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The Protein-Protein Interaction-Mediated Inactivation of PTEN

2014· review· en· W2144574330 on OpenAlexafffund
Jason De Melo, Liang He, Damu Tang

Bibliographic record

VenueCurrent Molecular Medicine · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsSt. Joseph’s Healthcare Hamilton
FundersCanadian Institutes of Health Research
KeywordsPTENTensinPhosphatasePI3K/AKT/mTOR pathwaySuppressorBiologyCarcinogenesisProtein kinase BCell biologyCancer researchFunction (biology)PhosphorylationGeneticsSignal transductionGene

Abstract

fetched live from OpenAlex

PTEN (Phosphatase and Tensin homologue deleted on chromosome 10, 10q23.3) is the dominant phosphatase responsible for the dephosphorylation of the 3-position phosphate from the inositol ring of phosphatidylinositol 3,4,5 triphosphate (PIP3), and thereby directly antagonizes the actions mediated by Phosphatidylinositol-3 Kinase (PI3K). PI3K functions in numerous pathways and cellular processes, including tumourigenesis. Therefore, mechanisms regulating PTEN function, either positively or negatively are of great interest not only to oncogenesis but also to other aspects of human health. Since its discovery in 1997, PTEN has been one of the most-heavily studied tumour suppressors and has been the subject of numerous reviews. Most investigations and reviews center on PTEN's function and its regulation. While the regulation of PTEN function via genetic and/or epigenetic mechanisms has been extensively studied, the impact of protein-protein interaction on PTEN function remains less clear. Recent research has revealed that PTEN can be specifically inhibited by its interaction with other proteins, which are collectively termed PTEN-negative regulators (PTENNRs). This review will summarize our current understanding on the protein network that influences PTEN function with a specific focus on PTEN-NRs.

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 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)0.001
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 score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.367
Teacher spread0.334 · 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 teacher head, not a consensus.

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

Citations9
Published2014
Admission routes2
Has abstractyes

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