Dual regulatory role for phosphatase and tensin homolog in specification of intestinal endocrine cell subtypes
Bibliographic record
Abstract
AIM: To investigate the impact of phosphatase and tensin homolog (Pten) in the specification of intestinal enteroendocrine subpopulations. METHODS: Using the Cre/loxP system, a mouse with conditional intestinal epithelial Pten deficiency was generated. Pten mutant mice and controls were sacrificed and small intestines collected for immunofluorescence and quantitative real-time polymerase chain reaction. Blood was collected on 16 h fasted mice by cardiac puncture. Enzyme-linked immunosorbent assay was used to measure blood circulating ghrelin, somatostatin (SST) and glucose-dependent insulinotropic peptide (GIP) levels. RESULTS: Results show an unexpected dual regulatory role for epithelial Pten signalling in the specification/differentiation of enteroendocrine cell subpopulations in the small intestine. Our data indicate that Pten positively regulates chromogranin A (CgA) expressing subpopulations, including cells expressing secretin, ghrelin, gastrin and cholecystokinin (CCK). In contrast, Pten negatively regulates the enteroendocrine subtype specification of non-expressing CgA cells such as GIP and SST expressing cells. CONCLUSION: The present results demonstrate that Pten signalling favours the enteroendocrine progenitor to specify into cells expressing CgA including those producing CCK, gastrin and ghrelin.
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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) | 0.000 | 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".