Mixed species biofilms act as planktonic cell factories despite isothiazolinone exposure under continuous‐flow conditions
Bibliographic record
Abstract
Abstract The primary approach to managing biofouling in industrial water systems involves the large‐scale use of biocides. It is well‐established that biofilms are ‘cell factories’ that release planktonic cells even when challenged with antimicrobials. The effect of isothiazolinone on the metabolic activity and biomass of mixed Pseudomonas biofilms was monitored in real‐time using the CEMS‐BioSpec system. The exposure of biofilms to the minimum inhibitory concentration (1.25 mg L −1 ) of biocide did not impact planktonic cell production (log 7.5 CFU mL −1 ), while whole‐biofilm metabolic activity and biomass accumulation increased. Only the maximum biocide concentration (80 mg L −1 ) resulted in a change in planktonic cell yields and temporal inhibition of biofilm activity and biomass, a factor that needs due consideration in view of dilution in industrial settings. Interfacing the real‐time measurement of metabolic activity and biomass with dosing systems is especially relevant to optimizing the use of biocides in industrial water systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".