Effects of bone marrow-derived mesenchymal stromal cells on gene expression in human alveolar type II cells exposed to TNF-<i>α</i>, IL-1<i>β</i>, and IFN-<i>γ</i>
Bibliographic record
Abstract
The acute respiratory distress syndrome (ARDS) is common in critically ill patients and has a high mortality rate. Mesenchymal stromal cells (MSCs) have demonstrated therapeutic potential in animal models of ARDS, and their benefits occur in part through interactions with alveolar type II (ATII) cells. However, the effects that MSCs have on human ATII cells have not been well studied. Using previously published microarray data, we performed genome-wide differential gene expression analyses of human ATII cells that were (1) unstimulated, (2) exposed to proinflammatory cytokines (CytoMix), or (3) exposed to proinflammatory cytokines plus MSCs. Findings were validated by qPCR. Alveolar type II cells differentially expressed hundreds of genes when exposed either to proinflammatory cytokines or to proinflammatory cytokines plus MSCs. Stimulation with proinflammatory cytokines increased expression of inflammatory genes and downregulated genes related to surfactant function and alveolar fluid clearance. Some of these changes, including expression of some cytokines and genes related to surfactant, were reversed by exposure to MSCs. In addition, MSCs induced upregulation of other potentially beneficial genes, such as those related to extracellular matrix remodeling. We confirmed several of these gene expression changes by qPCR. Thus, ATII cells downregulate genes associated with surfactant and alveolar fluid clearance when exposed to inflammatory cytokines, and mesenchymal stromal cells partially reverse many of these gene expression changes.
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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) | 0.000 | 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) | 0.002 | 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 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".