Functionalization of PCL-Based Fiber Scaffolds with Different Sources of Calcium and Phosphate and Odontogenic Potential on Human Dental Pulp Cells
Bibliographic record
Abstract
This study investigated the incorporation of sources of calcium, phosphate, or both into electrospun scaffolds and evaluated their bioactivity on human dental pulp cells (HDPCs). Additionally, scaffolds incorporated with calcium hydroxide (CH) were characterized for degradation, calcium release, and odontogenic differentiation by HDPCs. Polycaprolactone (PCL) was electrospun with or without 0.5% w/v of calcium hydroxide (PCL + CH), nano-hydroxyapatite (PCL + nHA), or β-glycerophosphate (PCL + βGP). SEM/EDS analysis confirmed fibrillar morphology and particle incorporation. HDPCs were cultured on the scaffolds to assess cell viability, adhesion, spreading, and mineralized matrix formation. PCL + CH was also evaluated for gene expression of odontogenic markers (RT-qPCR). Data were submitted to ANOVA and Student’s t-test (α = 5%). Added CH increased fiber diameter and interfibrillar spacing, whereas βGP decreased both. PCL + CH and PCL + nHA improved HDPC viability, adhesion, and proliferation. Mineralization was increased eightfold with PCL + CH. Scaffolds containing CH gradually degraded over six months, with calcium release within the first 140 days. CH incorporation upregulated DSPP and DMP1 expression after 7 and 14 days. In conclusion, CH- and nHA-laden PCL fiber scaffolds were cytocompatible and promoted HDPC adhesion, proliferation, and mineralized matrix deposition. PCL + CH scaffolds exhibit a slow degradation profile, providing sustained calcium release and stimulating HDPCs to upregulate odontogenesis marker genes.
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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".