Enthalpy of Interaction and Binding Isotherms of Non-ionic Surfactants onto Micellar Amphiphilic Polymers (Amphipols)
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Bibliographic record
Abstract
The interactions in water between short amphiphilic macromomolecules, known as amphipols, and three neutral surfactants (detergents), dodecylmaltoside (DM), n-octylthioglucoside (OTG), and n-octyltetraethyleneoxide (C8E4), have been assessed by static and dynamic light-scattering (SLS and DLS), capillary electrophoresis (CE), and isothermal titration calorimetry (ITC). The amphipols selected are random copolymers of the hydrophobic n-octylacrylamide (25-30 mol %), a charged hydrophilic monomer, either acrylic acid ( approximately 35 mol %) or a phosphorylcholine-modified acrylamide (40-70 mol %), and, optionally, N-isopropylacrylamide (30-40 mol %). In water, the copolymers form micelles of small size (hydrodynamic radius: approximately 5 nm). Neutral surfactants, below their critical micellar concentration (cmc), form mixed micelles with the amphipols irrespective of the chemical structure of the detergent or the polymer. The fraction of detergent in the surfactant/polymer complexes increases significantly (cooperatively) as the surfactant concentration nears the cmc. The ITC data, together with data gathered by CE, were fitted via a regular mixing model, which allowed us to predict the detergent concentration in equilibrium with complexes and the heat evolved upon transfer of detergent from water into a mixed surfactant/polymer complex. The enthalpy of transfer was found to be almost equal to the enthalpy of micellization, and the regular mixing model points to a near-ideal mixing behavior for all systems. Amphipols are promising tools in biochemistry where they are used, together with neutral surfactants, for the stabilization and handling of proteins. This study provides guidelines for the optimization of current protein purification protocols and for the formulations of surfactant/polymer systems used in pharmaceutics, cosmetics, and foodstuffs.
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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) | 0.001 | 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 it