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Record W1918246687 · doi:10.1002/ajmg.c.31362

Molecular Mechanisms of Childhood Overgrowth

2013· article· en· W1918246687 on OpenAlexfundno aff
Katrina Tatton‐Brown, Rosanna Weksberg

Bibliographic record

VenueAmerican Journal of Medical Genetics Part C Seminars in Medical Genetics · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic Syndromes and Imprinting
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsPI3K/AKT/mTOR pathwayPTENGeneBiologySomatic cellCell biologyGeneticsSignal transduction

Abstract

fetched live from OpenAlex

This issue of the Seminar Series C is dedicated to the molecular mechanisms of childhood overgrowth and celebrates the last decade of unprecedented gene discovery. Constitutional gene disorders, somatic gene disorders and imprinting dysregulation are each considered. The constitutional overgrowth genes discussed include NSD1, EZH2, GPC3, DIS3L2, and PTEN whilst the somatic overgrowth genes include AKT3, PIK3R2, and PIK3CA. Abnormalities of imprinting, exemplified by disruption of the (epi)genetic regulation of the imprinted 11p15 gene cluster, constitutes the final section of this issue. Many of the genes discussed in this issue encode components of the PI3K/mTOR growth regulatory pathway. This signaling cascade consists of dual, parallel branches, anchored by the serine-threonine kinase, mTOR, and has diverse downstream effects including inhibition of apoptosis, activation of protein synthesis, and enhanced cell survival. Activation of the PI3K/mTOR pathway promotes growth whereas inhibition, or abrogation, results in decreased cellular growth. Despite the rapid advances of the last decade, there is still an enormous amount to discover. We hope that some of the work reviewed in this issue will facilitate the next decade's discoveries and we look forward to a 10 years as productive as the last.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.004
GPT teacher head0.249
Teacher spread0.244 · 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.

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

Citations48
Published2013
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part C Seminars in Medical GeneticsSame topicGenetic Syndromes and ImprintingFrench-language works237,207