White-nose syndrome is associated with increased replication of a naturally persisting coronaviruses in bats
Bibliographic record
Abstract
Spillover of viruses from bats to other animals may be associated with increased contact between them, as well as increased shedding of viruses by bats. Here, we tested the prediction that little brown bats (Myotis lucifugus) co-infected with the M. lucifugus coronavirus (Myl-CoV) and with Pseudogymnoascus destructans (Pd), the fungus that causes bat white-nose syndrome (WNS), exhibit different disease severity, viral shedding and molecular responses than bats infected with only Myl-CoV or only P. destructans. We took advantage of the natural persistence of Myl-CoV in bats that were experimentally inoculated with P. destructans in a previous study. Here, we show that the intestines of virus-infected bats that were also infected with fungus contained on average 60-fold more viral RNA than bats with virus alone. Increased viral RNA in the intestines correlated with the severity of fungus-related pathology. Additionally, the intestines of bats infected with fungus exhibited different expression of mitogen-activated protein kinase pathway and cytokine related transcripts, irrespective of viral presence. Levels of coronavirus antibodies were also higher in fungal-infected bats. Our results suggest that the systemic effects of WNS may down-regulate anti-viral responses in bats persistently infected with M. lucifugus coronavirus and increase the potential of virus shedding.
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".