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Record W4415719860 · doi:10.70962/jhi.20250181

A <i>WAS</i> promoter variant underlying Wiskott-Aldrich syndrome in two kindreds

2025· article· en· W4415719860 on OpenAlexfundno aff
Pauline Ober, Christelle Lenoir, Arnaud Maillard, Marie‐Gabrielle Vigue, Marjolaine Willems, Sandrine Baron‐Joly, Carole E. Aubert, Eva Maria Tinner, Nathalie Lambert, Iben El Missaoui, Frédéric Parisot, Antoine Fayand, Yoann Seeleuthner, Sylvain Hanein, Tom Le Voyer, Martin Broly, Guilaine Boursier, Jean‐Laurent Casanova, Peng Zhang, Jana Pachlopnik Schmid, Sylvain Latour, Jérémie Rosain

Bibliographic record

VenueJournal of Human Immunity · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsnot available
FundersUniversität ZürichLigue Contre le CancerSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungInstitut National Du CancerFondation du SouffleInstitut National de la Santé et de la Recherche MédicaleFondation pour la Recherche MédicaleSociété Française de lutte contre les Cancers et les leucémies de l'Enfant et de l'AdolescentSCOR Corporate Foundation for ScienceRare Disease FoundationSt. Giles FoundationCentre National de la Recherche ScientifiqueRockefeller UniversityFondation Bettencourt SchuellerAgence Nationale de la RechercheHoward Hughes Medical InstituteFédération Enfants Cancers SantéNational Science Foundation
KeywordsGeneMutationIdentification (biology)AlleleFrameshift mutationPhenotype

Abstract

fetched live from OpenAlex

An ultra-rare noncoding variant (c.-64C>T) in the WAS promoter was identified in four male patients from two unrelated families presenting features of Wiskott-Aldrich syndrome. The patients' cells exhibited reduced WASP expression at both the mRNA and protein levels.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.320
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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