Evidence map›Paper›PMID 39720013›Full record

ArticleJournal of biomedical optics2024

Obtaining super-resolved images at the mesoscale through super-resolution radial fluctuations.

Mollie Brown, Shannan Foylan, Liam M Rooney, Gwyn W Gould, Gail McConnell

Abstract read
In one paragraph

Article in Journal of biomedical optics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mollie BrownUniversity of Strathclyde, Department of Physics, Glasgow, United Kingdom.ORCID 0009-0009-6433-2470
Shannan FoylanUniversity of Strathclyde, Strathclyde Institute of Pharmacy and Biomedical Sciences, Glasgow, United Kingdom.ORCID 0000-0001-8565-9207
Liam M RooneyUniversity of Strathclyde, Strathclyde Institute of Pharmacy and Biomedical Sciences, Glasgow, United Kingdom.ORCID 0000-0002-2237-501X
Gwyn W GouldUniversity of Strathclyde, Strathclyde Institute of Pharmacy and Biomedical Sciences, Glasgow, United Kingdom.ORCID 0000-0001-6571-2875
Gail McConnellUniversity of Strathclyde, Strathclyde Institute of Pharmacy and Biomedical Sciences, Glasgow, United Kingdom.ORCID 0000-0002-7213-0686

Funding

Medical Research Council MR/K015583/1
6 · The paper itself

Abstract

Significance: Current super-resolution imaging techniques allow for a greater understanding of cellular structures; however, they are often complex or only have the ability to image a few cells at once. This small field of view (FOV) may not represent the behavior across the entire sample, and manual selection of regions of interest (ROIs) may introduce bias. It is possible to stitch and tile many small ROIs; however, this can result in artifacts across an image. Aim: The aim is to achieve accurate super-resolved images across a large FOV ( Approach: We have applied super-resolution radial fluctuations processing in conjunction with the Mesolens, which has the unusual combination of a low-magnification and high numerical aperture, to obtain super-resolved images. Results: We demonstrate it is possible to achieve images with a resolution of Conclusions: We provide a simple method for obtaining accurate super-resolution images over a large FOV, allowing for a simultaneous understanding of both subcellular structures and their large-scale interactions.

Indexed as

Image Processing, Computer-AssistedAlgorithmsHumansMicroscopy, Fluorescencediffraction-limitedMesolensmicroscopysuper-resolution

Identifiers

PMID39720013
PMCPMC11667203

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.