Evidence map›Paper›PMID 35982061›Full record

ArticleNature communications2022

Multiscale light-sheet organoid imaging framework.

Gustavo de Medeiros, Raphael Ortiz, Petr Strnad, Andrea Boni, Franziska Moos, Nicole Repina, Ludivine Challet Meylan, Francisca Maurer, Prisca Liberali

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing 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

66 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Proceedings of the ... AAAI Conference on Artificial Intelligence. AAAI Conference on Artificial Intelligence · 2026
    Article
  15. Multiscale imaging of polarity in bovine oviductal organoids.Frontiers in cell and developmental biology · 2026
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

6 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

9 authors.

Gustavo de MedeirosFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.ORCID 0000-0001-5877-3012
Raphael OrtizFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Petr StrnadFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland. petr.strnad@viventis-microscopy.com.
Andrea BoniFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Franziska MoosFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Nicole RepinaFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Ludivine Challet MeylanFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Francisca MaurerFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland.
Prisca LiberaliFriedrich Miescher Institute for Biomedical Research (FMI) Maulbeerstrasse 66, 4058, Basel, Switzerland. prisca.liberali@fmi.ch.ORCID 0000-0003-0695-6081

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organoids provide an accessible in vitro system to mimic the dynamics of tissue regeneration and development. However, long-term live-imaging of organoids remains challenging. Here we present an experimental and image-processing framework capable of turning long-term light-sheet imaging of intestinal organoids into digital organoids. The framework combines specific imaging optimization combined with data processing via deep learning techniques to segment single organoids, their lumen, cells and nuclei in 3D over long periods of time. By linking lineage trees with corresponding 3D segmentation meshes for each organoid, the extracted information is visualized using a web-based "Digital Organoid Viewer" tool allowing combined understanding of the multivariate and multiscale data. We also show backtracking of cells of interest, providing detailed information about their history within entire organoid contexts. Furthermore, we show cytokinesis failure of regenerative cells and that these cells never reside in the intestinal crypt, hinting at a tissue scale control on cellular fidelity.

Indexed as

IntestinesOrganoidsImage Processing, Computer-Assisted

Identifiers

PMID35982061
PMCPMC9388485

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.