Evidence map›Paper›PMID 39011458›Full record

ReviewFrontiers in medicine2024

Modeling inherited retinal diseases using human induced pluripotent stem cell derived photoreceptor cells and retinal pigment epithelial cells.

Ivan Seah, Debbie Goh, Animesh Banerjee, Xinyi Su

Abstract readReview
In one paragraph

Review in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Evaluation of mesenchymal stem cells as anFrontiers in cell and developmental biology · 2024
    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.

Ivan SeahTranslational Retinal Research Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Debbie GohDepartment of Ophthalmology, National University Hospital (NUH), Singapore, Singapore.
Animesh BanerjeeTranslational Retinal Research Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.
Xinyi SuTranslational Retinal Research Laboratory, Institute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the discovery of induced pluripotent stem cell (iPSC) technology, there have been many attempts to create cellular models of inherited retinal diseases (IRDs) for investigation of pathogenic processes to facilitate target discovery and validation activities. Consistency remains key in determining the utility of these findings. Despite the importance of consistency, quality control metrics are still not widely used. In this review, a toolkit for harnessing iPSC technology to generate photoreceptor, retinal pigment epithelial cell, and organoid disease models is provided. Considerations while developing iPSC-derived IRD models such as iPSC origin, reprogramming methods, quality control metrics, control strategies, and differentiation protocols are discussed. Various iPSC IRD models are dissected and the scientific hurdles of iPSC-based disease modeling are discussed to provide an overview of current methods and future directions in this field.

Indexed as

induced pluripotent stem cellinherited retinal diseasesorganoidsphotoreceptor cellsretinal pigment epithelium

Identifiers

PMID39011458
PMCPMC11246861

What OpenQuestion holds

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LicenceCC BY
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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.