Double-Chamber Rotating Bioreactor for Dynamic Perfusion Cell Seeding of Large-Segment Tracheal Allografts: Comparison to Conventional Static Methods
Bibliographic record
Abstract
Tracheal transplantation with a long-segment recellularized tracheal allograft has previously been performed without the need for immunosuppressive therapy. Recipients' mesenchymal stromal cells (MSC) and tracheal epithelial cells (TEC) were harvested, cultured, expanded, and seeded on a donor trachea within a bioreactor. Prior techniques used for cellular seeding have involved only static-seeding methods. Here, we describe a novel bioreactor for recellularization of long-segment tracheae. Tracheae were recellularized with epithelial cells on the luminal surface and bone marrow-derived MSC on the external surface. We used dynamic perfusion seeding for both cell types and demonstrate an increase in both cellular counts and homogeneity scores compared with traditional methods. Despite these improvements, orthotopic transplantation of these scaffolds revealed no labeled cells at postoperative day 3 and lack of re-epithelialization within the first 2 weeks. The animals in this study had postoperative respiratory distress and tracheal collapse that was incompatible with life.
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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) | 0.000 | 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".