Dexamethasone and vitamin D loaded scaffolds for bone engineering
Bibliographic record
Abstract
Abstract Vitamin D and dexamethasone are known for their anti-inflammatory effects and have shown promise in promoting bone regeneration due to their role in mineralizing hard tissues. The aim of this study was to synthesize and characterize PLLA electrospun membranes that incorporate both vitamin D and dexamethasone and evaluate their potential for in vitro bone conduction and differentiation. PLLA membranes were synthesized, associating 5% dexamethasone and vitamin D in the ratios 1:1; 1:2; and 2:1, along with a drug-free control group. The membranes were characterized by scanning electron microscopy (SEM). The biological aspects of the scaffold were assessed using human cells from the periodontal ligament (hPDLSC). Cell proliferations were evaluated by Alamar Blue assay on days 1, 7, and 14 of culture. Cell differentiation in scaffolds was assessed by alizarin red assay after 21 days. The results were analysed using to one-way ANOVA (fibber diameter and alizarin red assay) or Kruskal –Wallis test (proliferation assay). Scanning electron microscopy showed an increase in fibber diameter with the addition of drugs, with the membrane with a 2:1 ratio of vitamin D/dexamethasone having the greatest average diameter. There was no difference in the proliferation of hPDLSCs with materials at 1 and 14 days; PLLA membrane with 5% vitamin D/ dexamethasone at 1:1 showed the greatest mineralization of the extracellular matrix, indicating better bone differentiation of hPDLSCs. It can be concluded that among the synthesized membranes, the membrane with the same ratio between vitamin D and dexamethasone was the one with the best osteodifferentiation ability of hPDLSCs.
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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 | 0.001 | 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".