Physiological Response of Pseudomonas Fluorescens to theDodecyldimethylamine Oxide in the Presence of a WashingFormulation
Bibliographic record
Abstract
Quaternary ammonium compounds (QAC) are unique surfactants, which are widely used as biocides for numerous industrial purposes.An efficiency of disinfectant is highly dependent on the physicochemical properties of environment.The aim of this study was to evaluate the antibacterial effect of the widely used QACs, i.e.N,N-dimethyldodecan-1-amine oxide (DDAO) in mixture with the commercially available surface washing formulation (WF).Pseudomonas fluorescens served as a test organism.The changes in kinetic parameters of bacterial growth, optical density, ATP concentration in the batch cultures, as well as morphological changes of cells were monitored in order to evaluate a physiological response of bacterial cultures to the different combinations of the tested chemicals.A decrease of WF concentration in the broth from 0.1 % to 0.02 % resulted in a gradual reducing the lag period in the presence of 0.03 % DDAO, while the specific growth rate did not depend on the WF concentration.Comparison of the effect of ATP concentration and the OD620 has revealed the differences in cells response to the presence of WF and DDAO.It was concluded that the antibacterial effect of QACs, particularly DDAO, is highly dependent on the composition of washing formulations, which can notably reduce the efficiency of the added QACs.
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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 | 0.000 |
| 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".