Release and swelling studies of an innovative antidiabetic-bile acid microencapsulated formulation, as a novel targeted therapy for diabetes treatment
Bibliographic record
Abstract
In previous studies carried out in our laboratory, a bile acid formulation exerted a hypoglycaemic effect in a rat model of type 1 diabetes (T1D). When the antidiabetic drug gliclazide was added to the bile acid, it augmented the hypoglycaemic effect. In a recent study, we designed a new formulation of gliclazide-deoxycholic acid (G-DCA), with good structural properties, excipient compatibility and which exhibited pseudoplastic-thixotropic characteristics. The aim of this study is to test the slow release and pH controlled properties of this new formulation. The aim is also to examine the effect of DCA on G release kinetics at various pH values and different temperatures. Microencapsulation was carried out using our Buchi-based microencapsulating system developed in our laboratory. Using sodium alginate (SA) polymer, both formulations were prepared including: G-SA (control) and G-DCA-SA (test) at a constant ratio (1:3:30), respectively. Microcapsules were examined for efficiency, size, release kinetics, stability and swelling studies at pH 1.5, 3, 7.4 and 7.8 and temperatures of 25 °C and 37 °C. The new formulation is further optimised by the addition of DCA. DCA reduced bead-swelling of the microcapsules at pH 7.8 and 3 at 25 °C and 37 °C, and even though bead size remains similar after DCA addition, the percentage of G release was enhanced at high pH values (pH 7.4 and 7.8, p < 0.01). The new formulation exhibits colon-targeted delivery and the addition of DCA prolonged G release suggesting its suitability for the sustained and targeted delivery of G and DCA to the lower intestine.
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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".