Milk Sphingomyelin Domains in Biomimetic Membranes and the Role of Cholesterol: Morphology and Nanomechanical Properties Investigated Using AFM and Force Spectroscopy
Bibliographic record
Abstract
Milk sphingomyelin (MSM) and cholesterol segregate into domains in the outer bilayer membrane surrounding milk fat globules. To elucidate the morphology and mechanical properties of theses domains, supported lipid bilayers with controlled molar proportions of MSM, dioleoylphosphatidylcholine (DOPC) and cholesterol were produced in buffer mimicking conditions of the milk aqueous phase. Atomic force microscopy imaging showed that (i) for T < 35 °C MSM segregated in gel phase domains protruding above the fluid phase, (ii) the addition of 20 mol % cholesterol resulted in smaller and more elongated l(o) phase domains than in equimolar MSM/DOPC membranes, (iii) the MSM/cholesterol-enriched l(o) phase domains were less salient than the MSM gel phase domains. Force spectroscopy measurements furthermore showed that cholesterol reduced the resistance of MSM/DOPC membrane to perforation. The results are discussed with respect to the effect of cholesterol on the biophysical properties of lipid membranes. The combination of AFM imaging and force mapping provides unprecedented insight into the structural and mechanical properties of milk lipid membranes, and opens perspectives for investigation of the functional properties of MSM domains during milk fat processing or digestion.
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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 | 0.000 |
| 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".