Animal board invited review: The contribution of adipose stores to milk fat: implications on optimal nutritional strategies to increase milk fat synthesis in dairy cows
Bibliographic record
Abstract
A wide range of nutritional and non-nutritional factors influence milk fat synthesis and explain the large variation observed in dairy herds. The capacity of the animal to synthesize milk fat will largely depend on the availability of substrates for lipid synthesis, some of which originate directly from the diet, ruminal fermentation or from adipose tissue stores. The mobilization of non-esterified fatty acids from adipose tissues is important to support the energy demands of milk synthesis and will therefore have an impact on the composition of milk lipids, especially during the early lactation period. Such mobilization is tightly controlled by insulin and catecholamines, and in turn, can be affected indirectly by factors that influence these signals, namely diet composition, lactation stage, genetics, endotoxemia, and inflammation. Environmental factors, such as heat stress, also impact adipose tissue mobilization and milk fat synthesis, mainly through endotoxemia and an immune response-related increase in concentrations of plasma insulin. Indeed, as proposed in the present review, the central role of insulin in the control of lipolysis is key to improving our understanding of how nutritional and non-nutritional factors impact milk fat synthesis. This is particularly the case during early lactation, as well as in situations where mammary lipid synthesis is more dependent on adipose-derived fatty acids.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".