<i>In Vivo</i>Remodeling of Fibroblast-Derived Vascular Scaffolds Implanted for 6 Months in Rats
Bibliographic record
Abstract
There is a clinical need for tissue-engineered small-diameter (<6 mm) vascular grafts since clinical applications are halted by the limited suitability of autologous or synthetic grafts. This study uses the self-assembly approach to produce a fibroblast-derived decellularized vascular scaffold (FDVS) that can be available off-the-shelf. Briefly, extracellular matrix scaffolds were produced using human dermal fibroblasts sheets rolled around a mandrel, maintained in culture to allow for the formation of cohesive and three-dimensional tubular constructs, and decellularized by immersion in deionized water. The FDVSs were implanted as an aortic interpositional graft in six Sprague-Dawley rats for 6 months. Five out of the six implants were still patent 6 months after the surgery. Histological analysis showed the infiltration of cells on both abluminal and luminal sides, and immunofluorescence analysis suggested the formation of neomedia comprised of smooth muscle cells and lined underneath with an endothelium. Furthermore, to verify the feasibility of producing tissue-engineered blood vessels of clinically relevant length and diameter, scaffolds with a 4.6 mm inner diameter and 17 cm in length were fabricated with success and stored for an extended period of time, while maintaining suitable properties following the storage period. This novel demonstration of the potential of the FDVS could accelerate the clinical availability of tissue-engineered blood vessels and warrants further preclinical studies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".