Stage‐Specific Generation of Human Pluripotent Stem Cell Derived Lung Models to Measure CFTR Function
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human embryonic stem cells (ES) and induced pluripotent stem cells (iPSC) are powerful tools that have the potential to generate in vitro human lung epithelial cells. However, challenges in efficiency and reproducibility remain in utilizing the cells for therapy discovery platforms. Here, we optimize our previously published protocols to efficiently generate three developmental stages of the lung model (fetal lung epithelial progenitors, fLEP; immature airway epithelial spheroid, AES; air-liquid interface culture, ALI), and demonstrate its potential for cystic fibrosis (CF) drug discovery platforms. The stepwise approach directs differentiation from hPSC to definitive endoderm, anterior ventral foregut endoderm, and fetal lung progenitor cells. The article also describes the generation of immature airway epithelial spheroids in Matrigel with epithelial cells sorted by a magnetic-activated cell sorting system, and the generation of adult-like airway epithelia through air-liquid interface conditions. We demonstrate that this optimized procedure generates remarkably higher cystic fibrosis transmembrane conductance regulator (CFTR) expression and function than our previous method, and thus is uniquely suitable for CF research applications. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: hESC/hiPSC differentiation to fetal lung progenitors Basic Protocol 2: Formation of airway epithelial spheroids Alternate Protocol 1: Cryopreservation of airway epithelial spheroids Basic Protocol 3: Differentiation and maturation in air-liquid interface culture Alternate Protocol 2: Differentiation and maturation of epithelial progenitors from airway epithelial spheroids in ALI culture.
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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) | 0.000 | 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 | 0.001 |
| 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 it