Repurposing of escitalopram oxalate and clonazepam in combination with ciprofloxacin and sulfamethoxazole–trimethoprim for treatment of multidrug-resistant microorganisms and evaluation of the cleavage capacity of plasmid DNA
Bibliographic record
Abstract
Bacterial resistance has become one of the most serious public health problems, globally, and drug repurposing is being investigated to speed up the identification of effective drugs. The aim of this study was to investigate the repurposing of escitalopram oxalate and clonazepam drugs individually, and in combination with the antibiotics ciprofloxacin and sulfamethoxazole-trimethoprim, to treat multidrug-resistant (MDR) microorganisms and to evaluate the potential chemical nuclease activity. The minimum inhibitory concentration, minimum bactericidal concentration, fractional inhibitory concentration index, and tolerance level were determined for each microorganism tested. In vitro antibacterial activity was evaluated against 47 multidrug-resistant clinical isolates and 11 standard bacterial strains from the American Type Culture Collection. Escitalopram oxalate was mainly active against Gram-positive bacteria, and clonazepam was active against both Gram-positive and Gram-negative bacteria. When associated with the two antibiotics mentioned, they had a significant synergistic effect. Clonazepam cleaved plasmid DNA, and the mechanisms involved were oxidative and hydrolytic. These results indicate the potential for repurposing these non-antibiotic drugs to treat bacterial infections. However, further studies on the mechanism of action of these drugs should be performed to ensure their safe use.
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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 | 0.000 |
| 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".