Development and Characterization of Functional Polylactic Acid/Chitosan Porous Scaffolds for Bone Tissue Engineering
Bibliographic record
Abstract
In this study, we developed and characterized various open-cell composite scaffolds for bone regeneration. These scaffolds were made from Polylactic acid (PLA) as the scaffold matrix biopolymeric phase, and chitosan (CS) and chitosan-grafted-PLA (CS-g-PLA) copolymer as the dispersed biopolymeric phase. As a first step, successful grafting of PLA onto CS backbone was executed and confirmed by both FTIR and XPS. Mechanical characterization confirmed that adding CS or CS-g-PLA to the intrinsically rigid PLA made their corresponding PLA/CS and PLA/CS-g-PLA composite scaffolds more flexible under compression. This flexibility was higher for the latter due to the improved compatibility between PLA and CS-g-PLA copolymer. The hydrolytic stability of both PLA/CS and PLA/CS-g-PLA composite scaffolds inside phosphate-buffered saline (PBS) solution, as well as MG-63 osteoblast cell adhesion and proliferation inside both scaffolds, were characterized. The corresponding results revealed that PLA/CS composite scaffolds showed hydrolytic degradation due to the cationic properties of CS. However, modified PLA/CS-g-PLA scaffolds were hydrolytically stable due to the improved interfacial adhesion between the PLA matrix and CS-g-PLA copolymer. Finally, biological characterization was done for both PLA/CS and PLA/CS-g-PLA composite scaffolds. Contrarily to what was observed for uncompatibilized PLA/CS scaffolds, compatibilized PLA/CS-g-PLA scaffolds showed a high MG-63 osteoblast cell proliferation after three and five days of cell culture. Moreover, it was observed that cell proliferation increased with CS-g-PLA content. This suggests that the PLA/CS-g-PLA composite scaffolds could be a potential solution for bone regeneration.
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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 | 0.000 | 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 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".