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Record W4414319101 · doi:10.1093/bjd/ljaf370

Metformin in necrobiotic xanthogranuloma

2025· article· en· W4414319101 on OpenAlexaff
Henning Klapproth, Manuel Huerta Arana, Jan‐Wilm Lackmann, Luisa Bopp, Muhammad Shehryar Hussain, Kerstin Becker, Esther von Stebut, Ramon I. Klein Geltink, Iliana Tantcheva‐Poór, Mario Fabri

Bibliographic record

VenueBritish Journal of Dermatology · 2025
Typearticle
Languageen
FieldMedicine
TopicInfectious Disease Case Reports and Treatments
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersInstitute of Nano Science and TechnologyMedizinische Fakultät, Universität zu KölnDeutsche ForschungsgemeinschaftMazak FoundationFaraday InstitutionHealth Research
KeywordsMetforminMacrophageDiseaseRepurposingGranulomatous diseaseDrug repositioning

Abstract

fetched live from OpenAlex

Necrobiotic xanthogranuloma (NXG) represents a rare granulomatous skin disease characterized by IFN-γ-activated macrophages with limited treatment options. This study shows that metformin not only suppresses IFN-γ-induced macrophage activation, but also induced clinical remission in a patient with NXG. These findings highlight metformin as a promising candidate for therapeutic repurposing in NXG.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.290

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 head0.005
GPT teacher head0.270
Teacher spread0.265 · 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 designCase report
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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