<i>Pten</i> Deficiency Activates Distinct Downstream Signaling Pathways in a Tissue-Specific Manner
Bibliographic record
Abstract
PTEN deficiency predisposes to a subset of human cancers, but the mechanism that underlies such selectivity is unknown. We have generated a mouse line that conditionally deletes Pten in urogenital epithelium. These mice develop carcinomas at high frequency in the prostate but at relatively low frequency in the bladder, despite early and complete penetrance of hyperplasia in both organs. Cell proliferation is initially high in the bladder of newborn Pten-deficient mice but within days is inhibited by p21 induction. In contrast, proliferation remains elevated in Pten-deficient prostate, where p21 is never induced, suggesting that p21 induction is a bladder-specific compensatory mechanism to inhibit proliferation caused by Pten deletion. Furthermore, the AKT/mammalian target of rapamycin growth pathway, which is highly activated in Pten-deficient prostate, is not activated in bladder epithelium. Our results reveal alternative downstream signaling pathways activated by Pten deficiency that lead to tissue-specific susceptibilities to tumorigenesis.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".