Functional vascularized lung grafts for lung bioengineering
Bibliographic record
Abstract
End-stage lung disease is the third leading cause of death worldwide, accounting for 400,000 deaths per year in the United States alone. To reduce the morbidity and mortality associated with lung disease, new therapeutic strategies aimed at promoting lung repair and increasing the number of donor lungs available for transplantation are being explored. Because of the extreme complexity of this organ, previous attempts at bioengineering functional lungs from fully decellularized or synthetic scaffolds lacking functional vasculature have been largely unsuccessful. An intact vascular network is critical not only for maintaining the blood-gas barrier and allowing for proper graft function but also for supporting the regenerative cells. We therefore developed an airway-specific approach to removing the pulmonary epithelium, while maintaining the viability and function of the vascular endothelium, using a rat model. The resulting vascularized lung grafts supported the attachment and growth of human adult pulmonary cells and stem cell-derived lung-specified epithelial cells. We propose that de-epithelialization of the lung with preservation of intact vasculature could facilitate cell therapy of pulmonary epithelium and enable bioengineering of functional lungs for transplantation.
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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 | 0.001 |
| 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".