The miRNA-targeted transcriptome of porcine alveolar macrophages upon infection with Porcine Reproductive and Respiratory Syndrome Virus
Bibliographic record
Abstract
Host miRNAs are known to modulate the cell response to virus infections. We characterized the miRNA-targeted transcriptome of porcine alveolar macrophages (PAMs) at early times after infection with a subtype 1.1 strain of PRRSV (Porcine Reproductive and Respiratory Syndrome Virus). We performed the immunoprecipitation of RISC (RNA-induced Silencing Complex) followed by microarray analysis of the RISC-bound miRNA targets (RIP-Chip) to evaluate the relative enrichment or depletion of expressed genes in RISC. The miRNA-mediated regulation occurred early after PRRSV infection and decreased fast (1,241 and 141 RISC-bound genes at 7 h and 10 h post-infection, respectively); it affected several cell functions with evidence of miRNA buffering of upregulated interferon-related genes. Eight miRNAs were highly enriched in RISC of both control and infected cells with no evidence of differential expression. Although miR-335-5p was the miRNA with most predicted targets among enriched RISC-bound genes, no effects on surface markers, cytokine expression and PRRSV replication were detected upon miR-335-5p mimics of primary PAMs. Our results do not point to specific miRNA-driven mechanisms regulating the early response to infection with this PRRSV 1.1 strain and indicate that the miRNome expressed by steady-state PAMs reacts promptly to counterbalance PRRSV infection by a pervasive modulation of host functions.
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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".