Ubiquitous Nature of Fluoroquinolones: The Oscillation between Antibacterial and Anticancer Activities
Bibliographic record
Abstract
Fluoroquinolones are synthetic antibacterial agents that stabilize the ternary complex of prokaryotic topoisomerase II enzymes (gyrase and Topo IV), leading to extensive DNA fragmentation and bacteria death. Despite the similar structural folds within the critical regions of prokaryotic and eukaryotic topoisomerases, clinically relevant fluoroquinolones display a remarkable selectivity for prokaryotic topoisomerase II, with excellent safety records in humans. Typical agents that target human topoisomerases (such as etoposide, doxorubicin and mitoxantrone) are associated with significant toxicities and secondary malignancies, whereas clinically relevant fluoroquinolones are not known to exhibit such propensities. Although many fluoroquinolones have been shown to display topoisomerase-independent antiproliferative effects against various human cancer cells, those that are significantly active against eukaryotic topoisomerase show the same DNA damaging properties as other topoisomerase poisons. Empirical models also show that fluoroquinolones mediate some unique immunomodulatory activities of suppressing pro-inflammatory cytokines and super-inducing interleukin-2. This article reviews the extended roles of fluoroquinolones and their prospects as lead for the unmet needs of "small and safe" multimodal-targeting drug scaffolds.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".