Carboxymethyl-Starch Excipients for Gastrointestinal Stable Oral Protein Formulations Containing Protease Inhibitors
Bibliographic record
Abstract
PURPOSE: The aim of this study was to develop a formulation for bioactive compounds using Carboxymethyl Starch (CMS) as excipient containing protease inhibitors. This formulation provided gastro protection and enhanced stability against pancreatic enzymes. Such stability is needed for formulation of oral vaccines with specific antigens. METHODS: CMS was synthesized by treatment of starch with monochloroacetic acid in conditions leading to a substitution degree of about 1 meq/g and used as excipient for monolithic devices (300 mg tablets). Pefabloc SC and Aprotinin inhibitors were tested in dissolution media and in formulation to prevent the degradation of released bioactive materials. To evaluate the structural integrity and biological stability of plant proteins in the CMS formulation, albumin and lipase were added to the plant protein extract as protein and respectively as enzyme markers. The amounts of released and recovered proteins were evaluated by SDS-PAGE and densitometric analysis. RESULTS: It was found that 1.6 % (w/w) of Pefabloc SC provides 98 % protection of the released plant proteins for formulations of 30 % alfalfa protein extract (APE) with CMS. In addition, when bovine serum albumin (BSA) added to the plant protein extract as a marker, 90 % protection of the released BSA was observed. Furthermore, a much higher lipase activity was found in the releasing media when the formulations contained Pefabloc SC. CONCLUSION: Formulations with CM-Starch excipients and containing protease inhibitors prevent protein degradation and protect lipase activity, showing a marked potential to use for orally administered bioactive peptides and therapeutic enzymes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".