Atomic force microscopy and other scanning probe microscopy methods to study nanoscale domains in model lipid membranes
Bibliographic record
Abstract
ABSTRACTThe cell membrane is a fundamental biological structure, which is only 6–10 nm thick. It is composed of hundreds of lipid types, which form small and dynamic lipid domains or rafts. These rafts are thought to be a major aspect of cell organization, to provide support for various transmembrane proteins and are central to the communication of cells with their environs. Understanding the functions of lipid rafts presents an exciting opportunity to understand the molecular mechanisms of biologically important processes, as well as to uncover fundamental molecular mechanisms of membrane-associated diseases. Due to the high complexity of cell membranes, model membranes composed of synthetic lipids have been developed and are widely used to mimic biomembranes in an effort to study the structure and dynamics of lipid domains and their role in cell function. Atomic force microscopy (AFM), Kelvin probe force microscopy (KPFM) and atomic force spectroscopy (AFS) significantly advanced the study of nanodomains in model lipid membranes and monolayers. We review applications of these methods to the study of model membranes, which are widely used to mimic eukaryotic and bacterial cells, as well as neuronal cellular membranes in Alzheimer’s disease (AD).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".