The mechanism of action of micafungin against pteropine orthoreovirus infection in the human A549 cell line
Bibliographic record
Abstract
Pteropine orthoreovirus (PRV) is a fusogenic virus carried by bats that causes respiratory illnesses in humans. Micafungin (MCFG), an approved drug for treatment of fungal infections, has been shown to inhibit the propagation of PRV, but its precise mechanism of action remains unclear. In this study, we investigated the molecular mechanism of action of MCFG against PRV propagation. A molecular docking simulation showed that the p17 protein of PRV is likely to be the primary target of MCFG. Differential gene expression analysis was performed to compare MCFG-treated PRV-infected host cells with untreated infected cells, and IL-6 was found to be the main regulator induced by MCFG. Silencing of IL-6 using siRNA resulted in markedly increased levels of PRV release and syncytium formation and marginally increased PRV RNA replication. Treatment with an antibody against p17, the presumed target of MCFG, markedly reduced syncytium formation but did not influence viral RNA replication. In contrast, MCFG significantly suppressed syncytium formation and slightly reduced PRV RNA replication, and MCFG and anti-p17 antibody both increased IL-6 mRNA expression. Molecular docking analysis also suggested that MCFG might inhibit other PRV proteins, including the nonstructural replication protein σNS. In conclusion, it is likely that MCFG primarily targets p17 and modulates host immunity through IL-6, which probably interferes directly with syncytium formation.
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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 | 0.001 |
| 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".