Dexamethasone-Functionalized PLLA Membranes: Effects of Layer-by-Layer Coating and Electrospinning on Osteogenesis
Bibliographic record
Abstract
The addition of dexamethasone in membranes for guided bone regeneration is promising due to its dual effect: (1) anti-inflammatory action and (2) induction of osteogenesis in host stem cells. Electrospun fiber coating with dexamethasone using the layer-by-layer (LBL) technique offers an interesting alternative for the gradual release of the drug, aiming for enhanced osteodifferentiation activity. This study aimed to develop synthetic poly-L-lactide (PLLA) membranes with dexamethasone incorporated into the fibers or coated on their surface, and to evaluate the drug release rate, as well as the material’s ability to promote proliferation, osteoconduction, and osteodifferentiation of human periodontal ligament stem cells (hPDLSCs). PLLA membranes were produced by electrospinning. Dexamethasone was incorporated using three techniques: (A) electrospinning of a co-solution of PLLA with 2.5 w/w% dexamethasone; (B) deposition of four layers on the PLLA membrane using alternating solutions of chitosan and heparin/dexamethasone; (C) deposition of 10 layers on the PLLA membrane using the same solutions. hPDLSC proliferation was measured via CCK-8 at 1, 7, 14, and 21 days. Cellular differentiation was assessed by alkaline phosphatase activity (7 days) and alizarin red staining (21 days) in clonogenic and osteogenic media (ODM). Data were analyzed using one or two-way ANOVA and Tukey test. Electrospun membranes with dexamethasone and those with 4 layers showed immediate drug release within 24 h, whereas 10 layers exhibited gradual release over 14 days. Cumulative drug release was higher for electrospun membranes at 1 and 7 days, similar to 10 layers at 14 and 21 days. The 4 LBL membrane promoted lower hPDLSC proliferation compared to the 10 LBL and electrospun membranes at 21 days but showed increased extracellular matrix mineralization in osteogenic media. No significant differences in alkaline phosphatase expression were observed between materials. Therefore, the addition of dexamethasone in 10 layers, combined with heparin, enables gradual drug release. However, lower drug release in the first 24 h by four LBL membranes improved the material’s osteogenesis properties. None of the materials improved the osteodifferentiation in the clonogenic medium.
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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".