Influence of phosphate and disinfection on the composition of biofilms produced from drinking water, as measured by fluorescence in situ hybridization
Bibliographic record
Abstract
Biofilms were grown in annular reactors supplied with drinking water enriched with 235 microg C/L. Changes in the biofilms with ageing, disinfection, and phosphate treatment were monitored using fluorescence in situ hybridization. EUB338, BET42a, GAM42a, and ALF1b probes were used to target most bacteria and the alpha (alpha), beta (beta), and gamma (gamma) subclasses of Proteobacteria, respectively. The stability of biofilm composition was checked after the onset of colonization between T = 42 days and T = 113 days. From 56.0% to 75.9% of the cells detected through total direct counts with DAPI (4'-6-diamidino-2-phenylindole) were also detected with the EUB338 probe, which targets the 16S rRNA of most bacteria. Among these cells, 16.9%-24.7% were targeted with the BET42a probe, 1.8%-18.3% with the ALF1b probe, and <2.5% with the GAM42a probe. Phosphate treatment induced a significant enhancement to the proportion of gamma-Proteobacteria (detected with the GAM42a probe), a group that contains many health-related bacteria. Disinfection with monochloramine for 1 month or chlorine for 3 days induced a reduction in the percentage of DAPI-stained cells that hybridized with the EUB338 probe (as expressed by percentages of EUB338 counts/DAPI) and with any of the ALF1b, BET42a, and GAM42a probes. The percentage of cells detected by any of the three probes (ALF1b+BET42a+GAM42a) tended to decrease, and reached in total less than 30% of the EUB338-hybridized cells. Disinfection with chlorine for 7 days induced a reverse shift; an increase in the percentage of EUB338 counts targeted by any of these three probes was noted, which reached up to 87%. However, it should be noted that the global bacterial densities (heterotrophic plate counts and total direct counts) tended to decrease over the duration of the experiment. Therefore, those bacteria that could be considered to resist 7 days of chlorination constituted a small part of the initial biofilm community, up to the point at which the other bacterial groups were destroyed by chlorination. The results suggest that there were variations in the kinetics of inactivation by disinfectant, depending on the bacterial populations involved.
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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".