Evidence map›Paper›PMID 17259276›Full record

ArticleBiophysical journal2007

Deconvolving single-molecule intensity distributions for quantitative microscopy measurements.

Sarah A Mutch, Bryant S Fujimoto, Christopher L Kuyper, Jason S Kuo, Sandra M Bajjalieh, Daniel T Chiu

Abstract readEvaluation Study
In one paragraph

Article in Biophysical journal, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

0numbers the graph read from it
0cells of the map it votes in
55citing 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

55 citing papers in PubMed.

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  19. Rigor and reproducibility: status and challenges for single vesicle analysis.Extracellular vesicles and circulating nucleic acids · 2022
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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

6 authors.

Sarah A MutchDepartment of Chemistry, University of Washington, Seattle, Washington 98195, USA.
Bryant S Fujimoto
Christopher L Kuyper
Jason S Kuo
Sandra M Bajjalieh
Daniel T Chiu

Funding

High-Resolution Analysis of Synaptic ProteinsR01NS052637 · NINDS · UNIVERSITY OF WASHINGTON · PI CHIU, DANIEL T · 2005 to 2013
$3.2M
NINDS NIH HHS NS052637NINDS NIH HHS R01 NS052637
6 · The paper itself

Abstract

In fluorescence microscopy, images often contain puncta in which the fluorescent molecules are spatially clustered. This article describes a method that uses single-molecule intensity distributions to deconvolve the number of fluorophores present in fluorescent puncta as a way to "count" protein number. This method requires a determination of the correct statistical relationship between the single-molecule and single-puncta intensity distributions. Once the correct relationship has been determined, basis histograms can be generated from the single-molecule intensity distribution to fit the puncta distribution. Simulated data were used to demonstrate procedures to determine this relationship, and to test the methodology. This method has the advantages of single-molecule measurements, providing both the mean and variation in molecules per puncta. This methodology has been tested with the avidin-biocytin binding system for which the best-fit distribution of biocytins in the sample puncta was in good agreement with a bulk determination of the avidin-biocytin binding ratio.

Indexed as

Models, BiologicalAlgorithmsAnimalsAvidinBrainCells, CulturedComputer SimulationImage Interpretation, Computer-AssistedLysineModels, StatisticalRatsStatistical DistributionsSynaptic VesiclesAvidinbiocytinLysine

Identifiers

PMID17259276
PMCPMC1831712

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.