PLLA Membranes Enriched with Chitosan/DCPA: Innovative Approach to Bone Tissue Engineering
Bibliographic record
Abstract
Background: Bone tissue engineering has been very promising.The use of scaffolds of synthetic and natural materials is an alternative to combine the advantages of both types of materials.This study aimed to evaluate electrospun polymeric matrices of pure PLLA or associated with 5% or 10% of chitosan particles loaded or not with DCPA in bone proliferation and differentiation of periodontal ligament stem cells (PDLSC).The particles and matrices were characterized by scanning electron microscopy.PDLSC were isolated from periodontal ligament fragments of human permanent teeth using the explant technique.Cell proliferation assay (Alamar Blue) was performed from 1 to 21 days of culture in clonogenic medium and Alizarin Red assay was performed after 21 days of culture in osteogenic medium.The data were analyzed using Kruskal-Wallis test, and the comparison between media was given by the Student-Newman-Keuls test ( = 0.05).On days 1 and 7 there were no statistical difference between materials regarding cell proliferation (p>0.05).The materials with 5 and 10% chitosan / DCPA showed greater proliferation than PLLA control on days 14 and 21 and the material with 10% pure chitosan was greater than the control in 21 days.Regarding the alizarin red assay, PLLA 5% chitosan, PLLA 5 and 10% chitosan / DCPA showed a greater degree of mineralization than the control and the PLLA 10% chitosan material, and they were similar to each other.We conclude that PLLA 5 and 10% chitosan / DCPA materials were able to increase both, cell proliferation and differentiation of PDLSC in bone cells.
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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".