Evidence map›Paper›PMID 34219165›Full record

ReviewDisease models & mechanisms2021

Advancing lung organoids for COVID-19 research.

Jelte van der Vaart, Mart M Lamers, Bart L Haagmans, Hans Clevers

Abstract readReview
In one paragraph

Review in Disease models & mechanisms, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
–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

36 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Frontiers in immunology · 2021
    Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Methods and Models for StudyingInternational journal of molecular sciences · 2024
    Review
  7. Article
  8. Modeling Liver Development and Disease in a Dish.International journal of molecular sciences · 2023
    Review
  9. Article
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Review
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

4 authors.

Jelte van der VaartOncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Centre, Uppsalalaan 8, Utrecht 3584 CT, The Netherlands.ORCID 0000-0002-4126-8420
Mart M LamersViroscience Department, Erasmus University Medical Centre, Rotterdam 3015 GD, The Netherlands.ORCID 0000-0002-1431-4022
Bart L HaagmansViroscience Department, Erasmus University Medical Centre, Rotterdam 3015 GD, The Netherlands.ORCID 0000-0001-6221-2015
Hans CleversOncode Institute, Hubrecht Institute, Royal Netherlands Academy of Arts and Sciences and University Medical Centre, Uppsalalaan 8, Utrecht 3584 CT, The Netherlands.ORCID 0000-0002-3077-5582

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has emphasised the need to develop effective treatments to combat emerging viruses. Model systems that poorly represent a virus' cellular environment, however, may impede research and waste resources. Collaborations between cell biologists and virologists have led to the rapid development of representative organoid model systems to study severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We believe that lung organoids, in particular, have advanced our understanding of SARS-CoV-2 pathogenesis, and have laid a foundation to study future pandemic viruses and develop effective treatments.

Indexed as

Models, BiologicalSARS-CoV-2AnimalsCOVID-19HumansLungOrganoidsPandemicsPulmonary AlveoliResearch Design

Identifiers

PMID34219165
PMCPMC8272930

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.