STM Studies of Fusion of Cholesterol Suspensions and Mixed 1,2-Dimyristoyl-<i>sn</i>-glycero-3-phosphocholine (DMPC)/Cholesterol Vesicles onto a Au(111) Electrode Surface
Bibliographic record
Abstract
Electrochemical scanning tunneling microscopy (EC-STM) has been applied to study the structure of the film formed by fusion of cholesterol suspensions and mixed dimyristoylphosphatidylcholine (DMPC)/cholesterol vesicles on a Au(111) electrode surface. It has been demonstrated that cholesterol molecules assemble at the gold support into several structures templated by the crystallography of the metal surface and involving flat or edge-on adsorbed molecules. Studies of the film formed by fusion of mixed DMPC/cholesterol vesicles revealed that ordered domains of either pure DMPC or pure cholesterol were formed. These results indicate that, at the metal surface, the molecules released by the rupture of a vesicle initially self-assemble into a well-ordered monolayer. The self-assembly is controlled by the hydrocarbon skeleton-metal surface interaction. In the case of mixed DMPC/cholesterol vesicles, the molecule-metal interactions induce segregation of the two components into single component domains. However, the molecule-metal interaction induced monolayer is a transient phenomenon. When more molecules accumulate at the surface, the molecule-molecule interactions dominate the assembly, and the monolayer is transformed into a bilayer.
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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) | 0.001 | 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".