Synergistic Removal of Ciprofloxacin and Sulfamethoxazole by Lemna minor and Salvinia molesta in Mixed Culture: Implications for Phytoremediation of Antibiotic-Contaminated Water
Bibliographic record
Abstract
Aquatic macrophytes have been used for the removal of antibiotics from contaminated water. Here, we have studied the capacity of Lemna minor and Salvinia molesta to reclaim ciprofloxacin (1.5 µg Cipro L−1) and/or sulfamethoxazole (0.3 µg Sulfa L−1) from artificially contaminated waters when plants were exposed in monoculture (L. minor or S. molesta) or in mixed culture (L. minor + S. molesta). Neither Cipro nor Sulfa alone induced negative effects on plants. As shown by the Abbot modelling, Cipro and Sulfa displayed antagonistic effects on plants. In both species, increased H2O2 concentrations and antioxidant enzyme activities were observed in plants when grown together. Although the antibiotics showed natural degradation, their concentration in water from treatments with plants was significantly lower, indicating the ability of the plants to uptake the compounds. When in co-culture, greater growth rates were observed for both plant species, which resulted in greater Cipro and Sulfa removal in the mixed system when compared with those with plants in monoculture. Both plants showed tolerance to the studied concentrations of antibiotics, with greater antibiotic uptake being reported for S. molesta. Although at the tested concentrations the antibiotics did not induce negative effects on plants, exposure to Cipro changed the relative yield of S. molesta, which may result in effects on community structure. The use of both L. minor and S. molesta in artificial wetlands may increase the phytoremediation capacity of systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".