cells. Due to the extended penetration depth of the infrared SP wave, the dynamics of cell adhesion can be detected with high accuracy and high temporal resolution. Analysis of the temporal variation of the SPR reflectivity spectrum revealed the existence of multiple phases in epithelial cell adhesion: initial contact of the cells with the substrate (cell deposition), cell spreading, formation of intercellular contacts, and subsequent generation of cell clusters. The final formation of a continuous cell monolayer could also be sensed. The SPR measurements were validated by optical microscopy imaging. However, in contrast to the SPR method, the optical analyses were laborious and less quantitative, and hence provided only limited information on the dynamics and phases of cell adhesion.

Indexed as

Cell CommunicationAnimalsCell MovementCells, CulturedCell ShapeDogsEpithelial CellsSpectroscopy, Fourier Transform InfraredSurface Plasmon ResonanceSurface PropertiesTime Factors

Identifiers

PMID21156146
PMCPMC3000480
OpenAlexW1977174354

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.