Milk and Serum J5-Specific Antibody Responses, Milk Production Change, and Clinical Effects following Intramammary <i>Escherichia coli</i> Challenge for J5 Vaccinate and Control Cows
Bibliographic record
Abstract
Holstein dairy cows (four J5 vaccinates and four controls) selected for no recorded intramammary disease and low somatic cell count (SCC) during the previous lactation were challenged by intramammary infusion of Escherichia coli. Vaccination with J5 was at 8 weeks and again 4 weeks before the anticipated calving date. Cows were challenged at 8 to 16 days in milk (DIM). Shedding of E. coli in milk was significantly higher among controls than vaccinates (no shedding) from 6 h to 21 h postchallenge. From 21 h to 132 h postchallenge, SCC in challenged quarters of controls (5,429,000/ml) was significantly higher than that of vaccinates (490,000/ml). On the day after challenge, milk production in control cows was 8 kg less, while vaccinates gained 0.5 kg, a significant difference. In serum immediately prior to challenge, J5-specific immunoglobulin G1 (IgG1) was significantly higher, IgG2 was nearly significantly higher, and IgM was the same in J5 vaccinates relative to controls. Vaccinates had proportionally more IgG2 in serum postcalving and in the first 12 h following challenge and less IgG2 in milk 24 h after challenge than the controls, approaching statistical significance. The ratio of J5-specific IgG1 and IgG2 combined compared to IgM was significantly higher in vaccinates than in controls in prechallenge serum (ratios of 15.8 and 3.2, respectively) and milk (5.0 and 1.3, respectively). Cows with higher IgM titers in milk 12 h postchallenge produced significantly less milk. Vaccination with J5 was significantly associated with higher production of J5-specific IgG1 and IgG2 in early lactation, reduced SCC, faster clearance of E. coli from milk, and less milk production loss following intramammary challenge.
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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 | 0.001 | 0.001 |
| 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".