Synthesis of Modified Guanidine-Based Polymers and their Antimicrobial Activities Revealed by AFM and CLSM
Bibliographic record
Abstract
Modified guanidine-based polymers with chain extension were synthesized by condensation and cross-linking polymerizations in an attempt to increase molecular weight and charge density of the antimicrobial polymers. The antimicrobial activity and the corresponding mechanisms were investigated by several approaches. The results indicated that the antimicrobial activities of the modified guanidine-based polymer, based on the minimum inhibition concentration (MIC) against E.coli, varied with alkyl monomer ratios. UV absorption at 260 nm further quantified the amount of intracellular components leaked into bacteria suspension. The UV absorption measurements were also used to monitor inhibition processes dynamically. It was found that the modified guanidine-based polymer inhibited the growth of bacteria by causing membrane compromised and intracellular leaked. Dual fluorescent dyes were used to stain all bacteria including the dead ones, which enabled us to utilize CLSM to visualize the viability of bacteria in the presence of various modified guanidine-based polymers without causing any damage. The morphologies of bacteria untreated and treated with modified guanidine-based polymer were observed using an atomic force microscope (AFM), which further demonstrated the damage of E.coli membrane and the leakage of intracellular component induced by the modified guanidine-based polymers.
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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".