Alterations of Innate Immunity Reactants in Transition Dairy Cows before Clinical Signs of Lameness
Bibliographic record
Abstract
The objectives of this study were to evaluate metabolic and innate immunity alterations in the blood of transition dairy cows before, during, and after diagnosis of lameness during periparturient period. Blood samples were collected from the coccygeal vain once per week before morning feeding from 100 multiparous Holstein dairy cows during -8, -4, disease diagnosis, and +4 weeks (wks) relative to parturition. Six healthy cows (CON) and six cows that showed clinical signs of lameness were selected for intensive serum analyses. Concentrations of interleukin-1 (IL-1), interleukin-6 (IL-6), tumor necrosis factor (TNF), haptoglobin (Hp), serum amyloid A (SAA), lipopolysaccharide binding protein (LBP), lactate, non-esterified fatty acids (NEFA), and β-hydroxybutyrate (BHBA) were measured in serum by ELISA or colorimetric methods. Health status, DMI, rectal temperature, milk yield, and milk composition also were monitored for each cow during the whole experimental period. Results showed that cows affected by lameness had greater concentrations of lactate, IL-6, and SAA in the serum vs. CON cows. Concentrations of TNF tended to be greater in cows with lameness compared with CON. In addition, there was a health status (Hs) by time (week) interaction for IL-1, TNF, and Hp in lameness cows vs. CON ones. Enhanced serum concentrations of lactate, IL-6, and SAA at -8 and -4 wks before parturition were different in cows with lameness as compared with those of the CON group. The disease was also associated with lowered overall milk production and DMI as well as milk fat and fat-to-protein ratio. In conclusion, cows affected postpartum by lameness had alterations in several serum variables related to innate immunity and carbohydrate metabolism that give insights into the etiopathogenesis of the disease and might serve to monitor health status of transition dairy cows in the near future.
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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".