Bibliographic record
Abstract
Abstract Loss of PTEN function has been implicated in the etiology of numerous human malignancies, including sporadic brain, prostate, thyroid, breast, uterine and kidney tumors. PTEN germline have also been found in patients with PHTS, an autosomal-dominant cancer predisposition syndrome. Despite a thorough understanding of the inhibitory role for PTEN in the PI3K pathway, acting as a 3′PI phosphatase and directly antagonizing PI3'K, relatively little is known about PTEN's functions in the nucleus, a cellular compartment where it also resides. Our recent work has uncovered a nuclear function of PTEN in tumor suppression, which is independent from its 3′PI-phosphatase activity, but relies on PTEN protein phosphatase activity. Nuclear PTEN, which is SUMOylated, plays a prominent role in homologous recombination-based DNA repair, acting downstream of the protein kinase ATM. PTEN-deficient cells and tumors are impaired in their response to DNA damage and display heightened sensitivity to genotoxic agents, which may have significant implications for the treatment of PTEN-deficient cancers. Citation Format: Vuk Stambolic. Nuclear PTEN in regulation of genome integrity. [abstract]. In: Proceedings of the AACR Special Conference: Targeting the PI3K-mTOR Network in Cancer; Sep 14-17, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(7 Suppl):Abstract nr IA10.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".