Evidence map›Paper›PMID 26035859›Full record

ReviewDisease models & mechanisms2015

Cellular models and therapies for age-related macular degeneration.

David L Forest, Lincoln V Johnson, Dennis O Clegg

Abstract readReview
In one paragraph

Review in Disease models & mechanisms, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.

0numbers the graph read from it
0cells of the map it votes in
47citing 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

47 citing papers in PubMed.

  1. Review
  2. Formulation Development andCurrent drug delivery · 2026
    Article
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  9. Review
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  18. Role of In Vitro Models for Development of Ophthalmic Delivery Systems.Critical reviews in therapeutic drug carrier systems · 2021
    Review
  19. Article
  20. 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.

David L ForestMolecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106-9625, USA.
Lincoln V JohnsonMolecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106-9625, USA.
Dennis O CleggMolecular, Cellular, and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA 93106-9625, USA dennis.clegg@lifesci.ucsb.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Age-related macular degeneration (AMD) is a complex neurodegenerative visual disorder that causes profound physical and psychosocial effects. Visual impairment in AMD is caused by the loss of retinal pigmented epithelium (RPE) cells and the light-sensitive photoreceptor cells that they support. There is currently no effective treatment for the most common form of this disease (dry AMD). A new approach to treating AMD involves the transplantation of RPE cells derived from either human embryonic or induced pluripotent stem cells. Multiple clinical trials are being initiated using a variety of cell therapies. Although many animal models are available for AMD research, most do not recapitulate all aspects of the disease, hampering progress. However, the use of cultured RPE cells in AMD research is well established and, indeed, some of the more recently described RPE-based models show promise for investigating the molecular mechanisms of AMD and for screening drug candidates. Here, we discuss innovative cell-culture models of AMD and emerging stem-cell-based therapies for the treatment of this vision-robbing disease.

Indexed as

Models, BiologicalStem Cell TransplantationAnimalsHumansMacular DegenerationAMDCell-culture modelshESCiPSCRPEStem-cell therapy

Identifiers

PMID26035859
PMCPMC4415892

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.