Ciprofloxacin Effects On Nitrogren Cycling Processes In Freshwater Aquatic Sediments
Bibliographic record
Abstract
Four experiments were designed to assess the effect of ciprofloxacin (cipro) on the function of microbial populations in freshwater environments, specifically on nitrogen cycling. Cipro is a broad-spectrum fluoroquinolone antibiotic used in the treatment of both human and veterinary pathogenic diseases. Previous studies reported the presence of cipro in aquatic environments. This study investigates whether cipro has adverse effects on environmental bacteria which perform critical ecosystem processes associated with the nitrogen cycle. Microcosms containing sediment and synthetic lake water were amended with a series of environmentally relevant concentrations of cipro ranging from 0.5 to 2.5 mg cipro per kg of sediment. Nitrogen cycling processes including nitrification, denitrification and ammonification were measured using a combination of flux measurements (NH4+, NO3-, NO2-), stable isotope techniques ( 15[superscript]N NO₃- dilution) and changes in N₂:Ar and O₂:Ar using Membrane Isotope Mass Spectroscopy (MIMS). Results indicate that cipro has a dose-dependent effect on nitrification, while denitrification is dependent on nitrate availability and may be stimulated by cipro. Ammonification and respiration were not affected at these concentrations. Impacts on nitrification and denitrification are likely to be realized only at the highest concentrations measured in the environment. At the lower end of the environmentally relevant concentration range, observed impacts are not likely to be ecologically important, especially when averaged over an entire lake ecosystem.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".