Community-Level Assessment of the Effects of the Broad-Spectrum Antimicrobial Chlorhexidine on the Outcome of River Microbial Biofilm Development
Bibliographic record
Abstract
Chlorhexidine is a common-use antibacterial agent found in a range of personal-care products. We used rotating annular reactors to cultivate river biofilms under the influence of chlorhexidine or its molar equivalent in nutrients. Studies of the degradation of [(14)C]chlorhexidine demonstrated that no mineralization of the compound occurred. During studies with 100 microg liter(-1) chlorhexidine, significant changes were observed in the protozoan and micrometazoan populations, the algal and cyanobacterial biomass, the bacterial biomass, and carbon utilization. Denaturing gradient gel electrophoresis (DGGE) in combination with statistical analyses showed that the communities developing under control and 100 microg liter(-1) chlorhexidine were significantly different. At 10 microg liter(-1) chlorhexidine, there was significantly increased algal and cyanobacterial biomass while the bacterial biomass was not significantly affected (P < 0.05). No significant effects on protozoan or metazoan grazing were detected at the 10-microg liter(-1) chlorhexidine level. Fluorescent in situ hybridization indicated a significant reduction in the abundance of betaproteobacteria and gammaproteobacteria (P < 0.05). Archaeal cell counts were significantly reduced by both chlorhexidine and nutrient treatments. DGGE and statistical analyses indicated that 10 microg liter(-1) chlorhexidine and molar equivalent nutrient treatments were significantly different from control communities. In contrast to community level observations, toxicological testing with a panel of cyanobacteria, algae, and protozoa indicated no detectable effects at 10, 50, and 100 microg liter(-1) chlorhexidine. Thus, community level assessment indicated a risk of low levels of chlorhexidine in aquatic habitats while conventional approaches did not.
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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) | 0.000 | 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".