Primiparous and multiparous females differ in mammary gland alveolar development: implications for milk production
Bibliographic record
Abstract
Mammary gland capacity is influenced by the number of secretory cells in the gland, the activity of those cells and the size and arrangement of the alveoli that they form. Although reproductive experience has been shown to affect the total number of secretory cells in the gland, its potential effect on the structural development of lobulo-alveolar tissues has not been directly investigated. To examine whether reproductive experience affects lobulo-alveolar development, we took mammary gland biopsies at early and peak lactation from primiparous and multiparous grey seal (Halichoerus grypus) females and used histological techniques to compare cell density, alveolar density and alveolar size within secretory lobules. Primiparous females had a significantly higher cell density compared with multiparous females throughout lactation, suggesting that primiparous females have smaller, less-developed secretory cells. Primiparous females had a significantly smaller average alveolar size compared with multiparous females throughout lactation. Although alveolar density was higher in primiparous females compared with multiparous females at early lactation, there was no significant difference between the groups at peak lactation. These results suggest that the mammary gland of primiparous females may have both a lower secretory capacity and a lower storage capacity on a relative basis than those of multiparous females and demonstrate, for the first time, that reproductive experience has a significant effect on both the rate and pattern of mammary gland alveolar development and, potentially, on a female's capacity for milk production.
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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) | 0.003 | 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".