Occurrence of retained placenta is preceded by an inflammatory state and alterations of energy metabolism in transition dairy cows
Bibliographic record
Abstract
BACKGROUND: Failure to expel fetal membranes within 24 h of calving is a pathological condition defined as retained placenta (RP). The objective of this investigation was to evaluate whether there are alterations in several selected serum variables related to innate immunity and carbohydrate and lipid metabolism that precede occurrence of RP in transition Holstein dairy cows. METHODS: One hundred multiparous Holstein dairy cows were involved in the study. Blood samples were collected from the coccygeal vein during the -8 to +4 wks around parturition, once per week before the morning feeding. Six healthy control cows (CON) and 6 cows with RP were selected and serum samples at -8, -4, time of diagnosis of disease, and +4 wks relative to parturition were used for analyses. All samples were analyzed for lactate, non-esterified fatty acids (NEFA), β-hydroxybutyrate (BHBA), interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor (TNF), haptoglobin (Hp), and serum amyloid A (SAA). RESULTS: Cows with RP had greater concentrations of serum lactate, IL-1, IL-6, TNF, and SAA in comparison with CON cows. Intriguingly, elevated concentrations of all five variables were observed at -8 and -4 wks before the occurrence of RP compared to healthy cows. Cows with RP also had lower DMI and milk production vs CON animals; however milk composition was not affected by RP. CONCLUSIONS: Cows with RP showed an activated innate immunity 8 wks prior to diagnosis of disease. Overall results suggest that serum IL-1, IL- 6, and TNF, and lactate can be used as screening biomarkers to indicate cows that might have health issues during the transition period.
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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 | 0.001 | 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".