Evidence map›Paper›PMID 39271788›Full record

ArticleScientific reports2024

Quantitative and comparative assessment of dyes and protocols for rapid ex vivo microscopy of fresh tissues.

Ivan Bozic, Madeline R Behr, J Quincy Brown

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 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

3 authors.

Ivan BozicDepartment of Biomedical Engineering, Tulane University, New Orleans, 70118, USA.
Madeline R BehrDepartment of Biomedical Engineering, Tulane University, New Orleans, 70118, USA.
J Quincy BrownDepartment of Biomedical Engineering, Tulane University, New Orleans, 70118, USA. jqbrown@tulane.edu.

Funding

High speed automated intraoperative microscopy of the prostate circumference to ensure tumor-free margins in radical prostatectomyR01CA222831 · NCI · TULANE UNIVERSITY OF LOUISIANA · PI BROWN, JONATHAN QUINCY · 2018 to 2021
$1.6M
NIH HHS R01 CA222831
6 · The paper itself

Abstract

Using ex vivo microscopy, virtual pathology can improve histological procedures by providing pathology images in near real-time without tissue destruction. Several emerging and promising approaches leverage fast-acting small-molecule fluorescent stains to replicate traditional pathology structural contrast, combined with rapid optical sectioning microscopes. However, several vital challenges must be addressed to translate virtual pathology into the clinical environment. One such challenge is selecting robust, reliable, and repeatable staining protocols that can be adopted across institutions. In this work, we addressed the effects of dye selection and staining protocol on image quality in rapid point-of-care imaging settings. For this purpose, we used structured illumination microscopy to evaluate fluorescent dyes currently used in the field of ex vivo virtual pathology, in particular, studying the effects of staining protocol and temporal and photostability on image quality. We observed that DRAQ5 and SYBR gold provide higher image quality than TO-PRO3 and RedDot1 in the nuclear channel and Eosin Y515 in the extracellular/cytoplasmic channel than Atto488. Further, we found that TO-PRO3 and Eosin Y515 are less photostable than other dyes. Finally, we identify the optimal staining protocol for each dye and demonstrate pan-species generalizability.

Indexed as

Fluorescent DyesStaining and LabelingAnimalsHumansMicroscopy, FluorescenceFluorescent Dyes

Identifiers

PMID39271788
PMCPMC11399393

What OpenQuestion holds

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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.