Swelling, mechanical strength, and release properties of probucol microcapsules with and without a bile acid, and their potential oral delivery in diabetes
Bibliographic record
Abstract
We have demonstrated a permeation-enhancing effect of deoxycholic acid (DCA), the bile acid, in diabetic rats. In this study, we designed DCA-based microcapsules for the oral delivery of the antilipidemic drug probucol (PB), which has potential antidiabetic effects. We aimed to further characterize these microcapsules and examine their pH-dependent release properties, as well as the effects of DCA on their stability and mechanical strength at various pH and temperature values. Using the polymer sodium alginate (SA), we prepared PB-SA (control) and PB-DCA-SA (test) microcapsules. The microcapsules were examined for drug content, size, surface composition, release, Micro-CT cross-sectional imaging, stability, Zeta potential, mechanical strength, and swelling characteristics at different pH and temperature values. The microencapsulation efficiency and production yield were also examined. The addition of DCA resulted in microcapsules with a greater density and with reduced swelling at a pH of 7.8 and at temperatures of 25°C and 37°C (p < 0.01). The size, surface composition, production yield, and microencapsulation efficiency of the microcapsules remained similar after DCA addition. PB-SA microcapsules produced multiphasic PB release, while PB-DCA-SA microcapsules produced monophasic PB release, suggesting more controlled PB release in the presence of DCA. The PB-DCA-SA microcapsules showed good stability and a pH-sensitive uniphasic release pattern, which may suggest potential applications in the oral delivery of PB in diabetes.
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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".