Transcriptional Analysis of PRRSV-Infected Porcine Dendritic Cell Response to Streptococcus suis Infection Reveals Up-Regulation of Inflammatory-Related Genes Expression
Bibliographic record
Abstract
The porcine reproductive and respiratory syndrome virus (PRRSV) is one of the most important swine pathogens and often serves as an entry door for other viral or bacterial pathogens, of which Streptococcus suis is one of the most common. Pre-infection with PRRSV leads to exacerbated disease caused by S. suis infection. Very few studies have assessed the immunological mechanisms underlying this higher susceptibility. Since antigen presenting cells play a major role in the initiation of the immune response, the in vitro transcriptional response of bone marrow-derived dendritic cells (BMDCs) and monocytes in the context of PRRSV and S. suis co-infection was investigated. BMDCs were found to be more permissive than monocytes to PRRSV infection; S. suis phagocytosis by PRRSV-infected BMDCs was found to be impaired, whereas no effect was found on bacterial intracellular survival. Transcription profile analysis, with a major focus on inflammatory genes, following S. suis infection, with and without pre-infection with PRRSV, was then performed. While PRRSV pre-infection had little effect on monocytes response to S. suis infection, a significant expression of several pro-inflammatory molecules was observed in BMDCs pre-infected with PRRSV after a subsequent infection with S. suis. While an additive effect could be observed for CCL4, CCL14, CCL20, and IL-15, a distinct synergistic up-regulatory effect was observed for IL-6, CCL5 and TNF-α after co-infection. This increased pro-inflammatory response by DCs could participate in the exacerbation of the disease observed during PRRSV and S. suis co-infection.
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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) | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".