PLGA nanoparticle-entrapped inactivated porcine reproductive and respiratory syndrome virus vaccine coadministered intranasally with a potent adjuvant elicits cross-protective immunity in the pig respiratory system (VAC7P.981)
Bibliographic record
Abstract
Abstract Porcine reproductive and respiratory syndrome (PRRS) is caused by a highly mutagenic RNA virus, PRRS virus (PRRSV). Currently used vaccines have failed to prevent PRRS outbreaks induced losses of estimated one billion dollar annually to the US pig farmers. The PRRSV infects primarily the lung macrophages. Because of safety advantage, we attempted to strengthen the immunogenicity of killed PRRSV vaccine antigens (KAg) in the pig respiratory system. We entrapped the KAg in biodegradable PLGA nanoparticles (NP-KAg) and coadministered the NP-KAg with a potent mucosal adjuvant, whole cell lysate of Mycobacterium tuberculosis (M. tb WCL), twice intranasally to growing pigs and challenged with a heterologous virus. Our results indicated that formulation of NP-KAg and unentrapped soluble M. tb WCL significantly cleared detectable replicating infective PRRSV with a 10-fold reduction in viral RNA load in the lungs, associated with substantially reduced microscopic lung pathology. Immunologically, enhanced virus neutralizing antibody titers by high avidity antibodies and augmented populations of IFN-γ secreting CD4+ and CD8+ lymphocytes, and reduced secretion of TGFbeta was detected in the lungs. Currently, we are in the process of identifying PRRSV epitope-specific T-cell response and frequency of apoptotic/necrotic immune cells in the lungs of vaccinated pigs. In conclusion, our vaccine formulation elicited broadly cross-protective anti-PRRSV immunity in the pig respiratory system.
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 | 0.000 |
| 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".