Biomechanical study of cellulose scaffolds for bone tissue engineering <i>in vivo</i> and <i>in vitro</i>
Bibliographic record
Abstract
ABSTRACT Plant-derived cellulose biomaterials have recently been utilized in several tissue engineering applications. These naturally-derived cellulose scaffolds have been shown to be highly biocompatible in vivo , possess structural features of relevance to several tissues, and support mammalian cell invasion and proliferation. Recent work utilizing decellularized apple hypanthium tissue has shown that it possesses a pore size similar to trabecular bone and can successfully host osteogenic differentiation. In the present study, we further examined the potential of apple-derived cellulose scaffolds for bone tissue engineering (BTE) and analyzed their mechanical properties in vitro and in vivo . MC3T3-E1 pre-osteoblasts were seeded in cellulose scaffolds. Following chemically-induced osteogenic differentiation, scaffolds were evaluated for mineralization and for their mechanical properties. Alkaline phosphatase and Alizarin Red staining confirmed the osteogenic potential of the scaffolds. Histological analysis of the constructs revealed cell invasion and mineralization throughout the constructs. Furthermore, scanning electron microscopy demonstrated the presence of mineral aggregates on the scaffolds after culture in differentiation medium, and energy-dispersive spectroscopy confirmed the presence of phosphate and calcium. However, although the Young’s modulus significantly increased after cell differentiation, it remained lower than that of healthy bone tissue. Interestingly, mechanical assessment of acellular scaffolds implanted in rat calvaria defects for 8 weeks revealed that the force required to push out the scaffolds from the surrounding bone was similar to that of native calvarial bone. In addition, cell infiltration and extracellular matrix deposition were visible within the implanted scaffolds. Overall, our results confirm that plant-derived cellulose is a promising candidate for BTE applications. However, the discrepancy in mechanical properties between the mineralized scaffolds and healthy bone tissue may limit their use to low load-bearing applications. Further structural re-engineering and optimization to improve the mechanical properties may be required for load-bearing applications.
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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 | 0.001 | 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".