Atorvastatin does not display an antimicrobial activity on its own nor potentiates the activity of other antibiotics against Acinetobacter baumannii ATCC17978 or A. baumannii AB030
Bibliographic record
Abstract
With the current arsenal of antibiotics increasingly becoming ineffective against bacteria, there is an increasing interest in the possibility of using previously approved non-antibiotic drugs as antimicrobials. Statins have recently been investigated for their antimicrobial activity and their ability to potentially synergize with current treatment options. Atorvastatin had been shown previously to be the most promising candidate for effectivity against Acinetobacter baumannii ATCC17978. In this study, we tested atorvastatin for its activity against an extensively drug-resistant (XDR) strain A. baumannii AB030. However, our data show that atorvastatin has no effect A. baumannii AB030. Intriguingly, atorvastatin was also ineffective against our laboratory’s A. baumannii ATCC17978. This lack of atorvastatin activity against A. baumannii ATCC17978 cannot be attributed to RND efflux pumps as a strain deficient in the three most clinically relevant RND efflux systems in A. baumannii showed no change in susceptibility compared to its parent strain ATCC17978. Further, atorvastatin failed to potentiate the activity of tobramycin and ciprofloxacin. While it is not clear to us why atorvastatin is not active against A. baumannii ATCC17978 used in our study, our study shows that evaluation of compounds for their antibacterial activity should involve multiple strains to account for strain-to-strain variation.
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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) | 0.002 | 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".