Stem cell therapy for acute respiratory distress syndrome
Bibliographic record
Abstract
PURPOSE OF REVIEW: Acute respiratory distress syndrome (ARDS) is a devastating disease process with a 40% mortality rate, and for which there is no therapy. Stem cells are an exciting potential therapy for ARDS, and are currently the subject of intensive ongoing research efforts. We review data concerning the therapeutic promise of cell-based therapies for ARDS. RECENT FINDINGS: Recent experimental studies suggest that cell-based therapies, particularly mesenchymal stem/stromal cells (MSCs), endothelial progenitor cells, and embryonic or induced pluripotent stem cells all offer considerable promise for ARDS. Of these cell types, mesenchymal stromal cells offer the greatest potential for allogeneic therapy, given the large body of preclinical data supporting their use, and the advanced state of our understanding of their diverse mechanisms of action. Although other stem cells such as EPCs also have therapeutic potential, greater barriers exist, particularly the requirement for autologous EPC therapy. Other stem cells, such as ESCs and iPSCs, are at an earlier stage in the translational process, but offer the hope of directly replacing injured lung tissue. Ultimately, lung-derived stem cells may offer the greatest hope for lung diseases, given their homeostatic role in replacing and repairing damaged native lung tissues.MSCs are currently in early phase clinical trials, the results of which will be of critical importance to subsequent translational efforts for MSCs in ARDS. A number of translational challenges exist, including minimizing variability in cell batches, developing standard tests for cell potency, and producing large amounts of clinical-grade cells for use in patients. SUMMARY: Cell-based therapies, particularly MSCs, offer considerable promise for the treatment of ARDS. Overcoming translational challenges will be important to fully realizing their therapeutic potential for ARDS.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".