Effect of Maternal Antibody Transfer on Antibody Dynamics and Control of Porcine Circovirus Type 2 Infection in Offspring
Bibliographic record
Abstract
Sow immunity plays an important role in preventing viral infection and disease in newborn piglets. Vertical transmission of porcine circovirus type 2 (PCV2) may perpetuate porcine circovirus associated disease (PCVAD) in newborn and growing pigs. Hence, the immunological effects of maternal immunoglobulin transfer of PCV2-specific antibodies on PCV2 viremia and immune response in piglets in commercial swine herds were evaluated. Sow vaccination has been shown to reduce viral shedding and viremia, and increases the neutralizing antibody (NA) titers. Since NAs are important for control of PCVAD and mammary secretions may contain high anti-PCV2 NA levels, we examined the PCV2 NA levels in colostrum, milk, sow serum, and piglet serum over time to investigate an association between NA levels and protection against infection. NA titers were remarkably high (up to 10−6 50% neutralizing titer) in sow serum and colostrum on all farms regardless of viremia levels. In piglets vaccinated at 3 weeks of age, NA titers peaked at 10 weeks of age and continued to maintain high viral neutralizing titers to slaughter. The impact of maternally derived neutralizing activity was most evident during the suckling period. Although PCV2 was transmitted from sows to piglets in colostrum, piglets were largely nonviremic at weaning. Thus, NAs appear to control or suppress initial infection even though they are unable to clear or prevent infection later in life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".