Comparison of L-selectin and Mac-1 expression on blood and milk neutrophils during experimental Escherichia coli-induced mastitis in cows
Bibliographic record
Abstract
OBJECTIVE: To evaluate L-selectin (CD62L) and Mac-1 (CD11b) expression at the surface of blood and milk neutrophils during the early inflammatory response to Escherichia coli-induced mastitis in cows. ANIMALS: 6 healthy Holstein heifers in early lactation. PROCEDURE: Blood and milk samples were collected before and after intramammary administration of 10(4) CFU's of E coli in the left mammary gland quarters. Bacterial counts and electrolyte concentrations in milk, rectal temperature, differential blood leukocyte counts, milk somatic cell counts, neutrophil viability, and the expression of CD62L and CD11b on blood and milk neutrophils were determined longitudinally. RESULTS: Bacteria grew during the first 6 hours after inoculation with a pronounced leukocytic influx. Coincident with neutrophil influx was an increase in CD62L+ and CD11b+ milk neutrophils, as well as an improved viability of milk neutrophils. The peak of the inflammatory reaction was reached approximately 12 hours after E coli inoculation. From that time forward, changes in CD62L and CD11b expression were opposed to each other, with a decrease in CD62L expression and an increase in CD11b expression on blood and milk neutrophils; the magnitude of the differences in CD62L and CD11b expression between blood and milk neutrophils decreased. Percentages of CD62L+ and CD11b+ milk neutrophils increased to percentages that were similar to blood neutrophils (ie, approx 92%). CONCLUSIONS AND CLINICAL RELEVANCE: The presence of adhesion molecules on a large percentage of milk neutrophils during the acute inflammatory response, together with the changes in receptor density, suggest a major role for CD62L and CD11b in neutrophil function during coliform mastitis.
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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) | 0.000 | 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".