Evidence map›Paper›PMID 36214410›Full record

ArticleDevelopment (Cambridge, England)2022

Approaches to benchmark and characterize in vitro human model systems.

Charlie J Childs, Madeline K Eiken, Jason R Spence

Open access · bronzeAbstract read
In one paragraph

Article in Development (Cambridge, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Review
  3. Cancer metastasisFrontiers in bioengineering and biotechnology · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. 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

3 authors at 1 institution in 1 country.

Charlie J ChildsDepartment of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.ORCID 0000-0002-4480-2625
Madeline K EikenDepartment of Biomedical Engineering, University of Michigan College of Engineering, Ann Arbor, MI 48109, USA.
Jason R SpenceDepartment of Cell and Developmental Biology, University of Michigan Medical School, Ann Arbor, MI 48109, USA.ORCID 0000-0001-7869-3992
University of Michigan · US

Funding

Niche support of human intestinal stem cellsU01DK103141 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SPENCE, JASON · 2014 to 2023
$3.9M
NIDDK NIH HHS U01 DK103141
6 · The paper itself

Abstract

In vitro human models, such as gastruloids and organoids, are complex three-dimensional (3D) structures often consist of cells from multiple germ layers that possess some attributes of a developing embryo or organ. To use these models to interrogate human development and organogenesis, these 3D models must accurately recapitulate aspects of their in vivo counterparts. Recent advances in single-cell technologies, including sequencing and spatial approaches, have enabled efforts to better understand and directly compare organoids with native tissues. For example, single-cell genomic efforts have created cell and organ atlases that enable benchmarking of in vitro models and can also be leveraged to gain novel biological insights that can be used to further improve in vitro models. This Spotlight discusses the state of current in vitro model systems, the efforts to create large publicly available atlases of the developing human and how these data are being used to improve organoids. Limitations and perspectives on future efforts are also discussed.

Indexed as

BenchmarkingOrganoidsHumansOrganogenesisCell atlasHuman developmentModel systems

Identifiers

PMID36214410
PMCPMC10906492
OpenAlexW4303986919

What OpenQuestion holds

Textmetadata
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.