Interaction Mechanism of Different Surfactants with Casein: A Perspective on Bulk and Interfacial Phase Behavior
Bibliographic record
Abstract
Understanding the interaction mechanism between proteins and surfactants is conducive to the application of protein/surfactant mixtures in the food industry. The present study investigated the interaction mechanism of casein with cationic Gemini surfactant (BQAS), anionic Gemini surfactant (SGS), anionic single-chain surfactant (sodium dodecyl sulfate [SDS]), and two biosurfactants (rhamnolipid [RL] and lactone sophorolipid [SL]) at the interface and in bulk phase. BQAS/casein and SDS/casein mixtures exhibit a strong synergistic effect on the surface activity. For SGS, RL, and SL, the formation of surfactant/casein complexes caused no improvement in surface activity. Dilational elasticity results indicate the displacement of casein by SGS, RL, and SL at the surface. However, the BQAS/casein complexes manifested varying dilational properties from pure casein surface. The strong electrostatic interaction between BQAS and casein produced large-size precipitate particles. For other surfactants, no precipitate particles formed. Determination of ζ-potential, UV-vis absorption spectra, and fluorescence spectra demonstrated the stronger interaction of BQAS and SDS with casein than that of SGS, RL, and SL. Addition of BQAS initially increased and then decreased the α-helix structure of casein. For SGS, RL, and SL, no noticeable change occurred in the casein structure. However, the formation of SDS/casein complexes was conducive to the casein structure. In conclusion, the interaction between BQAS and casein is similar to that of cationic single-chain surfactant. Furthermore, SGS exhibits a significantly different interaction mechanism from the corresponding monomer (SDS), possibly resulting from its excellent interfacial activity, low critical micelle concentration values, and strong self-assembly capability. For RL and SL, the weak interaction is attributed to the relatively complicated structure and less charged degree of hydrophilic headgroups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".