Chitosan-Based Trilayer Scaffold for Multitissue Periodontal Regeneration
Bibliographic record
Abstract
Periodontal regeneration is still a challenge for periodontists and tissue engineers, as it requires the simultaneous restoration of different tissues—namely, cementum, gingiva, bone, and periodontal ligament (PDL). Here, we synthetized a chitosan (CH)–based trilayer porous scaffold to achieve periodontal regeneration driven by multitissue simultaneous healing. We produced 2 porous compartments for bone and gingiva regeneration by cross-linking with genipin either medium molecular weight (MMW) or low molecular weight (LMW) CH and freeze-drying the resulting scaffolds. We synthetized a third compartment for PDL regeneration by CH electrochemical deposition; this allowed us to produce highly oriented microchannels of about 450-µm diameter intended to drive PDL fiber growth toward the dental root. In vitro characterization showed rapid equilibrium water content for MMW-CH and LMW-CH compartments (equilibrium water content after 5 min >85%). The MMW-CH compartment degraded more slowly and provided significantly more resistance to compression (28% ± 1% of weight loss at 4 wk; compression modulus H A = 18 ± 6 kPa) than the LMW-CH compartment (34% ± 1%; 7.7 ± 0.8 kPa) as required to match the physiologic healing rates of bone and gingiva and their mechanical properties. More than 90% of all human primary periodontal cell populations tested on the corresponding compartment survived during cytocompatibility tests, showing active cell metabolism in the alkaline phosphatase and collagen deposition assays. In vivo tests showed high biocompatibility in wild-type mice, tissue ingrowth, and vascularization within the scaffold. Using the periodontal ectopic model in nude mice, we preseeded scaffold compartments with human gingival fibroblasts, osteoblasts, and PDL fibroblasts and found a dense mineralized matrix within the MMW-CH region, with weakly mineralized deposits at the dentin interface. Together, these results support this resorbable trilayer scaffold as a promising candidate for periodontal regeneration.
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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".