Application of XCMS Online and toxicity bioassays to the study of transformation products of levofloxacin
Bibliographic record
Abstract
We studied the nature and antimicrobial activity of ozonolysis transformation products (OTPs) of levofloxacin (LEV), a frequently detected fluoroquinolone antimicrobial in environmental waters. Two bioassays, the Kirby-Bauer test and the broth microdilution assay, were used to measure changes in the antimicrobial activity of solutions at low LEV to O3 molar ratios (2:1, 2:3 and 1:3) compared to solutions without added O3 (LEV:O3 1:0). The Kirby-Bauer test was not sensitive enough to detect significant differences in the growth inhibition zones in samples LEV:O3 2:1 and LEV:O3 1:0; however, the broth microdilution assay showed that bacterial growth inhibition was significantly lower (P<0.001) in the solutions exposed to O3. Loss of antimicrobial activity in LEV:O3 2:1 solutions of (48±16)% was in agreement with the concentration decrease of LEV of (36±3)% in those same samples. A method of identification of OTPs using XCMS Online was applied to LEV:O3 2:1 and 1:0 samples and indicated the presence of an OTP of LEV of formula C18H20O5N3F, which was identified as LEV-N-oxide. The molecular structure of this compound was partially confirmed by tandem mass spectrometry experiments. This study showed that even at sub-optimal ozone doses, OTPs of higher antimicrobial activity than LEV were not formed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".