338 The Impact of an Aspergillus Oryzae Prebiotic on Mineral Bioavailability in Multiparous Beef Cows Supplemented with Vitaferm Concept-aid
Bibliographic record
Abstract
Abstract This study aimed to evaluate the effect of supplementation with an Aspergillus oryzae prebiotic (AOP) fed from ~30 d pre-partum until 30 d post-partum, on mineral concentrations in blood, liver, colostrum, and milk of multiparous beef cows. Thirty pregnant Angus crossbred cows were offered ad libitum Bermuda grass hay (Cynodon dactylon) plus a Vitaferm Concept-Aid (Biozyme Inc., St Joseph, MO) supplement at a rate of 112 g, containing (AOP; n = 15) or not (CTL; n = 15) an AOP. The treatments were delivered individually with a dried distillers grains-based premix at 454 g/d using an automated feeder (C-lock Inc, Rapid City, SD). For a minimum of 60 days prior to the expected calving date, the cows did not receive any mineral supplementation. Approximately 30 days prior to calving, right before supplementation began, blood and liver samples were collected, and mineral concentrations were used as a baseline. At calving (d 0) colostrum and blood samples were collected. Blood sampling, liver biopsies and milk collections were performed within one week after calving (d 7), and 30 days post-partum (d 30). All samples were analyzed to determine mineral concentration of P, Ca, Mg, Co, Cu, Fe, Zn, Mo, Mn, and Se. Concentrations of most micro minerals ranged from marginally adequate to deficient, with small improvement over time. Cows fed AOP had 11 and 14% lesser P and Se concentrations in serum, respectively (P < 0.05). Conversely, cows fed AOP had greater concentrations of Mn concentration in milk by 34% (P ≤ 0.05), and greater Cu in milk by 74% on day 7 (P < 0.05). Feeding AOP did not affect (P > 0.10) the mineral concentrations in liver nor in colostrum. In conclusion, feeding AOP may affect mineral bioavailability in beef cows as evidenced by changes in milk mineral concentrations.
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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".