Development and Characterization of a Novel Hybrid Tissue Engineering–Based Scaffold for Spinal Cord Injury Repair
Bibliographic record
Abstract
Spinal cord injury (SCI) represents a significant health and social problem, and therefore it is vital to develop novel strategies that can specifically target it. In this context, the objective of the present work was to develop a new range of three-dimensional (3D) tubular structures aimed at inducing the regeneration within SCI sites. Up to six different 3D tubular structures were initially developed by rapid prototyping: 3D bioplotting-based on a biodegradable blend of starch. These structures were then further complemented by injecting Gellan Gum, a polysaccharide-based hydrogel, in the central area of structures. The mechanical properties of these structures were assessed using dynamic mechanical analysis, under both dry and wet conditions, and their morphologies/porosities were analyzed using micro-computed tomography and scanning electron microscopy. Biological evaluation was carried out to determine their cytotoxicity, using both minimum essential medium (MEM) extraction and MTS tests, as well as by encapsulation of an oligodendrocyte-like cell (M03-13 cell line) within the hydrogel phase. The histomorphometric analysis showed a fully interconnected network of pores with porosity ranging from 70% to 85%. Scaffolds presented compressive modulus ranging from 17.4 to 62.0 MPa and 4.42 to 27.4 MPa under dry and wet conditions, respectively. Cytotoxicity assays revealed that the hybrid starch/poly-epsilon-caprolactone/Gellan Gum scaffolds were noncytotoxic, as they did not cause major alterations on cell morphology, proliferation, and metabolic viability. Moreover, preliminary cell encapsulation assays showed that the hybrid scaffolds could support the in vitro culture of oligodendrocyte-like cells. Finally, preliminary in vivo studies conducted in a hemisection rat SCI model revealed that the above-referred structures were well integrated within the injury and did not trigger chronic inflammatory processes. The results herein presented indicate that these 3D systems might be of use in future SCI regeneration approaches.
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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 | 0.001 | 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 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".