Evidence map›Paper›PMID 23473488›Full record

ArticleBiophysical journal2013

Aggregation distributions on cells determined by photobleaching image correlation spectroscopy.

Giuseppe D Ciccotosto, Noga Kozer, Timothy T Y Chow, James W M Chon, Andrew H A Clayton

Abstract 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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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.

Giuseppe D CiccotostoDepartment of Pathology and Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Australia.
Noga Kozer
Timothy T Y Chow
James W M Chon
Andrew H A Clayton

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The organization of molecules into macromolecular (nanometer scale), supramolecular complexes (submicron-to-micron scale), and within subcellular domains, is an important architectural principle of cellular biology and biochemistry. Determining the precise nature and distribution of complexes within the cellular milieu is a challenging biophysical problem. Time-series analysis of laser scanning confocal microscopy images by image correlation spectroscopy (ICS) or fluctuation moments methods provides information on aggregation, flow, and dynamics of fluorescently tagged macromolecules. All the methods to date require a brightness standard to relate the experimental data to absolute aggregation. In this article, we show that ICS as a function of gradual photobleaching is a sensitive indicator of aggregation distribution on the submicron scale. Specifically, in photobleaching ICS, the extent of nonlinearity of the apparent cluster density as a function of bleaching is related to the size of clusters. The analysis is tested using computer simulations on model aggregate systems and then applied to an experimental determination of Aβ peptide aggregation on nerve cells. The analysis reveals time-dependent increases in Aβ1-42 peptide aggregation. Globally, the datasets could be described by a monomer-dimer-tetramer-hexamer or a monomer-dimer-trimer-pentamer model. The results demonstrate the utility of photobleaching with ICS for determining aggregation states on the supramolecular scale in intact cells without the requirement for a brightness standard.

Indexed as

Computer SimulationPhotobleachingProtein MultimerizationAmyloid beta-PeptidesAnimalsFluorescent DyesMiceMice, Inbred C57BLMicroscopy, ConfocalNeuronsPeptide FragmentsSpectrometry, FluorescenceAmyloid beta-Peptidesamyloid beta-protein (1-42)Fluorescent DyesPeptide Fragments

Identifiers

PMID23473488
PMCPMC3870908

What OpenQuestion holds

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Registered trials

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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.