Polyelectrolyte Biomaterial Interactions Provide Nanoparticulate Carrier for Oral Insulin Delivery
Bibliographic record
Abstract
Nanospheres are being developed for the oral delivery of peptide-based drugs such as insulin. Mucoadhesive, biodegradable, biocompatible, and acid-protective biomaterials are described using a combination of natural polyelectrolytes, with particles formulated through nanoemulsion dispersion followed by triggered in situ gel complexation. Biomaterials meeting these criteria include alginate, dextran, chitosan, and albumin in which alginate/dextran forms the core matrix complexed with chitosan and albumin coat. Smaller size and higher albumin-based acid-protective formulation was orally administered to diabetic rats and glucose reduction and physiological response analyzed. Insulin encapsulation efficiency was 90, 82, and 66% for uncoated, chitosan-coated, and albumin-chitosan-coated alginate nanospheres, respectively. The choice of coating polymer seems to influence insulin release profile and to be crucial to prevent peptic digestion. Physiological response following oral delivery showed that insulin albumin-chitosan-coated alginate nanospheres reduced glycemia approximately 72% of basal values. Albumin serves as an important enteric coating providing acid- and protease protection enabling uptake of active drug following oral dosage.
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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) | 0.001 | 0.001 |
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".