Study of biodegradation behavior of chitosan-xanthan microspheres in simulated physiological media
Bibliographic record
Abstract
Microspheres of a polyelectrolyte complex hydrogel were prepared from chitosan and xanthan after interaction between the two polyionic polymers. Their biodegradation was studied vs. chitosan. Simulated gastric fluid (SGF, pH 1.2) and intestinal fluid (SIF, pH 7.5) both as biodegradation media and phosphate buffered saline (PBS, pH 7.4) as a negative control were used. The degradation studies were performed at 37 degrees C at 240 rpm permanent stirring to mimic the physiologic conditions. High performance liquid chromatography (HPLC) was carried out to quantify the chitosan degradation products using glucosamine (GA) and N-acetyl-D-glucosamine (N-Ac-GA) as references. The peaks area integration method was used to determine the amount of each degradation product as a function of incubation time in the media. The effect of the media on the morphological structure of microspheres was assessed by scanning electron microscopy. From HPLC studies, it appeared that in SGF and SIF the major degradation products were glucosamine (GA) and N-acetyl-D-glucosamine (NAc-GA). In the first 15 days, oligochitosan fractions were released from the complex, whereas N-acetyl-D-glucosamine was detected in the media after this period. The degradation kinetics were assessed by the measurement of the cumulative degradation products, which showed faster degradation of chitosan than the complex in SGF and SIF. SEM micrographs showed an enhancement of microsphere porosity as a function of incubation time in the simulated physiological media. Our results suggest a better control of the degradation kinetics when chitosan is complexed to xanthan.
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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".