477 Oligosaccharide and IgG concentrations throughout the first week of lactation in multiparous and primiparous Holstein dairy cattle.
Bibliographic record
Abstract
Colostrum and milk oligosaccharides (OS) can function as prebiotic substances, inhibit pathogenic organisms, and may enhance the uptake of IgG in the small intestine. The objective of this study was to characterize the OS profile during the first week of lactation in primiparous and multiparous Holstein dairy cattle. The experiment was conducted on a commercial dairy farm in Alberta, where multiparous (n=10, MP) and primiparous (n=10, PP) dairy cows were assigned to the study at the time of calving. The colostrum sample was taken within 12h after calving, followed by collection of milkings 2–6, 8, 10, 12 and 14. Samples were analyzed for concentrations of 3’sialyllactose (3’SL), 6’sialyllactose (6’SL), 3’sialyllactosamine (3’SLN), 6’sialyllactosamine (6’SLN) and disialyllactose (DSL) using a liquid chromatography-mass spectrometry system and for IgG concentrations using radial immunodiffusion. Data were analyzed using PROC MIXED (SAS 9.4) with milking and parity as a fixed effect and animal within parity as random effect. Concentrations of IgG were highest (P<0.0001) in colostrum and milking 2 compared to all other milkings. Moreover, PP animals (82.1 ± 3.14 mg/ml) had lower (P=0.03) concentrations of IgG compared to MP animals (106.1 ± 16.18 mg/ml) in colostrum. In regards to OS concentrations, 3’SL, 6’SL and 6’SLN were higher (P<0.0001) in colostrum and milking 2 compared to all other milkings, where as DSL was only different (P<0.0001) in colostrum. As expected, 3’SL was the most abundant (P<0.0001) OS in colostrum and milking 2 and 3’SLN was only detected in trace amounts. Differences among parity were detected for 6’SLN in colostrum, with PP animals having lower concentrations (P=0.08, 61.3 ± 23.13 μg/ml vs. 127.1 ± 23.6 μg/ml) compared to MP animals. These findings demonstrate that feeding milking 2 (transition milk) to newborn calves may have significant benefits in establishing a healthy gut bacterial community and immune system.
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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) | 0.001 | 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".