Influence of Human Urine on the in vitro Activity and Postantibiotic Effect of Ciprofloxacin against Escherichia coli
Bibliographic record
Abstract
The purpose of this investigation was to study the effects of human urine on the minimum inhibitory concentration (MIC) and the postantibiotic effect (PAE) of ciprofloxacin against Escherichia coli. MICs and the PAE were performed in Mueller-Hinton broth (MHB; pH 7.3 and 5.5) and in human urine (pH 5.5 and 7.3). In urine, pH 5.5, MICs increased 64-fold (from 0.016 to 1.024 micrograms/ml) and the PAE was abolished (from 101.6 to 3.7 min), when compared to MHB, pH 7.3. An acidic pH demonstrated the greatest effect on reduced susceptibility and PAE. Using ciprofloxacin concentrations adjusted for a higher MIC obtained in pH-adjusted urine and MHB, PAE values were similar for urine and MHB (approximately 280 min at 40 x MIC). This study demonstrated that the MIC and PAE of ciprofloxacin against E. coli are influenced by human urine and in particular its pH.
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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 | 0.002 |
| 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".