Abomasally infused SFA with varying chain length differently affect milk production and composition and alter hepatic and mammary gene expression in lactating cows
Bibliographic record
Abstract
The aim of the present study was to compare the effects of post-ruminally infused fat supplements, varying in fatty acid (FA) chain length, on animal performance, metabolism and milk FA. Eleven multiparous Holstein dairy cows were used in a replicated incomplete 3 × 3 Latin square design with 7-d periods, separated by 7-d washouts. Treatments were administered as abomasal infusions of enrichments providing 280 g/d of FA: (1) palmitic acid (98·4 % 16 : 0; PA), (2) caprylic and capric acids (56·2 % 8 : 0, 43·8 % 10 : 0; medium-chain TAG (MCT)) and (3) stearic acid (99·0 % 18 : 0; SA). Relative to PA, SA decreased the efficiency of fat-corrected milk production, which was associated with a tendency for higher DM intake and lower FA absorption with SA, whereas MCT was not different from PA for these variables. Milk fat concentration and yield were increased by PA relative to SA, but only fat yield tended to be greater relative to MCT. Relative to PA, MCT increased milk fat concentration of FA < 16 C, whereas SA increased FA > 16 C. Expression of mammary stearoyl-coA desaturase 1 was lower with SA than with PA. Relative to PA, liver expression of adenosine monophosphate-activated protein kinase-1 and pyruvate kinase was increased with MCT, whereas expression of these genes tended to be increased by SA. The mechanism of increased fat secretion with PA does not seem to be related to a modulation of the expression of lipogenesis-related genes, but rather to increased substrate availability as reflected by milk FA profile.
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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) | 0.001 | 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) | 0.001 | 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".