Human mesenchymal stromal cells decrease the severity of acute lung injury induced by E. coli in the rat
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Mesenchymal stromal cells (MSCs) demonstrate considerable promise in preclinical acute respiratory distress syndrome models. We wished to determine the efficacy and mechanisms of action of human MSCs (hMSCs) in the setting of acute lung injury induced by prolonged Escherichia coli pneumonia in the rat. METHODS: Adult male Sprague Dawley rats underwent intratracheal instillation of E. coli bacteria in all experiments. In Series 1, animals were randomised to intravenous administration of: (1) vehicle (phosphate buffered saline (PBS), 300 μL); (2) 1×10(7) fibroblasts/kg; (3) 1×10(7) hMSCs/kg or (4) 2×10(7) hMSCs/kg. Series 2 determined the lowest effective hMSC dose. Series 3 compared the efficacy of intratracheal versus intravenous hMSC administration, while Series 4 examined the efficacy of cryopreserved hMSC. Series 5 examined the efficacy of the hMSC secretome. Parallel in vitro experiments further assessed the potential for hMSCs to secrete LL-37 and modulate macrophage phagocytosis. RESULTS: hMSC therapy reduced the severity of rodent E. coli pneumonia, improving survival, decreasing lung injury, reducing lung bacterial load and suppressing inflammation. Doses as low as 5×10(6) hMSCs/kg were effective. Intratracheal hMSC therapy was as effective as intravenous hMSC. Cryopreserved hMSCs were also effective, while the hMSC secretome was less effective in this model. hMSC therapy enhanced macrophage phagocytic capacity and increased lung and systemic concentrations of the antimicrobial peptide LL37. CONCLUSIONS: hMSC therapy decreased E. coli induced pneumonia injury and reduced lung bacterial burden, potentially via enhanced macrophage phagocytosis and increased alveolar LL-37 concentrations.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it