Host Long Noncoding RNA lncRNA-PAAN Regulates the Replication of Influenza A Virus
Bibliographic record
Abstract
The productive infection of influenza A virus (IAV) depends on host factors. However, the involvement of long non-coding RNAs (lncRNAs) in IAV infection remains largely uninvestigated. In this work, we have discovered a human lncRNA, named lncRNA-PAAN (PA-associated noncoding RNA) that enhances IAV replication. The level of lncRNA-PAAN increases upon infection of IAV, but not other viruses, nor interferon treatment, suggesting specific up-regulation of lncRNA-PAAN expression by IAV. Silencing lncRNA-PAAN significantly decreases IAV replication through impairing the activity of viral RNA-dependent RNA polymerase (RdRp). This function of lncRNA-PAAN is a result of its association with viral PA protein, a key component of IAV RNA polymerase complex. Consequently, depletion of lncRNA-PAAN prevents the formation of functional RdRp. Together, these results suggest that lncRNA-PAAN promotes the assembly of viral RNA polymerase, thus warranting efficient viral RNA synthesis. Elucidating the functions of lncRNAs in IAV infection is expected to advance our understanding of IAV pathogenesis and open new avenues to the development of novel anti-IAV therapeutics.
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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".