Longitudinal comparison of the humoral immune response and viral load of Porcine Circovirus Type 2 in pigs with different vaccination schemes under field conditions
Bibliographic record
Abstract
<ns4:p> <ns4:bold>Background:</ns4:bold> Porcine Circovirus type 2 (PCV2) infections are distributed worldwide and cause Porcine Circovirus Associated Disease (PCVAD). To minimize the impact of PCV2 infection on swine health and production, different vaccination schemes have been used since 2006. However, the association between vaccination schemes, virus load and disease under field conditions are not completely understood. Therefore, the objective of this study was to compare the effect of two different PCV2 vaccination schemes on the humoral response and PCV2 load in pigs after weaning under field conditions. </ns4:p> <ns4:p> <ns4:bold>Methods:</ns4:bold> Two commercial pig farms (Farm A and B), endemically infected with PCV2, which were using two different PCV2 subunit vaccinations schemes for sow, gilts and piglets, were selected. We designed a longitudinal study and measured IgG levels by ELISA and virus load by quantitative PCR in pigs after weaning. Forty 3-week old piglets were randomly selected at weaning and followed for 20 weeks. IgG levels and virus loads were compared within and between farms and considered statistically different if the non-parametric Kruskal Wallis test p value was lower than 0.05. </ns4:p> <ns4:p> <ns4:bold>Results:</ns4:bold> We found that low virus loads were maintained in pigs from both farms regardless of the vaccination scheme used (p>0.05). However, there was significant difference in the mean IgG levels observed over time (p<0.05), suggesting that different humoral immune response are not necessarily associated with different virus loads observed over time. </ns4:p> <ns4:p> <ns4:bold>Conclusions:</ns4:bold> These results are important because they can help to prevent PCV2 infections using different vaccination schemes to minimize the effect of PCVAD on swine health and production. </ns4:p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".