Differential effects of the cystic fibrosis lung inflammatory environment on mesenchymal stromal cells
Bibliographic record
Abstract
Growing evidence demonstrates that human mesenchymal stromal cells (MSCs) modify their in vivo anti-inflammatory actions depending on the specific inflammatory environment encountered. Understanding this better is crucial to refine MSC-based cell therapies for lung and other diseases. Using acute exacerbations of cystic fibrosis (CF) lung disease as a model, the effects of ex vivo MSC exposure to clinical bronchoalveolar lavage fluid (BALF) samples, as a surrogate for the in vivo clinical lung environment, on MSC viability, gene expression, secreted cytokines, and mitochondrial function were compared with effects of BALF collected from healthy volunteers. CF BALF samples that cultured positive for Aspergillus sp. (Asp) induced rapid MSC death, usually within several hours of exposure. Further analyses suggested the fungal toxin gliotoxin as a potential mediator contributing to CF BALF-induced MSC death. RNA sequencing analyses of MSCs exposed to either Asp+ or Asp− CF BALF samples identified a number of differentially expressed transcripts, including those involved in interferon signaling, antimicrobial gene expression, and cell death. Toxicity did not correlate with bacterial lung infections. These results suggest that the potential use of MSC-based cell therapies for CF or other lung diseases may not be warranted in the presence of Aspergillus.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".