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Record W7132967266

GATA6: A Molecular Regulator of Pancreatic Tumour Growth and Phenotype

2023· dissertation· W7132967266 on OpenAlexaff
Tristan Suejin Donna Woo

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGATA6PhenotypeRegulatorPancreatic ductal adenocarcinomaGeneGene expressionRegulation of gene expression
DOInot available

Abstract

fetched live from OpenAlex

Pancreatic ductal adenocarcinoma (PDAC) has been classified into two main transcriptional subtypes, Basal-like and Classical. The Classical subtype correlates with GATA6 expression, and ~16% of tumors show amplification in GATA6. The goal of this project is to understand the role of GATA6 as a molecular regulator of the Classical subtype. Competition assays show loss of GATA6 reduced cell fitness. Gene expression analysis showed GATA6 was integral in maintaining Classical gene expression and loss led to shifts towards more Basal-like expression and pathways. Despite a transcriptional shift towards Basal-like expression, phenotypic characteristics of the Basal-like subtype were notably absent (i.e., no EMT, MYC expression, or aggressive growth). This data suggests that loss of GATA6 is not sufficient to cause a full Basal-like phenotype and may lead to a transitional state that does not offer the same growth advantages as being in a full Basal-like state.

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 score0.003
Threshold uncertainty score0.010

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.013
GPT teacher head0.327
Teacher spread0.314 · 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
Published2023
Admission routes1
Has abstractyes

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