Changes in the Proportion of Each Cell Type After hiPSC-Derived Airway Epithelia Transplantation
Bibliographic record
Abstract
No radical treatment is available for the regeneration of dysfunction and defects in airway epithelia. Artificial tracheae made of polypropylene and collagen sponge were used in clinical studies to reconstitute tracheae after resection. For early epithelialization of the luminal surface of the artificial trachea, a model was established, that is, an artificial trachea covered with human-induced pluripotent stem cell-derived airway epithelial cells (hiPSC-AECs) was transplanted into a tracheal defect in an immunodeficient rat. Unlike the cell types of hiPSC-derived cells that are currently used in clinical studies, AECs maintain tissues by proliferation and differentiation of basal cells into various cell types that constitute AECs constantly. Therefore, post-transplantation, the proportion of each cell type, such as ciliated and goblet cells, may change; however, no studies have examined this possibility. In this study, using our hiPSC-AEC-transplanted rat model, we investigated changes in the proportion of each cell type in hiPSC-AECs pre-transplantation and post-transplantation. As a result, the proportion of each cell type changed post-transplantation. The proportion of ciliated, basal, and club cells increased, and the proportion of goblet cells decreased post-transplantation. In addition, the proportion of each cell type in engrafted hiPSC-AECs is more similar to the proportion of each cell type in normal proximal airway tissue than the proportion of each cell type pre-transplantation. The results of this study are useful for the development of therapeutic techniques using hiPSC-AEC transplantation.
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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 | 0.000 | 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) | 0.000 | 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".