DDR1 signaling is essential to sustain Stat5 function during lactogenesis
Bibliographic record
Abstract
Postnatal development of the mammary gland is achieved by an interplay of endocrine and extracellular matrix-derived signals. Despite intense research, a comprehensive understanding of the temporal and spatial coordination of these hormonal and basement membrane stimuli is still lacking. Here, we address the role of the collagen-receptor DDR1 in integrating extracellular matrix-derived signaling with the lactogenic pathway initiated by the prolactin receptor. We found that stimulation of DDR1-overexpressing mammary epithelial HC11 cells with collagen and prolactin resulted in stronger and more sustained induction of Stat5 phosphorylation as compared to control cells. Enhanced Stat5 activity in HC11-DDR1 cells correlated with increased beta-casein gene expression. In contrast, cells derived from DDR1-null mice showed reduced Stat5 activation upon lactogenic stimulation and completely failed to induce beta-casein expression. The cell-autonomous role of DDR1 in controlling ductal branching and alveologenesis prior to the onset of lactogenesis was corroborated by mammary tissue transplantation experiments. Our results show that aside from hormone- and cytokine receptors, DDR1 signaling establishes a third matrix-derived pathway vital to maintain mammary gland function.
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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 | 0.001 |
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".