Effects of prepartum oilseed supplements on subclinical endometritis, pro- and anti-inflammatory cytokine transcripts in endometrial cells and postpartum ovarian function in dairy cows
Bibliographic record
Abstract
Postpartum uterine infections affect ovarian function and delay ovulation in cattle. As dietary fats can affect immune cell function, we investigated the influence of prepartum diets on postpartum uterine inflammatory status (UIS) as assessed 25±1 days postpartum by endometrial cytology (normal: ≤8% polymorphonuclear cells (PMN) vs subclinical endometritis (SCE): >8% PMN) and associations between SCE, pro- and anti-inflammatory cytokine gene expression and ovarian function. During the last 5 weeks of gestation, dairy cows received a diet supplemented with 8% rolled sunflower (n=10) or canola seed (n=9) or no oilseed (n=9). Ovaries were scanned until 35 days postpartum. Prepartum diets did not influence SCE, but a preovulatory-size follicle developed sooner (P≤0.05), the interval to first ovulation was shorter and the proportion of cows ovulating within 35 days postpartum was greater in the sunflower seed group. Although mRNA expression of cytokines was not affected by diet, cows with SCE had higher (P≤0.05) expression of interleukin-1β (IL1B), interleukin-8 (CXCL8), IL10 and tumour necrosis factor-α (TNF) than normal cows. The interval (mean ± s.e.m.) from calving to preovulatory-size follicle was shorter (P≤0.05) in normal (13.2±0.9 days) than SCE cows (18.7±1.4 days). In summary, a prepartum diet supplemented with sunflower seed positively influenced postpartum ovarian function without affecting UIS or pro- and anti-inflammatory cytokine gene expression in endometrial cells.
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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".