60 The Effect of Neomycin Inclusion in Milk Replacer on Gut Health and Development in Preweaned Male Holstein Calves
Bibliographic record
Abstract
Abstract Neomycin is commonly used in calf milk replacers (MR) to prevent diarrhea, however, antimicrobial exposure in early life may have consequences to gut development. The objective of this study was to investigate the effects of neomycin inclusion in MR on calf gut health and development. Thirty-six calves were randomly assigned to one of three treatments: control (CON), non-medicated (MR, n = 12), short-term antimicrobial exposure (ST: 20 mg/kg BW neomycin mixed in MR from d 1–14, n = 12), or long-term antimicrobial exposure (LT: 20 mg/kg BW neomycin in MR from d 1–28, n = 12). Fecal samples were collected weekly to measure total bacteria, and gut permeability was measured in week 2 and 4 by comparing serum recovery of orally dosed lactulose and D-mannitol markers. Calves were dissected at week 5 to collect intestinal tissues, which were used to analyze histology, gene expression and total bacteria abundance. Digesta samples were collected to analyze for total bacteria abundance and volatile fatty acid (VFA) concentrations. No treatment effects were found in the amounts of total bacteria in fecal, digesta, or tissue samples. Marker recovery in serum was higher at week 2 compared to week 4 (P < 0.01), suggesting that calves in early life have higher gut permeability. Histomorphological measures were similar, except for villi length in the distal jejunum, which was longest in ST calves (P = 0.05). Tight-junction, mucus, and inflammatory-associated gene expression was similar overall, although the expression of Tight junction protein-1 in the distal jejunum was lowest in CON calves (P = 0.04). Distal jejunum acetic acid, propionic acid, and total VFA tended to be highest in LT calves (P = 0.09; P = 0.06; P = 0.07, respectively). Although this study found few consequences of neomycin to gut health, the lack of benefits supports the argument that antimicrobials should be used prudently.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| 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) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".