Swine influenza A virus infection sets the local immunological landscape in subsequent infection with porcine reproductive and respiratory syndrome virus
Bibliographic record
Abstract
Abstract Farmed pigs are frequently exposed to respiratory infections, with swine influenza A virus (swIAV) and porcine reproductive and respiratory syndrome virus (PRRSV) being key drivers. Most co-infection studies with these viruses have focused on PRRSV infection followed by swIAV. However, the reverse scenario, where swIAV is given first and then PRRSV, has not been explored. This infection sequence is plausible under natural conditions and warrants further study, especially given that influenza A virus has been shown in mice to impair alveolar macrophages, which are the target cells for PRRSV. This study aimed to evaluate the impact of swIAV infection on the alveolar macrophage population, clinical signs, immune responses, and viral loads during a secondary infection with PRRSV initiated 7 days after the initial swIAV exposure. Results demonstrated that primary swIAV infection did not exacerbate the clinical progression of PRRSV infection, nor did it result in significant differences in PRRSV loads or affect the alveolar macrophage population in the lungs of super-infected pigs as compared to those of pigs infected with PRRSV alone. However, swIAV pre-infection was associated with an increase in the number of conventional dendritic cells type 1 (cDC1), perforin-expressing T cells and NK-related lymphocytes in bronchoalveolar lavage. This coincided with an increase of PRRSV-specific IFN-γ producing CD4 T cells in blood detected 7 days post-PRRSV infection. These findings suggest that a swIAV infection could enhance immune responses during subsequent PRRSV infection by recruiting cDC1 and inducing IL-12, promoting a type-1 immune response, highlighting the complex interplay and often unexpected outcomes of viral co-infections occurring in close temporal proximity.
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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) | 0.002 | 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".