Effect of weaning strategies on biosynthesis of oxylipids in Holstein dairy calves
Bibliographic record
Abstract
The aim of this study was to determine the effect of the weaning calves at 2 ages (early vs. late) and 2 weaning paces (abrupt over 3 d vs. gradual over 14 d) on plasma oxylipids. Seventy-one dairy calves (38.8 ± 4.4 kg, BW ± SD), blocked by sex and BW at birth, were randomly assigned in a 2 × 2 factorial arrangement of treatments. The factors were weaning age (early: 6-7 wk vs. late: 8-9 wk) and weaning pace (abrupt: 3 weaning steps over 2 d vs. gradual: 7 weaning steps over 14 d), generating 4 treatment groups: early-abrupt, early-gradual, late-abrupt, and late-gradual. Blood samples were collected from the jugular vein 1 d preweaning, and one day postweaning. Oxylipids concentration was measured by liquid chromatography-tandem MS. Fatty acid profile (including nonesterified fatty acids) was also assessed. Weaning pace, age, pace × age, BW at birth, and sex were included as fixed effect and cohort was included as random effect in the model. Linoleic acid derivatives 13- oxooctadecadienoic (OxoODE) and 9-OxoODE had a greater concentration in calves abruptly weaned when compared with those for gradually weaned calves. Calves weaned gradually showed a greater concentration of 9-hydroxyoctadecadienoic (HODE), 13-HODE, 12,13-dihydroxyoctadecenoic (DiHOME), 9,10-DiHOME, all linoleic acid-derived compared with that for abruptly weaned calves. Anti-inflammatory oxylipid 17,18-dihydroxyeicosatrienoic, an eicosapentaenoic acid derivative, was greater in calves abruptly weaned compared with those gradually weaned. Overall, the pace of weaning affected the plasma concentration of oxylipids, demonstrating that weaning pace affects the oxylipids status involved in inflammation in dairy calves.
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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 | 0.001 |
| 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 | 0.001 |
| 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".