Cell-Based Therapeutic Approaches for Cystic Fibrosis
Bibliographic record
Abstract
Cystic Fibrosis (CF) is a chronic autosomal recessive disease caused by defects in the cystic fibrosis transmembrane conductance regulator gene (CFTR). Cystic Fibrosis affects multiple organs but progressive remodeling of the airways, mucus accumulation, and chronic inflammation in the lung, result in lung disease as the major cause of morbidity and mortality. While advances in management of CF symptoms have increased the life expectancy of this devastating disease, and there is tremendous excitement about the potential of new agents targeting the CFTR molecule itself, there is still no curative treatment. With the recent advances in the identification of endogenous airway progenitor cells and in directed differentiation of pluripotent cell sources, cell-based therapeutic approaches for CF have become a plausible treatment method with the potential to ultimately cure the disease. In this review, we highlight the current state of cell therapy in the CF field focusing on the relevant autologous and allogeneic cell populations under investigation and the challenges associated with their use. In addition, we present advances in induced pluripotent stem (iPS) cell approaches and emerging new genetic engineering methods, which have the capacity to overcome the current limitations hindering cell therapy approaches.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".