pH-Responsive self-assembly of cationic surfactants with a star-shaped tetra-carboxylate acid and the solubilization of hydrophobic drugs
Bibliographic record
Abstract
This work involved the construction of pH-responsive self-assembly systems from a pH-sensitive four-arm carboxylate acid (4EOCOOH) and either the cationic single chain surfactant dodecyl trimethyl ammonium bromide (DTAB) or the cationic gemini surfactant hexamethylene-1,6-bis(dodecyldimethylammonium bromide) (12-6-12). It was found that the constructed oligomeric-like structures from the mixtures of 4EOCOOH with DTAB or 12-6-12 greatly enhance the aggregation ability of the mixtures, thus improving the pH-responsivity. In particular, surfactant concentrations significantly affect the pH-responsivity at a fixed 4EOCOOH concentration. At higher surfactant concentrations, the pH-responsivity is suppressed, while at lower surfactant concentrations, the mixed aggregates gradually change from micelles to unstable large spherical aggregates or vesicles, and then to stable spherical aggregates, with decreasing pH. Moreover, the surfactant/4EOCOOH systems have different solubilization abilities for three hydrophobic drugs. For quercetin and baicalein, the systems support much better solubilization at lower pH values, while for indomethacin, the systems show better solubilization at higher pH values. In particular, compared with DTAB, 12-6-12 is more efficient in constructing pH-responsive systems, and the 12-6-12/4EOCOOH mixture shows better ability for solubilizing hydrophobic drugs. This work will be helpful in the design of high-efficiency, pH-responsive surfactant systems for solubilizing hydrophobic drugs by simply mixing pH-sensitive molecules with surfactants.
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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".