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Record W2144187860 · doi:10.1093/nar/gkh967

A survey of splice variants of the human hypoxanthine phosphoribosyl transferase and DNA polymerase beta genes: products of alternative or aberrant splicing?

2004· article· en· W2144187860 on OpenAlexaff
Adonis Skandalis

Bibliographic record

VenueNucleic Acids Research · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsBrock University
Fundersnot available
KeywordsBiologyspliceRNA splicingGeneticsAlternative splicingGeneSplice site mutationNonsense-mediated decayHypoxanthine-guanine phosphoribosyltransferaseMolecular biologyExonRNAMutant

Abstract

fetched live from OpenAlex

Errors during the pre-mRNA splicing of metazoan genes can degrade the transmission of genetic information, and have been associated with a variety of human diseases. In order to characterize the mutagenic and pathogenic potential of mis-splicing, we have surveyed and quantified the aberrant splice variants in the human hypoxanthine phosphoribosyl transferase (HPRT) and DNA polymerase beta (POLB) in the presence and the absence of the Nonsense Mediated Decay (NMD) pathway, which removes transcripts with premature termination codons. POLB exhibits a high frequency of splice variants (40-60%), whereas the frequency of HPRT splice variants is considerably lower (approximately 1%). Treatment of cells with emetine to inactivate NMD alters both the spectrum and frequency of splice variants of POLB and HPRT. It is not certain at this point, whether POLB and HPRT splice variants are the result of regulated alternative splicing processes or the result of aberrant splicing, but it appears likely that at least some of the variants are the result of splicing errors. Several mechanisms that may contribute to aberrant splicing are discussed.

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)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.060
GPT teacher head0.344
Teacher spread0.284 · 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

Citations21
Published2004
Admission routes1
Has abstractyes

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