Symposium review: The impact of absorbed nutrients on energy partitioning throughout lactation
Bibliographic record
Abstract
Most nutrition models and some nutritionists view ration formulation as accounting transactions to match nutrient supplies with nutrient requirements. However, diet and stage of lactation interact to alter the partitioning of nutrients toward milk and body reserves, which, in turn, alters requirements. Fermentation and digestion of diet components determine feeding behavior and the temporal pattern and profile of absorbed nutrients. The pattern and profile, in turn, alter hormonal signals, tissue responsiveness to hormones, and mammary metabolism to affect milk synthesis and energy partitioning differently depending on the physiological state of the cow. In the fresh period (first 2 to 3 wk postpartum), plasma insulin concentration and insulin sensitivity of tissues are low, so absorbed nutrients and body reserves are partitioned toward milk synthesis. As lactation progresses, insulin secretion and sensitivity increase, favoring deposition instead of mobilization of body reserves. High-starch diets increase ruminal propionate production, the flow of gluconeogenic precursors to the liver, and blood insulin concentrations. During early lactation, the glucose produced will preferentially be used by the mammary gland for milk production. As lactation progresses and milk yield decreases, glucose will increasingly stimulate repletion of body reserves. Diets with less starch and more digestible fiber increase ruminal production of acetate relative to propionate and, because acetate is less insulinogenic than propionate, these diets can minimize body weight gain. High dietary starch concentration and fermentability can also induce milk fat depression by increasing the production of biohydrogenation intermediates that inhibit milk fat synthesis and thus favor energy partitioning away from the mammary gland. Supplemental fatty acids also impact energy partitioning by affecting insulin concentration and insulin sensitivity of tissues. Depending on profile, physiological state, and interactions with other nutrients, supplemental fatty acids might increase milk yield at the expense of body reserves or partition energy to body reserves at the expense of milk yield. Supplemental protein or AA also can increase milk production but there is little evidence that dietary protein directly alters whole-body partitioning. Understanding the biology of these interactions can help nutritionists better formulate diets for cows at various stages of lactation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.017 | 0.009 |
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".