Implication du facteur Tpit dans la différenciation hypophysaire et la pathogenèse du déficit corticotrope
Bibliographic record
Abstract
The pituitary gland is a very convenient model to study mechanisms implicated in cellular differentiation. This endocrine gland is composed of six cell lineages, each committed to the production of a different hormone: thyrotrophs (TSH), somatotrophs (GH), lactotrophs (PRL), gonadotrops (LH, FSH), melanotrophs (alpha-MSH) and corticotrophs (ACTH). ACTH and alpha-MSH are both processed from the same precursor, proopiomelanocortin (POMC). Pituitary hormone-producing cells differentiate sequentially from a common epithelial primordium, Rathke's pouch, under the combinatorial action of a subset of tissue- and cell-restricted transcription factors. In corticotrophs, Tpit and NeuroD1 are important for POMC transcription. Their expression closely precedes that of POMC, suggesting a role in the differentiation of this lineage. In order to better define the role of Tpit in POMC cell differentiation, we generated Tpit-null mice. These mice are deficient in POMC-expressing cells while other pituitary lineages are normal. Analysis of other corticotroph markers, such as NeuroD1, showed that lineage commitment was preserved in absence of Tpit. We next tested if Tpit and -NeuroD1 could be jointly required for corticotroph determination by producing Tpit-/- NeuroD1-/- mice. This experiment revealed that these two factors are not essential for early determination of corticotroph cells, suggesting different levels of control for commitment of POMC lineages compared to cell survival or to cell-specific transcription of POMC. Further investigation of Tpit-/- mice has revealed that Tpit is a negative regulator of the gonadotroph fate. These studies suggest a binary model of cell fate decisions for pituitary cell differentiation, suggesting the presence of a pituitary pluripotent precursor. Finally we have shown that mutations in the coding sequence of human TPIT are associated with isolated ACTH deficiency, a pathology very similar to that found in Tpit-null m
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".