Evidence map›Paper›PMID 27658367›Full record

ArticleNature communications2016

Two-dimensional flow nanometry of biological nanoparticles for accurate determination of their size and emission intensity.

Stephan Block, Björn Johansson Fast, Anders Lundgren, Vladimir P Zhdanov, Fredrik Höök

Abstract read
In one paragraph

Article in Nature communications, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  4. Multiparametric functional characterization of individual lipid nanoparticles using surface-sensitive light-scattering microscopy.Proceedings of the National Academy of Sciences of the United States of America · 2025
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  10. Review
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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.

Stephan BlockDepartment of Physics, Division of Biological Physics, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.
Björn Johansson FastDepartment of Physics, Division of Biological Physics, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.
Anders LundgrenDepartment of Physics, Division of Biological Physics, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.
Vladimir P ZhdanovDepartment of Physics, Division of Biological Physics, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.
Fredrik HöökDepartment of Physics, Division of Biological Physics, Chalmers University of Technology, Gothenburg SE-412 96, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Biological nanoparticles (BNPs) are of high interest due to their key role in various biological processes and use as biomarkers. BNP size and composition are decisive for their functions, but simultaneous determination of both properties with high accuracy remains challenging. Optical microscopy allows precise determination of fluorescence/scattering intensity, but not the size of individual BNPs. The latter is better determined by tracking their random motion in bulk, but the limited illumination volume for tracking this motion impedes reliable intensity determination. Here, we show that by attaching BNPs to a supported lipid bilayer, subjecting them to hydrodynamic flows and tracking their motion via surface-sensitive optical imaging enable determination of their diffusion coefficients and flow-induced drifts, from which accurate quantification of both BNP size and emission intensity can be made. For vesicles, the accuracy of this approach is demonstrated by resolving the expected radius-squared dependence of their fluorescence intensity for radii down to 15 nm.

Identifiers

PMID27658367
PMCPMC5036154

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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.