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Record W4403041961 · doi:10.1111/1758-2229.70010

Mixed species biofilms act as planktonic cell factories despite isothiazolinone exposure under continuous‐flow conditions

2024· article· en· W4403041961 on OpenAlexaff
Kyle B. Klopper, Elanna Bester, Martha van Schalkwyk, Gideon Wolfaardt

Bibliographic record

VenueEnvironmental Microbiology Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial biofilms and quorum sensing
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBiocideBiofilmBiomass (ecology)BiofoulingChemistryMetabolic activityPlanktonEnvironmental chemistryMicrobiologyMicroorganismBacteriaPulp and paper industryFood scienceEnvironmental scienceBiologyEcologyBiochemistry

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.006
GPT teacher head0.196
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

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