Cationic Cellulose and Chitin Nanocrystals for Novel Therapeutic Applications
Bibliographic record
Abstract
Polysaccharides are a class of biopolymers that have gained popularity in various fields due to their abundance, non-toxicity, biocompatibility and biodegradability. Recently, the applications of polysaccharide nanocrystals have been explored in different areas due to their high mechanical strength, surface functionality and low density. Nanocrystals of cellulose and chitin (the two most abundant biopolymers) have received increasing interest in recent years. Chitin nanocrystals naturally possess cationic groups, whereas cellulose nanocrystals require functionalization to impart a positive charge on their surface. These nanocrystals constitute an emerging group of renewable nanomaterials with improved properties. They contribute to the reduction of greenhouse gases and help rejuvenate the forestry and marine sectors. The use of these renewable materials in the design of biomedical systems will contribute to sustainable development solutions that have increasingly been given high priority by private and public organizations. In this chapter, the preparation, characterization and application of these nanocrystals in the biomedical field, such as nanocomposites, tissue engineering, wound healing, biosensors and delivery of therapeutics, are reviewed and discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".