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Record W7073884813

Effects of MECP2 Mutation Type, Location and X-inactivation in Modulating Rett Syndrome Phenotype

2003· article· en· W7073884813 on OpenAlexaff

Bibliographic record

VenueUWA Profiles and Research Repository (University of Western Australia) · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsCentre for Global Health Research
Fundersnot available
KeywordsRett syndromeMECP2MutationPhenotypeMutation testingClinical phenotypeFrameshift mutation
DOInot available

Abstract

fetched live from OpenAlex

Rett syndrome (RTT) is a clinically defined disorder that describes a subset of patients with mutations in the X-linked MECP2 gene. However, there is a high degree of variability in the clinical phenotypes produced by mutations in MECP2, even amongst classical RTT patients. In a large-scale screening project, this variability has been examined by looking at the effects of mutation type, functional domain affected and X-inactivation. Mutations have been identified in 60% of RTT patients in this study (25% of whom were atypical), including 23 novel mutations and polymorphisms. More mutations were found in classical patients (63%) compared to atypical patients (44%). All of the pathogenic mutations were de novo in patients for whom parent DNA was available for screening. A composite phenotype score was developed, based on the recommendations for reporting clinical features in RTT of an international collaborative group. This score proved useful for summarising phenotypic severity, but did not correlate with mutation type, domain affected or X-inactivation, probably due to complex interactions between all three. Other correlations suggested that truncating mutations and mutations affecting the methyl-CpG-binding domain tend to lead to a more severe phenotype. Skewed X-inactivation was found in a large proportion (43%) of our patients, particularly in those with truncating mutations and mutations affecting the MBD. It is therefore likely that X-inactivation does modulate the phenotype in RTT. © 2003 Wiley-Liss, Inc.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.593
Threshold uncertainty score0.230

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 head0.023
GPT teacher head0.273
Teacher spread0.251 · 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

Citations4
Published2003
Admission routes1
Has abstractyes

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