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The Molecular Genetics of Retinoblastoma

2016· article· en· W2560151569 on OpenAlexaff
Timothy W. Corson, Helen Dimaras

Bibliographic record

VenueReviews in Cell Biology and Molecular Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicOcular Oncology and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRetinoblastomaBiologyRetinoblastoma proteinCancer researchE2F1Cell cycleTumor suppressor geneGeneticsGermline mutationE2FGeneMutationCarcinogenesis

Abstract

fetched live from OpenAlex

Retinoblastoma is a rare, malignant, childhood tumor that is primarily initiated by the inactivation of both alleles of the retinoblastoma tumor susceptibility gene, RB1, in a developing human retinal cell. A rare subset of retinoblastoma is initiated by somatic amplification of the MYCN oncogene in a predisposing retinal cell. Surprisingly the retinoblastoma protein (pRB), encoded by RB1, is an important transcription factor. Cell-cycle control by pRB is mainly accomplished by transcriptional repression of the genes required for cell-cycle progression. Control of differentiation by pRB is achieved by the activation of transcription. Through extensive post-translational modifications and interactions with other proteins, pRB and family members also influence senescence, chromosomal stability, and apoptosis. Almost every type of tumor has disruption in the retinoblastoma pathway associated with tumor progression, but germline mutation of the RB1 gene predisposes children to a 95% specific risk of developing retinoblastoma and a significantly increased risk of second primary tumors, such as osteosarcoma and melanoma. However, retinoblastoma is also characterized by other genomic changes subsequent to RB1 mutation. Keywords: aneuploidy; apoptosis; chromosome instability (CIN); E2F ; LOH ; MYCN ; proband; RB1 ; retinoblast; retinoma; SV40 ; TAg ; tumor suppressor

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.319
Teacher spread0.304 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations2
Published2016
Admission routes1
Has abstractyes

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