Evidence map›Paper›PMID 24382708›Full record

ReviewChemphyschem : a European journal of chemical physics and physical chemistry2014

The role of molecular dipole orientation in single-molecule fluorescence microscopy and implications for super-resolution imaging.

Mikael P Backlund, Matthew D Lew, Adam S Backer, Steffen J Sahl, W E Moerner

Abstract readReview
In one paragraph

Review in Chemphyschem : a European journal of chemical physics and physical chemistry, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

  1. Article
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  6. Review
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  8. Self-Blinking Thioflavin T for Super-resolution Imaging.The journal of physical chemistry letters · 2024
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  15. Review
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  18. Imaging nanoscale axial dynamics at the basal plasma membrane.The international journal of biochemistry & cell biology · 2023
    Review
  19. Article
  20. Article

4 more citing papers are in PubMed but not listed here.

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.

Mikael P BacklundDepartment of Chemistry. Stanford University, Stanford, CA 94305 (USA).
Matthew D Lew
Adam S Backer
Steffen J Sahl
W E Moerner

Funding

Three-Dimensional Superresolution Imaging in Living Cells Using Single-Molecule AR01GM085437 · NIGMS · STANFORD UNIVERSITY · PI MOERNER, WILLIAM E · 2008 to 2015
$2.1M
NIGMS NIH HHS R01 GM085437NIGMS NIH HHS R01GM085437
6 · The paper itself

Abstract

Numerous methods for determining the orientation of single-molecule transition dipole moments from microscopic images of the molecular fluorescence have been developed in recent years. At the same time, techniques that rely on nanometer-level accuracy in the determination of molecular position, such as single-molecule super-resolution imaging, have proven immensely successful in their ability to access unprecedented levels of detail and resolution previously hidden by the optical diffraction limit. However, the level of accuracy in the determination of position is threatened by insufficient treatment of molecular orientation. Here we review a number of methods for measuring molecular orientation using fluorescence microscopy, focusing on approaches that are most compatible with position estimation and single-molecule super-resolution imaging. We highlight recent methods based on quadrated pupil imaging and on double-helix point spread function microscopy and apply them to the study of fluorophore mobility on immunolabeled microtubules.

Indexed as

Microscopy, FluorescenceMicrotubulesfluorescence microscopymolecular orientationrotational mobilitysingle-molecule studiessuper-resolution imaging

Identifiers

PMID24382708
PMCPMC3992256

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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.