Mesenchymal cells support the early retention of primary alveolar type 2 cells on acellular mouse lung scaffolds
Bibliographic record
Abstract
Objectives: Tissue engineering approaches via repopulation of acellular biological grafts provide an exciting opportunity to generate lung grafts for transplantation. Alveolar type 2 (AT2) cells are a promising cell source for re-epithelialization. There are however inherent limitations with respect to their survival and growth, thus impeding their usability for tissue engineering applications. This study investigates the use of mesenchymal stromal cells to support primary AT2 cells for recellularization of mouse lung scaffolds. Methods: AT2 cells and bone marrow-derived mesenchymal cells (BMC) were co-delivered to decellularized mouse lung scaffolds. Recellularized lungs were evaluated for cell surface coverage, viability, and differentiation at 1 and 4 days after cell seeding. Recellularization was evaluated via histological analysis and immunofluorescence. Results: Simultaneous delivery of AT2 and BMC into acellular lung scaffolds resulted in enhanced cell surface coverage and reduced AT2 cell apoptosis in the recellularized scaffolds at Day 1 but not Day 4. AT2 cell number decreased after 4 days in both of AT2 only and codelivery groups suggesting limited expansion potential in the scaffold. After retention in the scaffold, AT2 cells differentiated into Aqp5-expressing cells. Conclusions: Our results indicate that BMC support AT2 cell survival during the initial attachment and engraftment phase of recellularization. While our findings suggest only a short-term beneficial effect of BMC, our study demonstrates that AT2 cells can be delivered and retained in acellular lung scaffolds; thus with preconditioning and supporting cells, may be used for re-epithelialization. Selection and characterization of appropriate cell sources for use in recellularization, will be critical for ultimate clinical application.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".