Tendon Decellularized Matrix Modified Fibrous Scaffolds with Porous and Crimped Microstructure for Tendon Regeneration
Bibliographic record
Abstract
Current engineered synthetic scaffolds fail to functionally repair and regenerate ruptured native tendon tissues, partly because they cannot satisfy both the unique biological and biomechanical properties of these tissues. Ideal scaffolds for tendon repair and regeneration need to provide porous topographic structures and biological cues necessary for the efficient infiltration and tenogenic differentiation of embedded stem cells. To obtain crimped and porous scaffolds, highly aligned poly(l-lactide) fibers were prepared by electrospinning followed by postprocessing. Through a mild and controlled hydrogen gas foaming technique, we successfully transformed the crimped fibrous mats into three-dimensional porous scaffolds without sacrificing the crimped microstructure. Porcine derived decellularized tendon matrix was then grafted onto this porous scaffold through fiber surface modification and carbodiimide chemistry. These biofunctionalized, crimped, and porous scaffolds supported the proliferation, migration, and tenogenic induction of tendon derived stem/progenitor cells, while enabling adhesion to native tendons. Together, our data suggest that these biofunctionalized scaffolds can be exploited as promising engineered scaffolds for the treatment of acute tendon rupture.
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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) | 0.000 | 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".