PRRSV-infected monocyte-derived dendritic cells express high levels of SLA-DR and CD80/86 but do not stimulate PRRSV-naïve regulatory T cells to proliferate
Bibliographic record
Abstract
In vitro generated monocyte-derived dendritic cells (moDCs) have frequently been used to study the influence of porcine reproductive and respiratory syndrome virus (PRRSV) infection on antigen presenting cells. However, obtained results have often been conflicting in regard to expression of co-stimulatory molecules and interaction with T cells. In this study we performed a detailed phenotypic characterisation of PRRSV-infected moDCs and non-infected moDCs. For CD163 and CD169, which are involved in PRRSV-entry into host cells, our results show that prior to infection porcine moDCs express high levels of CD163 but only very low levels for CD169. Following infection with either PRRSV-1 or PRRSV-2 strains after 24 h, PRRSV-nucleoprotein (N-protein)(+) and N-protein(-) moDCs derived from the same microculture were analyzed for expression of swine leukocyte antigen-DR (SLA-DR) and CD80/86. N-protein(+) moDCs consistently expressed higher levels of SLA-DR and CD80/86 compared to N-protein(-) moDCs. We also investigated the influence of PRRSV-infected moDCs on proliferation and frequency of Foxp3(+) regulatory T cells present within CD4(+) T cells in in vitro co-cultures. Neither CD3-stimulated nor unstimulated CD4(+) T cells showed differences in regard to proliferation and frequency of Foxp3(+) T cells following co-cultivation with either PRRSV-1 or PRRSV-2 infected moDCs. Our results suggest that a more detailed characterisation of PRRSV-infected moDCs will lead to more consistent results across different laboratories and PRRSV strains as indicated by the major differences in SLA-DR and CD80/86 expression between PRRSV-infected and non-infected moDCs present in the same microculture.
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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) | 0.001 | 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".