Interaction of LL-37 human cathelicidin peptide with a model microbial-like lipid membrane
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The only representative of cathelicidin peptides in humans is LL-37, a multifunctional antimicrobial peptide (AMP) that is a part of the innate immune response. Details of the LL-37 direct activity against pathogens are not well understood at the molecular level. Here, we present research on the mechanism of interaction between LL-37 and a model multicomponent bilayer lipid membrane (BLM), mimicking microbial cell membrane. Electrochemical impedance spectroscopy (EIS), high-resolution atomic force microscopy (AFM) imaging, and polarization-modulation infrared reflection-absorption spectroscopy (PM-IRRAS) were applied to study the peptide influence on a model microbial-like membrane. We show that LL-37 causes changes in the phospholipid molecules conformation and orientation, leading to membrane disintegration, significantly affecting the membrane electrical parameters, such as capacitance and resistance. High-resolution AFM imaging shows topographical and mechanical effects of such disintegration, while PM-IRRAS data indicates that introduction of LL-37 causes changes in the phospholipid acyl chains from all-trans to gauche conformations. Moreover, the presence of LL-37 significantly alters the value of the phospholipid tilt angle. Altogether, our results suggest a "carpet" membrane dissolution followed by a detergent-like membrane disruption mechanism upon LL-37 activity. This research gives a novel insight into the understanding of LL-37 influence on multicomponent model membranes and a promising contribution to the development of LL-37-derived therapeutic agents against drug-resistant bacteria.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it