Electrospun Poly(<scp>l</scp>-lactide-<i>co</i>-acryloyl carbonate) Fiber Scaffolds With a Mechanically Stable Crimp Structure For Ligament Tissue Engineering
Bibliographic record
Abstract
The aim of this study was to prepare a fibrous scaffold that possesses a crimped morphology using a photo-cross-linkable biodegradable copolymer. To obtain the crimped morphology, the polymer was first electrospun onto a rotating wire mandrel to obtain aligned straight fibers. Postprocessing by immersion in aqueous buffer at 37 °C generated a crimplike pattern in the fibers. It was reasoned that cross-linking the fibers following formation of the crimped structure would endow the scaffolds with a recoverable crimp pattern and mechanical properties similar to that of the collagen fibers in the anterior cruciate ligament (ACL). To achieve this aim, a trimethylene carbonate based monomer bearing an acrylate pendant group was synthesized and copolymerized with l-lactide. The copolymer was electrospun and photo-cross-linked yielding fibrous scaffolds possessing a substantial increase in tensile modulus and crimp stability compared to the uncross-linked fibrous scaffolds. The crimp-stabilized scaffolds also showed good cytocompatibility toward 3T3 fibroblasts, which attached and grew along the crimped fibers. These findings suggest that these cross-linked fiber scaffolds may be useful for the generation of cultured ligament tissue.
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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".