Effect of anti-inflammatory treatment on systemic inflammation, immune function, and endometrial health in postpartum dairy cows
Bibliographic record
Abstract
Systemic inflammation (SI) is increasingly studied in several species because it may be central in many metabolic disturbances and be a risk factor for clinical disease. This proof-of-concept study evaluated the effects of the anti-inflammatory drug meloxicam on markers of SI and energy metabolism, polymorphonuclear neutrophil (PMN) function, and endometritis in clinically healthy postpartum dairy cows. Cows received meloxicam (0.5 mg/kg of body weight; n = 20) once daily for 4 days (10-13 days postpartum) or were untreated (n = 22). Blood samples were collected -7, 1, 3, 5, 7, 10, 11, 12, 13, 14, 18, 21, 28, and 35 days relative to calving to measure serum concentrations of metabolic and inflammatory markers. Function of peripheral blood PMN were evaluated at 5, 10, 14, and 21, and proportion of PMN in endometrial cytology were performed at 5, 10, 14, 21, 28 and 35 days postpartum. Meloxicam decreased serum haptoglobin from the second until the last day of treatment, and improved indicators of energy metabolism (lesser β-hydroxybutyrate and greater insulin-like growth factor-1 during treatment, and greater glucose at the end of treatment than control cows). This improved PMN function at 14 days postpartum, but the endometrial inflammatory status was not affected.
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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) | 0.001 | 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".