The Protein-Protein Interaction-Mediated Inactivation of PTEN
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".