Multi-species biofilms defined from drinking water microorganisms provide increased protection against chlorine disinfection
Bibliographic record
Abstract
A model biofilm, formed of multiple species from environmental drinking water, including opportunistic pathogens, was created to explore the tolerance of multi-species biofilms to chlorine levels typical of water-distribution systems. All species, when grown planktonically, were killed by concentrations of chlorine within the World Health Organization guidelines (0.2-5.0 mg l(-1)). Higher concentrations (1.6-40-fold) of chlorine were required to eradicate biofilm populations of these strains, ~70% of biofilms tested were not eradicated by 5.0 mg l(-1) chlorine. Pathogenic bacteria within the model multi-species biofilms had an even more substantial increase in chlorine tolerance; on average ~700-1100 mg l(-1) chlorine was required to eliminate pathogens from the biofilm, 50-300-fold higher than for biofilms comprising single species. Confocal laser scanning microscopy of biofilms showed distinct 3D structures and multiple cell morphologies and arrangements. Overall, this study showed a substantial increase in the chlorine tolerance of individual species with co-colonization in a multi-species biofilm that was far beyond that expected as a result of biofilm growth on its own.
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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) | 0.000 | 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 | 0.001 |
| Research integrity | 0.001 | 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 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".