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Record W4411750799 · doi:10.1093/bjd/ljaf257

Comprehensive profiling of the mutational landscape of hidradenoma papilliferum validates key role of alterations in the phosphoinositide 3-kinase/AKT pathway

2025· article· en· W4411750799 on OpenAlexfundno aff
Saamin Cheema, Louise van der Weyden, Kim Ping Wong, Martin Del Castillo Velasco‐Herrera, Jamie Billington, Ian Vermes, Elizabeth Anderson, Laura Allen, Nicolas de Saint Aubain, Michiel P J van der Horst, Ahmed Al‐Omari, Carolin Mogler, Carlos Monteagudo, Derek Frew, Steven D. Billings, Mark J. Arends, Ingrid Ferreira, Thomas Brenn, David J. Adams

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldMedicine
TopicCancer and Skin Lesions
Canadian institutionsnot available
FundersMedical Research Council CanadaWellcome Trust
KeywordsPI3K/AKT/mTOR pathwayHidradenomaBiologyPathogenesisGeneCancer researchGeneticsProtein kinase BComputational biologyBioinformaticsSignal transductionImmunology

Abstract

fetched live from OpenAlex

Comprehensive characterization of the mutational landscape of hidradenoma papilliferum (HP) identified PIK3CA and PIK3R1 as mutually exclusive driver genes. Taken together with the mutation of other genes involved in phosphoinositide 3-kinase/AKT signalling, our findings confirm a key role of the alteration of this pathway in the pathogenesis of HP. The absence of a significant presence of human papillomavirus (HPV) sequences suggests that HPV is not involved in the aetiology of HP.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.218

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 head0.009
GPT teacher head0.258
Teacher spread0.249 · 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 designObservational
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

Citations1
Published2025
Admission routes1
Has abstractyes

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