Novel Candidate Regulators and Developmental Trajectory of Pituitary Thyrotropes
Bibliographic record
Abstract
The pituitary gland regulates growth, metabolism, reproduction, the stress response, uterine contractions, lactation, and water retention. It secretes hormones in response to hypothalamic input, end organ feedback, and diurnal cues. The mechanisms by which pituitary stem cells are recruited to proliferate, maintain quiescence, or differentiate into specific cell types, especially thyrotropes, are not well understood. We used single-cell RNA sequencing in juvenile P7 mouse pituitary cells to identify novel factors in pituitary cell populations, with a focus on thyrotropes and rare subtypes. We first observed cells coexpressing markers of both thyrotropes and gonadotropes, such as Pou1f1 and Nr5a1. This was validated in vivo by both immunohistochemistry and lineage tracing of thyrotropes derived from Nr5a1-Cre; mTmG mice and demonstrates that Nr5a1-progenitors give rise to a proportion of thyrotropes during development. Our data set also identifies novel factors expressed in pars distalis and pars tuberalis thyrotropes, including the Shox2b isoform in all thyrotropes and Sox14 specifically in Pou1f1-negative pars tuberalis thyrotropes. We have therefore used single-cell transcriptomics to determine a novel developmental trajectory for thyrotropes and potential novel regulators of thyrotrope populations.
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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".