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Record W7117546271 · doi:10.1111/exd.70191

Mimicking Darier Disease In Vitro: A Human Epidermal Organoid Approach

2025· article· en· W7117546271 on OpenAlexaff
R. P. Agarwal, Erika Parente, Simon Müller, Elisabeth A. Kappos, Tanja Dittmar, M. Kunz, Roni P. Dodiuk‐Gad, Nisim Asayag, Johann E. Gudjonsson, Beda Mühleisen, Emmanuel Contassot, Alexander Andreas Navarini

Bibliographic record

VenueExperimental Dermatology · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and rare skin diseases.
Canadian institutionsUniversity of Toronto
FundersUniversität Basel
KeywordsDarier's diseaseOrganoidKeratinocytePhenotypeDarier DiseaseEpidermis (zoology)TranscriptomeDiseaseCell

Abstract

fetched live from OpenAlex

Darier disease (DD) is a rare genetic disorder caused by mutations in the ATP2A2 gene, resulting in calcium dysregulation and impaired keratinocyte adhesion. Due to the paucity of suitable models, understanding the molecular mechanisms of DD has been challenging. In this study, we developed a human epidermal organoid model derived from DD patient keratinocytes to investigate the molecular and phenotypic features of the disease. The model recapitulates key aspects of DD pathology, including acantholysis, desmosomal dysfunction and barrier disruption, with mislocalisation of desmosomal proteins. Furthermore, the transcriptomic landscape of DD organoids reflected broad perturbations in epidermal structure. Enrichment of pathways associated with epidermal development, cell adhesion, cell migration and keratinocyte differentiation underscored the multifaceted disruption of epithelial integrity and homeostasis that defines DD pathology. Our work demonstrates that epidermal organoids derived from patients with Darier disease are a valuable model for studying DD. They provide a platform to study complex genetic epidermal disorders and personalised drug screening.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.270
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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