Evidence map›Paper›PMID 40903528›Full record

ReviewNpj imaging2025

Single cell resolution 3D imaging and segmentation within intact live tissues.

Giulia Paci, Pablo Vicente-Munuera, Inés Fernandez-Mosquera, Álvaro Miranda, Katherine Lau, Qingyang Zhang, Ricardo Barrientos, Yanlan Mao

Abstract readReview
In one paragraph

Review in Npj imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 3D epithelial cell topology tunes signaling range to promote precise patterning.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  2. Article
  3. 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

8 authors.

Giulia Paci *Laboratory for Molecular Cell Biology, University College London, London, UK. g.paci@ucl.ac.uk.
Pablo Vicente-Munuera *Laboratory for Molecular Cell Biology, University College London, London, UK. p.munuera@ucl.ac.uk.
Inés Fernandez-MosqueraLaboratory for Molecular Cell Biology, University College London, London, UK.
Álvaro MirandaLaboratory for Molecular Cell Biology, University College London, London, UK.
Katherine LauLaboratory for Molecular Cell Biology, University College London, London, UK.
Qingyang ZhangLaboratory for Molecular Cell Biology, University College London, London, UK.
Ricardo BarrientosLaboratory for Molecular Cell Biology, University College London, London, UK.
Yanlan Mao *Laboratory for Molecular Cell Biology, University College London, London, UK. y.mao@ucl.ac.uk.

Funding

EMBO Long-Term Fellowship ALTF 786-2020EPSRC EP/X03139X/1Leverhulme Trust Project Grant RPG-2020-068Medical Research Council MR/W027437/1
6 · The paper itself

Abstract

Epithelial cells form diverse structures, from squamous spherical organoids to densely packed pseudostratified folded tissues. Quantification of cellular properties in these contexts requires high-resolution deep imaging and computational techniques to achieve truthful three-dimensional (3D) structural features. Here, we describe a detailed step-by-step protocol for sample preparation, imaging and deep-learning-assisted cell segmentation to achieve accurate quantification of fluorescently labelled individual cells in 3D within a live tissue: the Drosophila wing disc. We share the "lessons learned" through troubleshooting 3D imaging, including considerations on the choice of microscopy modality and settings (objective, sample mounting) and available segmentation methods. In addition, we include a computational pipeline alongside custom code to assist replication of the protocol. While we focus on the segmentation of cell outlines from membrane labelling in the Drosophila wing disc, we believe it will be valuable for studying other tissues that demand complex analysis in 3D.

Identifiers

PMID40903528
PMCPMC12408837

What OpenQuestion 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 OpenQuestion graph.