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Long‐term follow‐up of granulocyte colony‐stimulating factor receptor mutations in patients with severe congenital neutropenia: implications for leukaemogenesis and therapy

2003· article· en· W2041513065 on OpenAlexfundno aff
Phil Ancliff, Rosemary E. Gale, Ri Liesner, Ian Hann, David C. Linch

Bibliographic record

VenueBritish Journal of Haematology · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBlood disorders and treatments
Canadian institutionsnot available
FundersHospital for Sick ChildrenAmgen
KeywordsCongenital NeutropeniaNeutropeniaGranulocyte colony-stimulating factorMutationGranulocyte colony-stimulating factor receptorMedicineMyeloidImmunologyInternal medicineGranulocyteMyeloid leukemiaCancer researchChemotherapyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

Severe congenital neutropenia (SCN) is characterized by profound neutropenia, recurrent severe bacterial infections and maturation arrest in the myeloid lineage. Granulocyte colony-stimulating factor (G-CSF) treatment results in clinical improvement in over 90% of cases. Point mutations of the G-CSF receptor (G-CSFR) have been implicated in the progression of SCN to acute myeloid leukaemia (AML). Data are presented here on the 9-year follow-up of seven patients and the further screening of 18 other cases. One of the two original cases with a G-CSFR mutation has improved clinically; nevertheless, mutant DNA could still be detected at a very low level > 8 years after identification. The second child with a mutation progressed to myelodysplasia/AML 5 years after her mutation was detected. No mutations were found in the 18 new cases. One of three transformed cases had a G-CSFR mutation. This work is in agreement with the suggestion that G-CSFR mutations may provide a survival advantage to haemopoietic stem cells, but argues against the inevitability of leukaemic progression in their presence. Furthermore, the low frequency of G-CSFR mutations in SCN and the importance of regular screening and close clinical and laboratory follow-up if a mutation is found were demonstrated.

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 score0.015
Threshold uncertainty score0.408

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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

Citations45
Published2003
Admission routes1
Has abstractyes

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