A comparison between electrokinetic capillary chromatography and absorption spectroscopy for the analysis of peptide‐micelle association by weak hydrophobic interactions
Bibliographic record
Abstract
Micellar electrokinetic capillary chromatography (MEKC) was compared to absorption spectroscopy to estimate equilibrium association constans (K(as)) for peptide-micelle systems involving three peptides (leucine-enkephalin, methionine-enkephalin and leucine-phenylalanine (LF)) and two surfactant micelles (sodium dodecyl sulfate (SDS) and cetyltrimethylammonium bromide (CTAB)). Buffer pH was chosen to minimize purely electrostatic interactions between peptides and micelles that could not be interrogated by absorption spectroscopy. Viscosity-corrected MEKC mobilities gave reasonably similar estimates of K(as) between the two methods for all three peptide-SDS micelle systems, with K(as) values ranging from 13.7 +/- 0.3 to 49 +/- 1 M(-1). For CTAB, estimates of K(as) for LF-CTAB micelle association were of the same order of magnitude as the SDS micelle by the two methods of estimation. On the other hand, enkephalin-CTAB micelle binding was about 10 times stronger (K(as) = 122 +/- 3 M(-1) to 311 +/- 9 M(-1)) than the enkephalin-SDS micelle binding. In addition, MEKC underestimated the K(as) values relative to spectroscopy by a factor of 2-3 for the enkephalin-CTAB system.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".