Brown adipocytes can display a mammary basal myoepithelial cell phenotype in vivo
Bibliographic record
Abstract
Previous work has suggested that white adipocytes may also show a mammary luminal secretory cell phenotype during lactation. The capacity of brown and beige/brite adipocytes to display a mammary cell phenotype and the levels at which they demonstrate such phenotypes in vivo is currently unknown. To investigate the putative adipocyte origin of mammary gland cells, we performed genetic lineage-labeling experiments in BAT and the mammary glands. These studies indicated that the classic brown adipocytes (Ucp1+) and subcutaneous beige/brite adipocytes (Ucp1−/+) were found in the mammary gland during lactation, when they exhibited a mammary myoepithelial phenotype. Up to 2.5% of the anterior dorsal interscapular mammary myoepithelial cell population had a brown adipocyte origin with an adipose and myoepithelial gene signature during lactation. Eliminating these cells, along with all the brown adipocytes, significantly slowed offspring growth, potentially demonstrating their functional importance. Additionally, we showed mammary epithelial lineage Mmtv+ and Krt14+ cells expressed brown adipocyte markers after weaning, demonstrating that mammary gland cells can display an adipose phenotype. The identification of a brown adipocyte origin of mammary myoepithelial cells provides a novel perspective on the interrelationships between adipocytes and mammary cells with implications for our understanding of obesity and breast cancer.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".