Lethal weapon IL: a nano-copper/tetraalkylphosphonium ionic liq-uid composite material with potent antibacterial activity
Bibliographic record
Abstract
Ionic liquid (IL) based composite materials have shown great promise as antimicrobial coatings, owing to their inherent germicidal properties, as well as their ability to stabilize metal nanoparticles (NPs), which may serve as a secondary antimicrobial reservoir. Here, we show that tetraalkylphosphonium ILs (TAPILs) on their own can annihilate pathogens by interfering with their cell membranes; however, the nature of the alkyl substituents on the central P atom and the nature of the anion play decisive roles in determining their antimicrobial activities. Con-comitantly, TAPILs can stabilize copper nanoparticles (Cu NPs) generated directly within the IL matrices without the addition of any second-ary stabilizers. The composites thus generated were thoroughly characterized and shown to be far more lethal to E. coli than just the TAPILs. The antibacterial effect demonstrated by the composite created from P[6,6,6,8]Cl (TAPIL-2) was orders of magnitude more lethal to microbes in comparison with P[6,6,6,8]Cl or copper nanoparticles alone. Neither the parent TAPIL-2 nor composite-2 were compromised by ambient storage conditions over a period of months with regards to their bactericidal effects. The composite with the best performance (composite-2) also proved to be effective against a panel of selected microbes. SEM studies were conducted to image E. coli after exposure to the TAPILs or composite-2; with the latter, only bacterial debris were noticed post-exposure, indicating total bacterial annihilation. The killing kinetic assay and regression analyses for time-dependent bactericidal activity of composite-2 against E. coli and S. aureus demonstrated increase in log re-duction values over time, indicating the effectiveness of composite-2 in reducing the viable cell counts for both bacterial strains. Finally, Cu K-edge XANES was used to investigate the fate of Cu NPs within the composites, revealing oxidative disintegration of the Cu NPs within the TAPIL matrices over time, releasing charged copper ions and/or small copper clusters which interfere with the integrity and the permeability of E. coli cell membranes, inducing cell death. This was confirmed by SEM of bacterial preparations before and after exposure to both the TAPILs themselves as well as to the composites. Exposing E. coli to composite-2 causes complete cellular destruction, leaving behind cellular debris as the only visible organic matter. Thus, these TAPIL-based composites containing ‘ion reservoir’ metal NPs are potent antimicrobial materials, deserving additional research.
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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 | 0.001 |
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".