Novel chitosan-coralline composite biomatrices for bone tissue engineering applications : microarchitectural features and in vitro mesenchymal stem cell responses
Bibliographic record
Abstract
The purpose of this work was to develop novel 3D coralline-chitosan macroporous composite scaffolds for in vitro bone tissue engineering and investigate cellular responses to these scaffolds. In these composites, coral skeletal material, which is made of calcium carbonate (CaCO3), was simultaneously used as particulate reinforcing phase and gas-forming agent to obtain a structure with large pores and improved mechanical and biological properties. The reaction between the coralline material and the acidic chitosan polymer solvent, which produces carbon dioxide (CO2), was rapidly stopped by the subsequent thermally induced phase separation step, leaving coral particulates in the polymeric structure. Scaffolds containing 5 different proportions of coralline material (0, 25, 50, 75, and 100 wt%) were developed and studied under two different aspects. In a first part, the coralline:chitosan weight ratio parameter was studied for its effects on the physical properties of the scaffolds with a combination of scanning electron microscope (SEM), micro-CT imaging, and compression testing. In a second part, the scaffolds were cultured with mice MSCs. Cellular morphology, DNA content, as well as expression of osteogenic markers alkaline phosphatase (ALP) activity and osteocalcin release were evaluated. The effect of cell culture medium supplementation with beta-glycerophosphate and dexamethasone was studied. The results showed that higher coralline concentration increased the pore wall thickness and favoured large pore formation. Varying the coralline powder to chitosan polymer ratio from 0 to 75 wt% increased the observed pore sizes from 80 microm to 400 microm in average and decreased the porosity from 91% to 78%. The equilibrium compressive modulus was improved proportionally with the coral content, and the 75 wt% composites had a significantly higher modulus than all the other chitosan-based scaffolds. The coralline scaffolds showed by far the highest evaluation of cell number and ALP activity over all the other chitosan-based scaffolds. They were the only materials on which the osteocalcin protein was release throughout the study and generally at a high level. Nevertheless, the coralline:chitosan composite scaffolds containing high coralline ratios generally showed higher results than the pure chitosan scaffolds. Of all the chitosan-based scaffolds, the cells cultured on the 75:25 coralline:chitosan scaffolds obtained the highest peak of ALP activity and generally obtained the highest cell number. While the presence of osteogenic supplements had no obvious effect on cell behaviour and osteogenic differentiation, distinct cell morphology and osteoblastic phenotype expression were observed depending on the coralline to chitosan ratios composing the scaffolds. The results strongly suggest that coralline:chitosan composites, especially those having a high coralline content, may enhance adhesion proliferation and osteogenic differentiation of MSCs in comparison with pure chitosan. In conclusion, composite scaffolds with improved mechanical and biological properties concomitant with large pores were achieved by increasing the coralline:chitosan weight ratio. These composites possess therefore many advantages over coralline and chitosan scaffolds, suggesting that they have an excellent potential as biomatrices for tissue engineering.
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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".