Remdesivir does not affect mitochondrial DNA copy number or deletion mutation frequency in aged male rats: A short report
Bibliographic record
Abstract
Remdesivir is a leading therapy in patients with moderate to severe coronavirus 2 (SARS-CoV-2) infection; the majority of whom are older individuals. Remdesivir is a nucleoside analog that incorporates into nascent viral RNA, inhibiting RNA-directed RNA polymerases, including that of SARS-CoV-2. Less is known about remdesivir's effects on mitochondria, particularly in older adults where mitochondria are known to be dysfunctional. Furthermore, its effect on age-induced mitochondrial mutations and copy number has not been previously studied. We hypothesized that remdesivir adversely affects mtDNA copy number and deletion mutation frequency in aged rodents. To test this hypothesis, 30-month-old male F333BNF1 rats were treated with remdesivir for three months. To determine if remdesivir adversely affects mtDNA, we measured copy number and mtDNA deletion frequency in rat hearts, kidneys, and skeletal muscles using digital PCR. We found no effects from three months of remdesivir treatment on mtDNA copy number or deletion mutation frequency in 33-month-old rats. These data support the notion that remdesivir does not compromise mtDNA quality or quantity at old age in mammals. Future work should focus on examining additional tissues such as brain and liver, and extend testing to human clinical samples.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".