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Record W2188373415

Novel variants in the hotspot region of RP1 in South African patients with retinitis pigmentosa.

2006· article· en· W2188373415 on OpenAlexaboutno aff
Lisa Roberts, Lecia Bartmann, Raj Ramesar, Jacquie Greenberg

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsRetinitis pigmentosaGeneticsBiologyMutation frequencyHigh Resolution MeltFounder effectRhodopsinMutationGenePolymerase chain reactionHaplotypeGenotypeRetinalBotany
DOInot available

Abstract

fetched live from OpenAlex

PURPOSE: Mutations in the hotspot of RP1 are reportedly responsible for 4-7% of autosomal dominant retinitis pigmentosa (ADRP) in the United States, Canada, and Europe. South Africa (SA) has unique subpopulations and a comparatively low observed frequency of rhodopsin mutations, which lead to this investigation of the contribution of RP1 mutations to the ADRP disease burden in SA. METHODS: Fifty-seven affected, unrelated South African individuals with ADRP were selected for mutation screening of the RP1 hotspot, using denaturing high performance liquid chromatography (HPLC). Variants were identified by direct sequencing, after which cosegregation analysis and population frequency studies were performed using restriction fragment length polymorphism analysis, nondenaturing HPLC, or denaturing HPLC. RESULTS: Three mutations were identified, including two novel sequence variations and the common Arg677X mutation. A wide spectrum of disease severity was observed in the families with these RP1 gene mutations. Two nondisease-associated polymorphisms were also detected, with the frequency of one of these variants being significantly low in Black African individuals. CONCLUSIONS: Mutations were only found in Caucasian families with origins in the British Isles. The observed RP1 mutation frequency of 5.3% in SA ADRP patients is comparable to the frequency reported in other populations.

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 score0.009
Threshold uncertainty score0.237

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 head0.009
GPT teacher head0.173
Teacher spread0.164 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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