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Record W2114561002 · doi:10.1002/ajmg.10635

Reevaluation of a genetic model for the development of exostosis in hereditary multiple exostosis

2002· article· en· W2114561002 on OpenAlexafffund
Catherine Rhoades Hall, William G. Cole, Richard Haynes, Jacqueline T. Hecht

Bibliographic record

VenueAmerican Journal of Medical Genetics · 2002
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsHospital for Sick Children
FundersHospital for Sick ChildrenShriners Hospitals for Children
KeywordsHereditary multiple exostosesExostosisLoss of heterozygosityExtracellular matrixGeneticsBiologyMutationHeparan sulfateSomatic cellHomeoboxGeneGermlineAlleleGene expressionAnatomyCell

Abstract

fetched live from OpenAlex

EXT1 and EXT2 are genes that have been shown to cause hereditary multiple exostosis (HME), a syndrome marked by the formation of bony growths juxtaposed to the growth plate. These genes are members of a growing family of proteins with glycosyltransferase activity required for the synthesis of heparan sulfate chains. This protein activity is predicted to play a role in the expression of proteoglycans on the cell surface and in the extracellular matrix. We and others have previously suggested that a two-hit mutational model applies to the development of an exostosis where a germline mutation coupled with a somatic mutation results in the loss of EXT1 or EXT2 function and subsequent tumor formation. We report the direct sequencing and loss of heterozygosity (LOH) analysis of 12 exostoses from 10 HME families, 4 solitary exostoses, and their corresponding constitutional DNA. Of the 16 exostoses screened, we find only one solitary case in which two somatic mutations, a deletion and an LOH, are present. This provides limited support for the two-hit hypothesis involving the EXT1 and EXT2 genes for the development of an exostosis. Alternative models are developed based on the functional significance of EXT proteins in heparan sulfate biosynthesis.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.313

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.068
GPT teacher head0.319
Teacher spread0.250 · 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 designOther design
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

Citations57
Published2002
Admission routes2
Has abstractyes

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