Evidence map›Paper›PMID 21785274›Full record

ReviewCell adhesion & migration

Dissecting cell adhesion architecture using advanced imaging techniques.

Penny E Morton, Maddy Parsons

Open access · goldAbstract readReview
In one paragraph

Review in Cell adhesion & migration. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Fungal adhesion protein guides community behaviors and autoinduction in a paracrine manner.Proceedings of the National Academy of Sciences of the United States of America · 2013
    Article
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 at 2 institutions in 2 countries.

Penny E MortonRandall Division of Cell and Molecular Biophysics, King's College London, London, UK.
Maddy Parsons
Institute of Molecular Biology and Biophysics · RUKing's College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell adhesion to extracellular matrix proteins or to other cells is essential for the control of embryonic development, tissue integrity, immune function and wound healing.  Adhesions are tightly spatially regulated structures containing over a hundred different proteins that co-ordinate both dynamics and signalling events at these sites. Extensive biochemical and morphological analysis of adhesion types over the past three decades has greatly improved understanding of individual protein contributions to adhesion signalling and, in some cases, dynamics. However, it is becoming increasingly clear that these diverse macromolecular complexes contain a variety of protein sub-networks, as well as distinct sub-domains that likely play important roles in regulating adhesion behaviour. Until recently, resolving these structures, which are often less than a micron in size, was hampered by the limitations of conventional light microscopy. However recent advances in optical techniques and imaging methods have revealed exciting insight into the intricate control of adhesion structure and assembly. Here we provide an overview of the recent data arising from such studies of cell:matrix and cell:cell contact and an overview of the imaging strategies that have been applied to study the intricacies and hierarchy of proteins within adhesions.

Indexed as

Actin CytoskeletonAnimalsCell AdhesionCell Adhesion MoleculesCell-Matrix JunctionsExtracellular MatrixFluorometryHumansMicroscopyCell Adhesion Molecules

Identifiers

PMID21785274
PMCPMC3210303
OpenAlexW1990286161

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.