Effects of Different Drug Combinations in Immunodeficient Mice Infected with an Influenza A/H3N2 Virus
Bibliographic record
Abstract
The prolonged treatment of immunosuppressed (IS) individuals with anti-influenza monotherapies may lead to the emergence of drug-resistant variants. Herein, we evaluated oseltamivir and polymerase inhibitors combinations against influenza A/H3N2 infections in an IS mouse model. Mice were IS with cyclophosphamide and infected with 3 × 103 PFU of a mouse-adapted A/Switzerland/9715293/2013 (H3N2) virus. Forty-eight hours post-infection, the animals started oseltamivir, favipiravir or baloxavir marboxil (BXM) as single or combined therapies for 10 days. Weight losses, survival rates and lung viral titers (LVTs) were determined. The neuraminidase (NA) and polymerase genes from lung viral samples were sequenced. All untreated animals died. Oseltamivir and favipiravir monotherapies only delayed mortality (the mean day to death (MDD) of 21.4 and 24 compared to 11.4 days for those untreated) while a synergistic improvement in survival (80%) and LVT reduction was observed in the oseltamivir/favipiravir group compared to the oseltamivir group. BXM alone or in double/triple combination provided a complete protection and significantly reduced LVTs. Oseltamivir and BXM monotherapies induced the E119V (NA) and I38T (PA) substitutions, respectively, while no resistance mutation was detected with combinations. We found that the multiple dose regimen of BXM alone provided superior benefits compared to oseltamivir and favipiravir monotherapies. Moreover, we suggest the potential for drug combinations to reduce the incidence of resistance.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".