Evaluation of Domperidone Dosages and Delivery Methods for the Treatment of Fescue Toxicosis in Beef Heifers
Bibliographic record
Abstract
The objective of this study was to develop a practical method of domperidone delivery to ameliorate fescue toxicosis. Experiment 1 used heifers assigned to 7 treatment groups (n = 6 each): positive control (0.44mg domperidone/kg BW daily s.c. for 9 d), negative control, and 0.22, 0.44, 0.88, and 1.76mg domperidone/kg BW per os daily for 9 d, or a 3g domperidone i.m. injection. Blood was collected every third day for 24 d. Domperidone concentrations in the 0.88 and 1.76 mg/kg BW treatments and the i.m. treatment were greater than positive control (P < 0.05) on d 3. None of the oral treatments were greater than the positive control on subsequent days. Between d 6 and 24, no oral treatments differed from the negative control except for the 1.76 mg/kg of BW treatment on d 9. The i.m. formulation increased domperidone when compared with the negative and positive controls (P < 0.05) on d 3 through d 21. Experiment 2 evaluated the i.m. injection protocol on performance. Heifers were assigned to control (n = 15) or i.m. domperidone (n = 15) treatments and grazed endophyte-infected fescue paddocks. Blood was sampled weekly and analyzed for progesterone and prolactin concentrations. Controls had reduced BW gains (P < 0.001) and BCS (P < 0.05) and elevated rectal temperatures (P < 0.05) compared with treated heifers. Domperidone treatment interacted with day on affecting prolactin (P < 0.0001) and progesterone (P < 0.0001). Intramuscular delivery of domperidone is an effective method for relieving fescue toxicosis.
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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) | 0.000 | 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, 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".