Effects of nutrient restriction on mammary cell turnover and mammary gland remodeling in lactating dairy cows
Bibliographic record
Abstract
The aim of this study was to investigate the effects of a severe nutrient restriction on mammary tissue morphology and remodeling, mammary epithelial cell (MEC) turnover and activity, and hormonal status in lactating dairy cows. We used 16 Holstein × Normande crossbred dairy cows, divided into 2 groups submitted to different feeding levels (basal and restricted) from 2 wk before calving to wk 11 postpartum. Restricted-diet cows had lower 11-wk average daily milk yield from calving to slaughter than did basal-diet cows (20.5 vs. 33.5 kg/d). Feed restriction decreased milk fat, protein, and lactose yields. Restriction also led to lower plasma insulin-like growth factor 1 and higher growth hormone concentrations. Restricted-diet cows had lighter mammary glands than did basal-diet cows. The total amount of DNA in the mammary gland and the size of the mammary acini were smaller in the restricted-diet group. Feed restriction had no significant effect on MEC proliferation at the time of slaughter but led to a higher level of apoptosis in the mammary gland. Gelatin zymography highlighted remodeling of the mammary extracellular matrix in restricted-diet cows. Udders from restricted-diet cows showed lower transcript expression of α-lactalbumin and kappa-casein. In conclusion, nutrient restriction resulted in lower milk yield in lactating dairy cows, partly due to modulation of MEC activity and a lower number of mammary cells. An association was found between feed restriction-induced changes in the growth hormone-insulin-like growth factor-1 axis and mammary epithelial cell dynamics.
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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) | 0.000 | 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".