Recent Advancements in the Generation and Application of Therapeutic Cell Populations for Lung Epithelial Repair
Bibliographic record
Abstract
Chronic respiratory diseases are a major global health concern. Lung epithelial dysfunction is a common underlying feature of many such conditions; hence, reconstructing the diseased epithelium with functional epithelial cells is a promising therapeutic approach. There are various endogenous stem cell and progenitor populations in the lung epithelium that can be utilized for transplantation. Additionally, pluripotent stem cells (PSCs) have emerged as a valuable source for generating therapeutic cells due to their capacity for indefinite self-renewal and the availability of directed differentiation protocols to transform them into lung progenitors or mature lung epithelial cells. This review discusses the endogenous stem cell and progenitor populations of the lung epithelium, recent advances in developing directed differentiation protocols to generate these cells, and the application of both endogenous and PSC-derived lung epithelial cells for disease modeling in vitro and as cell therapies in vivo. It provides valuable insights into the current progress of regenerative medicine within the respiratory field and highlights areas that require further research.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".