Factors Affecting the Behavior and Effectiveness of Phospholipid Bilayer Coatings for Capillary Electrophoretic Separations of Basic Proteins
Bibliographic record
Abstract
Phospholipid bilayer coatings can prevent adsorption of cationic proteins on the surface of fused silica capillaries used in capillary electrophoresis. However, the performance of such bilayer coatings is strongly dependent on solution conditions. The factors affecting the rate of formation of phospholipid bilayer coatings were investigated using the double-chained zwitterionic 1,2-dimyristoyl-sn-glycero-phosphocholine (DMPC, C(14)) as a model phospholipid. The effectiveness of these coatings for CE separations of model cationic lysozyme, cytochrome c, ribonuclease A, and alpha-chymotrypsinogen A was also assessed. Increasing the ionic strength of a 0.1 mM DMPC solution reduced capillary coat times from >2 hours in 2.5 mM Tris (pH 7.4) buffer to 3.4 min in 40 mM Tris and dramatically improved separation performance such that > or =1.4 x 10(5) plates/m were observed in capillaries coated for 5 min with 0.1 mM DMPC in 20 mM Tris-HCl (pH 7.4). The presence of Ca(2+) in the coating solution also increases the rate of formation of the phospholipid bilayer coating. The type of vesicle strongly affects its adsorption rate onto the silica surface. The time required to coat the capillary was 7.2 min for small unilamellar vesicles (SUVs) and 22.5 min for large unilamellar vesicles and excessively long for multilamellar vesicles. Highest efficiency protein separations were achieved with bilayer coatings prepared from SUVs. The coating rate was enhanced by using greater DMPC concentrations and unaffected by pH. The type of buffer present in the DMPC coating solution affects the coating behavior, with HEPES buffer yielding a faster coat time than either Tris or phosphate buffers. Histone H1 was separated on a 0.1 mM DMPC-coated capillary.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".