New Generation of <i>N</i>-Chloramine/QAC Composite Biocides: Efficient Antimicrobial Agents To Target Antibiotic-Resistant Bacteria in the Presence of Organic Load
Bibliographic record
Abstract
Abstract We previously reported that covalently joining an amide-based N-chloramine with a quaternary ammonium compound (QAC) can yield a new composite biocide with faster inactivation of various bacteria. Importantly, the composite biocide was found to reduce the risk for potential bacterial resistance associated with QAC. However, similar to other N-chloramines and QACs, this high-performance composite biocide becomes less potent against pathogenic bacteria in the presence of high protein fluids. In this study, we substituted the amide-based N-chloramine moiety in the previously reported composite biocide with a secondary amine-based N-chloramine to improve the biocidal efficacy in biological fluids. The N–Cl bond in the synthesized tetramethylpiperidine-based composite biocides is more stable in a high protein medium (HPM) than that in the hydantoin (amide)-based composite biocides. The composite biocide, 2-[4-(1-chloro-2,2,6,6-tetramethyl-piperidin-4-yloxymethyl)-[1,2,3]triazol-1-yl]-ethyl-dodecyl-dimethyl-ammonium chloride (6a), showed the best antibacterial activity in both phosphate-buffered saline and HPM among various composite biocides and benzyldodecyldimethylammonium chloride used in this study.
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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".