Magnetically Oriented Bicelles with Monoalkylphosphocholines: Versatile Membrane Mimetics for Nuclear Magnetic Resonance Applications
Bibliographic record
Abstract
Bicelles (bilayered micelles) are model membranes used in the study of peptide structure and membrane interactions. They are traditionally made of long- and short-chain phospholipids, usually dimyristoylphosphatidylcholine (D14PC) and dihexanoyl-PC (D6PC). They are attractive membrane mimetics because their composition and planar surface are similar to the native membrane environment. In this work, to improve the solubilization of membrane proteins and allow their study in bicellar systems, D6PC was replaced by detergents from the monoalkylphosphocholine (MAPCHO) family, of which dodecylphosphocholine (12PC) is known for its ability to solubilize membrane proteins. More specifically 12PC, tetradecyl- (14PC), and hexadecyl-PC (16PC) have been employed. To verify the possibility of making bicelles with different hydrophobic thicknesses to better accommodate membrane proteins, D14PC was also replaced by phospholipids with different alkyl chain lengths: dilauroyl-PC (D12PC), dipalmitoyl-PC (D16PC), distearoyl-PC (D18PC), and diarachidoyl-PC (D20PC). Results obtained by 31 P solid-state nuclear magnetic resonance (NMR) and isothermal titration calorimetry (ITC) at several lipid-to-detergent molar ratios ( q ) and temperatures indicate that these new MAPCHO bicelles can be formed under a variety of conditions. The quality of their alignment is similar to that of classical bicelles, and the low critical micelle concentration (CMC) of the surfactants and their miscibility with phospholipids are likely to be advantageous for the reconstitution of membrane proteins.
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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".