Thermo-Responsive Poly(N-Isopropylacrylamide)-Cellulose Nanocrystals Hybrid Hydrogels for Wound Dressing
Bibliographic record
Abstract
-isopropylacrylamide) (PNIPAAm), reinforced both with covalent and non-covalent interactions with cellulose nanocrystals (CNC), were synthesized via free-radical polymerization in the absence of any additional cross-linkers. The properties of PNIPAAm-CNC hybrid hydrogels were dependent on the amounts of incorporated CNC. The thermal stability of the hydrogels decreased with increasing CNC content. The rheological measurement indicated that the elastic and viscous moduli of hydrogels increased with the higher amounts of CNC addition, representing stronger mechanical properties of the hydrogels. Moreover, the hydrogel injection also supported the hypothesis that CNC reinforced the hydrogels; the increased CNC content exhibited higher structural integrity upon injection. The PNIPAAm-CNC hybrid hydrogels exhibited clear thermo-responsive behavior; the volume phase transition temperature (VPTT) was in the range of 36 to 39 °C, which is close to normal human body temperature. For wound dressing purposes, metronidazole, an antibiotic and antiprotozoal often used for skin infections, was used as a target drug to study drug-loading and the release properties of the hydrogels. The hydrogels showed a good drug-loading capacity at room temperature and a burst drug release, which was followed by slow and sustained release at 37 °C. These results suggested that newly developed drugs containing injectable hydrogels are promising materials for wound dressing.
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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 | 0.000 |
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".