JoVE Video Dataset
Bibliographic record
Abstract
Plant-derived cellulose biomaterials have been employed in various tissue engineering applications. In vivo studies have shown the remarkable biocompatibility of scaffolds made of cellulose derived from natural sources. Additionally, these scaffolds possess structural characteristics that are relevant for multiple tissues, and they promote the invasion and proliferation of mammalian cells. Recent research using decellularized apple hypanthium tissue has demonstrated the similarity of its pore size to that of trabecular bone as well as its ability to effectively support osteogenic differentiation. The present study further examined the potential of apple-derived cellulose scaffolds for bone tissue engineering (BTE) applications and evaluated their in vitro and in vivo mechanical properties. MC3T3-E1 preosteoblasts were seeded in apple-derived cellulose scaffolds that were then assessed for their osteogenic potential and mechanical properties. Alkaline phosphatase and alizarin red S staining confirmed osteogenic differentiation in scaffolds cultured in differentiation medium. Histological examination demonstrated widespread cell invasion and mineralization across the scaffolds. Scanning electron microscopy (SEM) revealed mineral aggregates on the surface of the scaffolds, and energy-dispersive spectroscopy (EDS) confirmed the presence of phosphate and calcium elements. However, despite a significant increase in the Young's modulus following cell differentiation, it remained lower than that of healthy bone tissue. In vivo studies showed cell infiltration and deposition of extracellular matrix within the decellularized apple-derived scaffolds after 8 weeks of implantation in rat calvaria. In addition, the force required to remove the scaffolds from the bone defect was similar to the previously reported fracture load of native calvarial bone. Overall, this study confirms that apple-derived cellulose is a promising candidate for BTE applications. However, the dissimilarity between its mechanical properties and those of healthy bone tissue may restrict its application to low load-bearing scenarios. Additional structural re-engineering and optimization may be necessary to enhance the mechanical properties of apple-derived cellulose scaffolds for load-bearing applications.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.801 | 0.508 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".