Related pituitary cell lineages develop into interdigitated 3D cell networks
Bibliographic record
Abstract
The pituitary gland has long been considered to be a random patchwork of hormone-producing cells. By using pituitary-scale tridimensional imaging for two of the least abundant cell lineages, the corticotropes and gonadotropes, we have now uncovered highly organized and interdigitated cell networks that reflect homotypic and heterotypic interactions between cells. Although newly differentiated corticotrope cells appear on the ventral surface of the gland, they rapidly form homotypic strands of cells that extend from the lateral tips of the anterior pituitary along its ventral surface and into the medial gland. As the corticotrope network is established away from the microvasculature, cell morphology changes from rounded, to polygonal, and finally to cells with long cytoplasmic processes or cytonemes that connect corticotropes to the perivascular space. Gonadotropes differentiate later and are positioned in close proximity to corticotropes and capillaries. Blockade of corticotrope terminal differentiation produced by knockout of the gene encoding the transcription factor Tpit results in smaller gonadotropes within an expanded cell network, particularly in the lateral gland. Thus, pituitary-scale tridimensional imaging reveals highly structured cell networks of unique topology for each pituitary lineage. The sequential development of interdigitated cell networks during organogenesis indicate that extensive cell:cell interactions lead to a highly ordered cell positioning rather than random patchwork.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".