Evidence map›Paper›PMID 40336952›Full record

ArticleJournal of tissue engineering

Development of an iPSC-derived immunocompetent skin model for identification of skin sensitizing substances.

Marla Dubau, Tarada Tripetchr, Lava Mahmoud, Fabian Schumacher, Burkhard Kleuser

Abstract read
In one paragraph

Article in Journal of tissue engineering. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

5 authors.

Marla DubauFreie Universität Berlin, Department of Pharmacology and Toxicology, Institute of Pharmacy, Berlin, Germany.
Tarada TripetchrFreie Universität Berlin, Department of Pharmacology and Toxicology, Institute of Pharmacy, Berlin, Germany.
Lava MahmoudFreie Universität Berlin, Department of Pharmacology and Toxicology, Institute of Pharmacy, Berlin, Germany.
Fabian SchumacherFreie Universität Berlin, Department of Pharmacology and Toxicology, Institute of Pharmacy, Berlin, Germany.ORCID https://orcid.org/0000-0001-8703-3275
Burkhard KleuserFreie Universität Berlin, Department of Pharmacology and Toxicology, Institute of Pharmacy, Berlin, Germany.ORCID https://orcid.org/0000-0002-1888-9595

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of immunocompetent skin models marks a significant advancement in in vitro methods for detecting skin sensitizers while adhering to the 3R principles, which aim to reduce, refine, and replace animal testing. This study introduces for the first time an advanced immunocompetent skin model constructed entirely from induced pluripotent stem cell (iPSC)-derived cell types, including fibroblasts (iPSC-FB), keratinocytes (iPSC-KC), and fully integrated dendritic cells (iPSC-DC). To evaluate the skin model's capacity, the model was treated topically with a range of well-characterized skin sensitizers varying in potency. The results indicate that the iPSC-derived immunocompetent skin model successfully replicates the physiological responses of human skin, offering a robust and reliable alternative to animal models for skin sensitization testing, allowing detection of extreme and even weak sensitizers. By addressing critical aspects of immune activation and cytokine signaling, this model provides an ethical, comprehensive tool for regulatory toxicology and dermatological research.

Indexed as

adverse outcome pathwaycytokine secretiondendritic cellsimmunocompetent skin modelinduced pluripotent stem cellsskin sensitizationsphingolipids

Identifiers

PMID40336952
PMCPMC12056326

What OpenQuestion holds

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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.