Role of Membrane Permeabilization and Ergosterol Content in the Inhibitory Activity of Membrane-Targeting Antimicrobials
Bibliographic record
Abstract
The growing resistance of fungal pathogens to synthetic fungicides and their environmental impact calls for the development and research of sustainable alternatives.This study investigated the effectiveness of membrane-targeting antimicrobial compound and how fungal membrane composition, including the fungal membrane sterol ergosterol, modulates the effectiveness of various membrane-targeting antifungal compounds including nystatin, iturin, fengycin, surfactin, nisin, and daptomycin.Using unilamellar liposomes with varying ergosterol levels as model membranes, the research explores how these compounds interact with fungal membranes, focusing on changes in size, polydispersity index (PDI), and ζ-potential.The results demonstrated that ergosterol rich membranes are most susceptible to nystatin and iturin, which directly bind to ergosterol and disrupt membrane integrity.In contrast, surfactin and nisin exhibit antifungal activity through different mechanisms that do not rely on increasing membrane permeability.The findings emphasize the critical role of ergosterol in determining antifungal efficacy and provide insights into optimizing antifungal strategies.
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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".