Pore size and LbL chitosan coating influence mesenchymal stem cell<i>in vitro</i>fibrosis and biomineralization in 3D porous poly(epsilon-caprolactone) scaffolds
Bibliographic record
Abstract
Poly(epsilon-caprolactone) (PCL) is a hydrophobic bioplastic under development for bone tissue engineering applications. Limited information is available on the role of internal geometry and cell-surface attachment on osseous integration potential. We tested the hypothesis that human bone marrow mesenchymal stem cells (MSCs) deposit more mineral inside porous 3D PCL scaffolds with fully interconnected 84 or 141 µm pores, when the surfaces are coated with chitosan via Layer-by-Layer (LbL)-deposited polyelectrolytes. Freshly trypsinized MSCs were seeded on PCL 3D cylinders using a novel static cold seeding method in 2% serum to optimally populate all depths of the scaffold discs, followed by 10 days of culture in proliferation medium and 21 additional days in osteogenic medium. MSCs were observed by SEM and histology to spread faster and to proliferate more on chitosan-coated pore surfaces. Most pores, with or without chitosan, became filled by collagen networks sparsely populated with fibroblast-like cells. After 21 days of culture in osteogenic medium, sporadic matrix mineralization was detected histologically and by micro-CT in highly cellular surface layers that enveloped all scaffolds and in cell aggregates in 141 µm pores near the edges. LbL-chitosan promoted punctate mineral deposition on the surfaces of 84 µm pores (p < 0.05 vs. PCL-only) but not the 141 µm pores. This study revealed that LbL-chitosan coatings are sufficient to promote MSC attachment to PCL but only enhance mineral formation in 84 µm pores, suggesting a potential inhibitory role for MSC-derived fibroblasts in osteoblast terminal differentiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".