Phase evolution in cholesterol/DPPC monolayers: atomic force microscopy and near field scanning optical microscopy studies
Bibliographic record
Abstract
A combination of atomic force microscopy (AFM) and near field scanning optical microscopy has been used to study domain formation in dipalmitoylphosphatidylcholine (DPPC)/cholesterol monolayers with cholesterol concentrations ranging from 0 to 50%. The results show a clear evolution from a mixture of liquid expanded and liquid condensed phases for cholesterol concentrations < 10% to a mixture of liquid expanded and two cholesterol-containing phases at intermediate concentrations, and finally to a single homogeneous liquid ordered phase for 33% cholesterol. Mixtures of the various phases are clearly identified by height differences in AFM and in some cases by fluorescence imaging for samples containing 0.5% BODIPY dye, which localizes preferentially in the more fluid phase. Note that fluorescence imaging, at least with the dye used here, is unable to distinguish between the cholesterol-rich and cholesterol-poor phases detected at intermediate cholesterol concentrations. The combination of fluorescence and AFM imaging provides a more complete picture of the phase evolution for cholesterol/DPPC monolayers than could be obtained by either technique alone, and presents substantial advantages over conventional fluorescence microscopy in that submicrometre-sized domains can be readily detected.
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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 | 0.001 | 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 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".