Characterization of the antibody isotype response in serum and milk of heifers vaccinated with a <i>Staphylococcus aureus</i> bacterin (Lysigin<sup>TM</sup>)
Bibliographic record
Abstract
The objective was to characterize the antibody isotype responses to vaccination with a commercial Staphylococcus aureus bacterin in dairy heifers. Twenty-five Holstein-Friesian dairy heifers were assigned at random to one of two groups, vaccinates (n=14) or controls (n=11). Vaccinates received two 5-ml doses of Lysigin 28 d apart in late gestation. Both groups were challenged with a heterologous serotype 5 strain of Staph. aureus by aseptic intramammary infusion on days 6, 7 and 8 of lactation. Samples for serum antibody isotype (IgG, IgG1, IgG2 and IgM) determinations were taken before each vaccination, immediately prior to challenge (6 d post-calving) and at the end of the study (28 d post-calving). Samples for milk antibody isotype determinations were taken immediately prior to challenge and at the end of the study. Antibody isotype sample-to-positive ratios (S:P ratio=(mean test sample OD-mean within-plate negative control OD)/(mean within-plate positive control OD-mean within-plate negative control OD)) were determined in milk and serum using a series of ELISAs coated with different strains of Staph. aureus belonging to capsular polysaccharide (CP) serotype 5 or 8 or surface polysaccharide (SP) serotype 336. Vaccinates had higher mean serum IgG1 and IgG2 S:P ratios than controls against all three strains of Staph. aureus (P < or = 0.023). Vaccinates had higher mean milk IgG S:P ratios than controls against CP8 and SP336 strains of Staph. aureus (P< or = 0.030). Hence, a humoural immune response to the vaccine was detected in serum and milk, but responses varied according to strain and antibody isotype tested.
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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".