Evidence map›Paper›PMID 23280111›Full record

ArticleMethods in enzymology2013

Fluorescence fluctuation approaches to the study of adhesion and signaling.

Alexia I Bachir, Kristopher E Kubow, Alan R Horwitz

Abstract read
In one paragraph

Article in Methods in enzymology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Alexia I BachirDepartment of Cell Biology, University of Virginia, Charlottesville, Virginia, USA. ab8su@virginia.edu
Kristopher E Kubow
Alan R Horwitz

Funding

Cancer Research Training Program: From Molecular Mechanisms to Therapeutic StrategiesT32CA009109 · NCI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Andrew Carl Dudley, Melanie R Rutkowski · 1985 to 2026
$13.9M
DETERMINANTS OF MYOGENIC MEMBRANE PHENOMENAR01GM023244 · NIGMS · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI HORWITZ, ALAN F. "RICK" · 1985 to 2014
$6.7M
NCI NIH HHS T32 CA009109NIGMS NIH HHS R01 GM023244
6 · The paper itself

Abstract

Cell-matrix adhesions are large, multimolecular complexes through which cells sense and respond to their environment. They also mediate migration by serving as traction points and signaling centers and allow the cell to modify the surroucnding tissue. Due to their fundamental role in cell behavior, adhesions are germane to nearly all major human health pathologies. However, adhesions are extremely complex and dynamic structures that include over 100 known interacting proteins and operate over multiple space (nm-μm) and time (ms-min) regimes. Fluorescence fluctuation techniques are well suited for studying adhesions. These methods are sensitive over a large spatiotemporal range and provide a wealth of information including molecular transport dynamics, interactions, and stoichiometry from a single time series. Earlier chapters in this volume have provided the theoretical background, instrumentation, and analysis algorithms for these techniques. In this chapter, we discuss their implementation in living cells to study adhesions in migrating cells. Although each technique and application has its own unique instrumentation and analysis requirements, we provide general guidelines for sample preparation, selection of imaging instrumentation, and optimization of data acquisition and analysis parameters. Finally, we review several recent studies that implement these techniques in the study of adhesions.

Indexed as

Signal TransductionFluorescenceFluorescent DyesProteinsSpectrometry, FluorescenceFluorescent DyesProteins

Identifiers

PMID23280111
PMCPMC3693452

What OpenQuestion holds

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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.