Glucose‐induced self‐assembly in structurally diverse polyoxyethylene based nonionic surfactants for enhanced anticancer drug solubilization
Bibliographic record
Abstract
Abstract This study investigates the influence of glucose in inducing the micellar growth/transition in several structurally diverse, longer, and shorter chain polyoxyethylene (POE)‐based nonionic surfactants, commercially known as Kolliphor® HS15 (Solutol), Kolliphor EL®, Akypo®, Brij®‐78, Pluronic® (P103 and F77), Tetronic® (T1304), and Tyloxapol® in aqueous solution environment. It was observed that the addition of glucose induces dehydration of the POE moieties or chains in the tested systems, thereby enhancing the inter‐micellar interactions via hydrogen bonding in the hydrophilic part of the selected surfactants. This dehydration leads to an interesting clouding behavior across all the studied surfactant systems. Also, the dynamic light scattering (DLS) technique accounted for the probable self‐assembly and micellar growth in water and 1 M glucose (fix) across various temperatures. Being pharmaceutical excipients, these micellar entities were successfully employed to assay the hydrophobic anticancer drug curcumin (Cur) solubilized, as confirmed by the peak intensity variation from UV–visible spectroscopy. Cur solubilization into glucose‐containing micelles revealed enhanced solubility expressed in terms of drug loading efficiency (DL%), encapsulation efficiency (EE%), partition coefficient (log P), and standard free energy of solubilization (ΔG°), which is due to the glucose‐induced hydrophobicity in the examined nonionic micellar systems.
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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 | 0.000 | 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 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".