A Satellite dsRNA Attenuates the Induction of Helper Virus-Mediated Symptoms in Aspergillus flavus
Bibliographic record
Abstract
Aspergillus flavus is an important fungal pathogen of animals and plants. Previously, we reported a novel partitivirus, Aspergillus flavus partitivirus 1 (AfPV1), infecting A. flavus. In this study, we obtained a small double-stranded (ds) RNA segment (734 bp), which is a satellite RNA of the helper virus, AfPV1. The presence of AfPV1 altered the colony morphology, decreased the number of conidiophores, created significantly larger vacuoles, and caused more sensitivity to osmotic, oxidative, and UV stresses in A. flavus, but the small RNA segment could attenuate the above symptoms caused by the helper virus AfPV1 in A. flavus. Moreover, AfPV1 infection reduced the pathogenicity of A. flavus in corn (Zea mays), honeycomb moth (Galleria mellonella), mice (Mus musculus), and the adhesion of conidia to host epithelial cells, and increased conidial death by macrophages. However, the small RNA segment could also attenuate the above symptoms caused by the helper virus AfPV1 in A. flavus, perhaps by reducing the genomic accumulation of the helper virus AfPV1 in A. flavus. We used this model to investigate transcriptional genes regulated by AfPV1 and the small RNA segment in A. flavus, and their role in generating different phenotypes. We found that the pathways of the genes regulated by AfPV1 in its host were similar to those of retroviral viruses. Therefore, some pathways may be of benefit to non-retroviral viral integration or endogenization into the genomes of its host. Moreover, some potential antiviral substances were also found in A. flavus using this system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".