Functional analysis of the tumour suppressor gene PTEN in murine B cells and keratinocytes
Bibliographic record
Abstract
To investigate the roles of the PTEN (phosphatase and tensin homologue deleted from chromosome 10)/PI3K (phosphoinositide 3-kinase) signalling pathway in vivo, we have generated a series of mutant mice with null or tissue-specific gene-targeted deletions of Pten. Here we present our investigations of Pten function in B cells and keratinocytes in mice. Mice with a B cell-specific mutation of Pten showed increased serum autoantibodies and elevated numbers of B1a cells. Among conventional B (B2) cells in mutant spleens, numbers of marginal zone B cells were significantly increased, while those of follicular B cells were reciprocally decreased. Immunoglobulin class switch recombination was defective and associated with impaired induction of activation-induced cytidine deaminase. Mice with a keratinocyte-specific mutation of Pten exhibited epidermal hyperplasia, hyperkeratosis and accelerated skin morphogenesis. Within 3 weeks of birth, 90% of these animals died of malnutrition, possibly caused by hyperkeratosis of the oesophageal epithelia. Surviving mutant mice developed spontaneous skin tumours within 8.5 months of birth, and chemical treatment accelerated the onset of tumours. Our data show that PTEN is an important regulator in B cells and keratinocytes.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".