Lipid Domain Morphologies in Phosphatidylcholine−Ceramide Monolayers
Bibliographic record
Abstract
In cells, one of the main roles of ceramide-enriched membrane domains is to recruit or exclude intracellular signaling molecules and receptors, thereby facilitating signal transduction cascades. Accordingly, in model membranes, even low contents of ceramide segregate into lateral domains. The impact of the N-acyl chain on this segregation and on the morphology of the domains remains to be explored. Using Langmuir monolayers, we have systematically studied binary mixtures of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and ceramide (2:1, molar ratio) and varied the N-acyl chain length of ceramide from 2 to 24 carbon atoms (Cer2 to Cer24). Fluid Cer2, Cer6, and Cer8/DMPC mixtures were miscible at all surface pressures. Longer ceramides, however, formed surface pressure-dependent immiscible mixtures with DMPC. The domain morphology under fluorescence microscopy after including a trace amount of fluorescent NBD-phosphatidylcholine into DMPC/Cer mixtures was found to be very sensitive to the N-acyl chain length. Shorter ceramides (Cer10-Cer14) formed flower-like (seaweed) domains, whereas longer ceramides (N-acyl chain length>14 carbon atoms) formed round and regular domains. We attribute the formation of the flower patterns to diffusive morphological instabilities during domain growth.
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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) | 0.001 | 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".