Lung inflammatory environments differentially alter mesenchymal stromal cell behavior
Bibliographic record
Abstract
Mesenchymal stromal (stem) cells (MSCs) are increasingly demonstrated to ameliorate experimentally induced lung injuries through disease-specific anti-inflammatory actions, thus suggesting that different in vivo inflammatory environments can influence MSC actions. To determine the effects of different representative inflammatory lung conditions, human bone marrow-derived MSCs (hMSCs) were exposed to in vitro culture conditions from bronchoalveolar lavage fluid (BALF) samples obtained from patients with either the acute respiratory distress syndrome (ARDS) or with other lung diseases including acute respiratory exacerbations of cystic fibrosis (CF) (non-ARDS). hMSCs were subsequently assessed for time- and BALF concentration-dependent effects on mRNA expression of selected pro- and anti-inflammatory mediators, and for overall patterns of gene and mRNA expression. Both common and disease-specific patterns were observed in gene expression of different hMSC mediators, notably interleukin (IL)-6. Conditioned media obtained from non-ARDS BALF-exposed hMSCs was more effective in promoting an anti-inflammatory phenotype in monocytes than was conditioned media from ARDS BALF-exposed hMSCs. Neutralizing IL-6 in the conditioned media promoted generation of anti-inflammatory monocyte phenotype. This proof of concept study suggest that different lung inflammatory environments potentially can alter hMSC behaviors. Further identification of these interactions and the driving mechanisms may influence clinical use of MSCs for treating lung diseases.
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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) | 0.001 | 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 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".