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Record W2114141697 · doi:10.1051/medsci/200824121049

Micro-ARN : oncogènes et suppresseurs de tumeurs

2008· review· fr· W2114141697 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuemédecine/sciences · 2008
Typereview
Languagefr
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA modifications and cancer
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMolecular biologyChemistryBiology

Abstract

fetched live from OpenAlex

microRNAs constitute one of the most important discovery in the past few years in the field of gene expression regulation. They can precisely regulate the expression of a specific protein by inhibiting its translation and/or promoting the degradation of its mRNA. In several cancers, the expression of some microRNAs is misregulated, pointing toward the existence of microRNAs with oncogenic or tumour suppressor properties. The miR-17-92 miRNA cluster has been reported to have a pro-oncogenic role in a mouse model system of Myc-induced B cell lymphoma. Some of its targets mRNAs code for proteins with pro-apoptotic or anti-proliferative functions, which shed some light on the mechanism of action of this cluster. On the other hand, a tumour suppressor miRNA like let-7 targets mRNAs coding for oncogenes and is frequently down-regulated in cancers. The finding that c-Myc controls the expression of several of these microRNAs reveals new information on how misregulation of this proto-oncogene can promote tumorigenesis.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.061
GPT teacher head0.363
Teacher spread0.302 · 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