ReviewBiochimica et biophysica acta2014
Förster resonance energy transfer - an approach to visualize the spatiotemporal regulation of macromolecular complex formation and compartmentalized cell signaling.
Review in Biochimica et biophysica acta, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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.
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.
Who cites it
4 citing papers in PubMed, 10 citations in OpenAlex.
- Nanoparticle-based probes to enable noninvasive imaging of proteolytic activity for cancer diagnosis.Nanomedicine (London, England) · 2016Review
- Methods to Study Mrp4-containing Macromolecular Complexes in the Regulation of Fibroblast Migration.Journal of visualized experiments : JoVE · 2016Article
- A novel small-molecule inhibitor of influenza A virus acts by suppressing PA endonuclease activity of the viral polymerase.Scientific reports · 2016Article
- PKA and actin play critical roles as downstream effectors in MRP4-mediated regulation of fibroblast migration.Cellular signalling · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundSignaling messengers and effector proteins provide an orchestrated molecular machinery to relay extracellular signals to the inside of cells and thereby facilitate distinct cellular behaviors. Formations of intracellular macromolecular complexes and segregation of signaling cascades dynamically regulate the flow of a biological process. SCOPE OF REVIEW: In this review, we provide an overview of the development and application of FRET technology in monitoring cyclic nucleotide-dependent signalings and protein complexes associated with these signalings in real time and space with brief mention of other important signaling messengers and effector proteins involved in compartmentalized signaling. MAJOR
conclusionsThe preciseness, rapidity and specificity of cellular responses indicate restricted alterations of signaling messengers, particularly in subcellular compartments rather than globally. Not only the physical confinement and selective depletion, but also the intra- and inter-molecular interactions of signaling effectors modulate the direction of signal transduction in a compartmentalized fashion. To understand the finer details of various intracellular signaling cascades and crosstalk between proteins and other effectors, it is important to visualize these processes in live cells. Förster Resonance Energy Transfer (FRET) has been established as a useful tool to do this, even with its inherent limitations. GENERAL SIGNIFICANCE: FRET technology remains as an effective tool for unraveling the complex organization and distribution of various endogenous signaling proteins, as well as the spatiotemporal dynamics of second messengers inside a single cell to distinguish the heterogeneity of cell signaling under normal physiological conditions and during pathological events.
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What OpenQuestion holds
Registered trials
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.