Evidence map›Paper›PMID 38682883›Full record

ArticleJournal of microscopy2025

Characterisation and correction of polarisation effects in fluorescently labelled fibres.

Nandini Aggarwal, Richard Marsh, Stefania Marcotti, Tanya J Shaw, Brian Stramer, Susan Cox, Siân Culley

Abstract read
In one paragraph

Article in Journal of microscopy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

7 authors.

Nandini AggarwalRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.
Richard MarshRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.
Stefania MarcottiRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.
Tanya J ShawCentre for Inflammation Biology & Cancer Immunology, School of Immunology & Microbial Sciences, King's College London, London, UK.
Brian StramerRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.
Susan CoxRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.
Siân CulleyRandall Centre for Cell & Molecular Biophysics, King's College London, London, UK.ORCID 0000-0003-2112-0143

Funding

Biotechnology and Biological Sciences Research CouncilH2020 European Research CouncilLeverhulme TrustRoyal SocietyWellcome Trust
6 · The paper itself

Abstract

Many biological structures take the form of fibres and filaments, and quantitative analysis of fibre organisation is important for understanding their functions in both normal physiological conditions and disease. In order to visualise these structures, fibres can be fluorescently labelled and imaged, with specialised image analysis methods available for quantifying the degree and strength of fibre alignment. Here we show that fluorescently labelled fibres can display polarised emission, with the strength of this effect varying depending on structure and fluorophore identity. This can bias automated analysis of fibre alignment and mask the true underlying structural organisation. We present a method for quantifying and correcting these polarisation effects without requiring polarisation-resolved microscopy and demonstrate its efficacy when applied to images of fluorescently labelled collagen gels, allowing for more reliable characterisation of fibre microarchitecture.

Indexed as

CollagenFluorescent DyesImage Processing, Computer-AssistedStaining and LabelingMicroscopy, FluorescenceMicroscopy, PolarizationCollagenFluorescent DyesAlexa Fluor dyescollagenfibre anisotropyfibre detectionfluorescence microscopypolarisation

Identifiers

PMID38682883
PMCPMC11987583

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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.