MétaCan
Menu
Back to cohort
Record W7133018424

The role of p16(INK4A) in SMAD signalling

2007· dissertation· W7133018424 on OpenAlexaff
Isabel Beatrice Lokody

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsCanadian HeritageLibrary and Archives Canada
Fundersnot available
KeywordsCDKN2AMelanomaKinaseCell cycleSMADMutantGeneMutation
DOInot available

Abstract

fetched live from OpenAlex

Individuals carrying germline mutations in the CDKN2A gene have an increased risk of developing cutaneous melanoma. The CDKN2A gene encodes the cell cycle inhibitor p16INK4A, which binds and inhibits the cell cycle kinases CDK4 and CDK6. Recently it was reported that CDK4 also phosphorylates SMAD3, implying that p16 INK4A may also regulate SMAD3 signalling. Since p16INK4A inhibits CDK4, I hypothesized that p16INK4A should prevent CDK4 from phosphorylating SMAD3 and that melanoma-associated p16INK4A mutants lose this function. Using a series of reporter-based assays and quantitative PCR, I have demonstrated that p16INK4A can affect one SMAD3 signalling target, c-myc. In addition, several melanoma-associated p16 INK4A mutants do not affect c-myc mRNA expression in a melanoma cell line. These results are important because they may link melanoma to SMAD signalling---a well-established cancer-related pathway. Moreover, this work may also lead to alternate drug targets relevant for treatment of melanoma and other p16INK4A relevant malignancies.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.012
GPT teacher head0.337
Teacher spread0.325 · 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 designBench or experimental
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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueTSpaceSame topicCancer-related Molecular PathwaysFrench-language works237,207