Cholesterol in Bilayers with PUFA Chains: Doping with DMPC or POPC Results in Sterol Reorientation and Membrane-Domain Formation
Bibliographic record
Abstract
Using neutron diffraction Harroun et al. [(2006) Biochemistry 45, 1227-1233; (2008) Biochemistry 47, 7090-7096] carried out studies that unequivocally demonstrated cholesterol preferentially sequestering in the middle of bilayers (i.e., flat orientation) made of lipids with polyunsaturated fatty acids (PUFA), in contrast to its "usual" position where its hydroxyl group locates near the lipid/water interface (i.e., upright orientation). Here we clearly show, using neutron diffraction, cholesterol's orientational preference in different lipid bilayers. For example, although it requires 50 mol % POPC (16:0-18:1 PC) in DAPC (di20:4 PC) bilayers to cause cholesterol to revert to its upright orientation, only 5 mol % DMPC (di14:0 PC) is needed to achieve the same effect. This result demonstrates not only cholesterol's affinity for saturated hydrocarbon chains, but also its aversion for PUFAs. Molecular dynamics (MD) simulations performed on similar systems show that in high PUFA content bilayers cholesterol is simultaneously capable of assuming different orientations within a bilayer. Although this result is known from previous MD studies by Marrink et al. [(2008) J. Am. Chem. Soc. 130, 10-11], it has yet to be confirmed experimentally. Importantly, MD simulations predict the formation of DMPC-rich domains, data corroborated by experiment (i.e., 10 mol % DMPC-doped DAPC bilayers), where cholesterol preferentially locates in its upright orientation, while in DMPC-depleted domains cholesterol is found mostly in the bilayer center (i.e., flat orientation). These results lend credence to DMPC's aversion for PUFAs, supporting the notion that domain formation is primarily driven by lipids.
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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".