Associations among serum pro- and anti-inflammatory cytokines, metabolic mediators, body condition, and uterine disease in postpartum dairy cows
Bibliographic record
Abstract
BACKGROUND: Adipose tissue is an active endocrine organ which secretes a wide range of hormones and protein factors, collectively termed adipokines. Adipokines affect appetite and satiety, glucose and lipid metabolism, inflammation and immune functions. The objectives were to evaluate serum concentrations of adipokines (adiponectin, leptin, tumor necrosis factor (TNF)-alpha, interleukin (IL)-1beta and IL-6) in lactating dairy cows with postpartum uterine inflammatory conditions (metritis, clinical endometritis or subclinical endometritis) and in cows experiencing loss of body condition, and to assess the relationship of adipokines and body condition loss in the establishment of persistent uterine inflammatory conditions. METHODS: Lactating multiparous Holstein cows (N = 40), with body condition scores (BCS) from 2 to 4 (eight cows for each 0.5 score increment) were enrolled. Body condition was monitored for all cows weekly for 7 weeks post calving; cows with uterine inflammatory conditions were also re-evaluated 2 weeks later. Blood samples were collected from 1 week prior to calving to 7 weeks after calving for determination of serum concentrations of adipokines, insulin and insulin like growth factor (IGF)-1. RESULTS: Cows with metritis or clinical endometritis had higher serum concentrations of adiponectin, leptin, TNF-alpha, IL-1beta and IL-6 compared to normal cows (P < 0.05). Furthermore, serum leptin, TNF-alpha, IL-1beta and IL-6 were higher in cows with subclinical endometritis compared to normal cows (P < 0.05), and insulin and IGF-1 concentrations were lower in cows with metritis or clinical endometritis. Cows with low BCS (2 and 2.5) had significantly higher adiponectin, TNF-alpha, IL-1beta and IL-6 than those with high BCS (3 to 4). Cows with persistent uterine inflammatory conditions had higher adiponectin, leptin TNF-alpha, IL-1beta and IL-6 and insulin compared to normal and spontaneously recovered cows, except for IGF-1 (P < 0.05). CONCLUSIONS: Serum concentrations of adipokines, insulin, and IGF-1 had significant associations with BCS categories (low vs. high) and postpartum uterine inflammatory conditions. Perhaps loss of body condition mediated increases in anti- and pro-inflammatory cytokines, whereas increased pro- and anti-inflammatory cytokines concentrations mediated body condition loss and thereby prolonged persistence of uterine inflammation in dairy cows.
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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 | 0.001 |
| 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".