High Speed AFM and NanoInfrared Spectroscopy Investigation of Aβ1–42 Peptide Variants and Their Interaction With POPC/SM/Chol/GM1 Model Membranes
Bibliographic record
Abstract
Due to an ageing population, neurodegenerative diseases such as Alzheimer’s disease (AD) have become a major health issue. In the case of AD, Aβ1-42 peptides, through the formation of senile plaques via their aggregation, have been clearly identified as one of the trigger agents that play a role in memory impairment and other tragic syndromes associated with the disease. Many studies have shown that not only the morphology and structure of Aβ1-42 peptide assembly are playing an important role in the formation of amyloid plaques, but also the interactions between Aβ1-42 and the cellular membrane are crucial regarding the fibrillogenesis and toxicity of the amyloid peptides. Though these studies brought valuable information to the field, questions arise especially concerning the molecular mechanisms involved in AD, which remain elusive and require in-depth investigation at the local scale to clearly decipher the role of the sequence of the amyloid peptides, their secondary structures, their oligomeric state and of their interaction with lipidic membranes. In this original study, through the use of Atomic Force (AFM) related-techniques, high-speed AFM and nanoInfrared AFM, we tried to unravel at the nanoscale the link between aggregation state, structure and interaction with membranes in the amyloid / membrane interaction. Using three mutants of Aβ peptides, L34T, oG37C and WT Aβ1-42 peptides, with differences in morphology, structure and assembly process, as well as model lipidic membranes whose composition and structure allow interactions with the peptides, our AFM study coupling high spatial and temporal resolution and nanoscale structure information clearly evidence a local correlation between the secondary structure of the peptides, their fibrillation kinetics and their interactions with model membranes. The membrane disruption is associated to amyloid species that i) present strong interactions with the membrane, as well as ii) an antiparallel β-sheet secondary structure, and iii) are only transient small oligomeric entities in the early stages of aggregation. The strong interaction between oligomeric species and the membrane in Aβ1-42 toxicity is therefore a therapeutic target to consider.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".