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Record W2053580956 · doi:10.1016/j.febslet.2014.02.026

The multifaceted von Hippel–Lindau tumour suppressor protein

2014· review· en· W2053580956 on OpenAlexafffund
Claire M. Robinson, Michael Ohh

Bibliographic record

VenueFEBS Letters · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsUbiquitin ligaseEpigenomeCancer researchHypoxia-inducible factorsUbiquitinBiologyEpigeneticsSuppressorTumor suppressor geneLoss functionClear cell renal cell carcinomaRenal cell carcinomaCancerCarcinogenesisGeneGeneticsDNA methylationMedicineInternal medicineGene expressionPhenotype

Abstract

fetched live from OpenAlex

Loss of von Hippel-Lindau protein (pVHL) is known to contribute to the initiation and progression of tumours associated with VHL disease as well as certain sporadic tumours including clear cell renal cell carcinoma (ccRCC). The VHL gene was first identified and cloned over 20 years ago and our understanding of its functions and effects has significantly increased since then. The best-known function of pVHL is its role in promoting the degradation of hypoxia-inducible factor α subunit (HIFα) as part of an E3 ubiquitin ligase complex. HIF stabilisation and transcriptional activation are also associated with various epigenetic alterations, indicating a potential role for VHL loss with changes in the epigenome. This review will highlight current knowledge regarding pVHL as well as discuss potentially novel roles of pVHL and how these may impact on cancer progression.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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

Citations102
Published2014
Admission routes2
Has abstractyes

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