Sourcing Interchangeability in Commercial Chitosan: Focus on the Physical–Chemical Properties of Six Different Products and Their Impact on the Release of Antibacterial Agents
Bibliographic record
Abstract
Sourcing and batch differences are often cited as intrinsic drawbacks for all natural polymers. Chitosan makes no exception. Chitosan is a biocompatible and biodegradable biopolymer with high potential for several biomedical applications, especially for releasing drugs and bactericidal and virucidal agents. Despite the potential of chitosan as a matrix for producing antibacterial films, the variability in its composition, stemming from its natural sources, can hinder the translation from bench to industry. To overcome this concern, we conducted a study to access the interchangeability of chitosan for the development of antibacterial drug release systems, in particular one system crosslinked with tannic acid and iron sulfate. Chitosans from different suppliers were characterized and used to synthetize films containing gentamicin, according to a previously reported protocol. The impact of molecular weight (MW), deacetylation degree and purity on film properties and antibiotic release kinetics was assessed and results were compared. The films exhibited different initial bursts followed by similar sustained release profiles. All films exhibited antibacterial activity against both E. coli and S. aureus for at least 42 days. Moreover, films were cyto- and hemocompatible. Therefore, despite some differences in physicochemical properties, the interchangeability among the studied chitosan suppliers to produce antibacterial films is feasible, and the final product properties and performances are not significantly altered.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".