Nasal mucosa-derived ecto-mesenchymal stem cells ameliorate LPS-induced acute lung injury
Bibliographic record
Abstract
Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are associated with significant morbidity and mortality rates. Mesenchymal stem cells (MSCs) derived from nasal mucosa, known as EMSCs, have demonstrated therapeutic potential in conditions such as liver failure and bone defects. However, investigations focusing on the application of EMSCs in ALI are still lacking. In our study, an ALI model was induced in rats through lipopolysaccharide (LPS) administration, with subsequent intravenous delivery of either saline or EMSCs. Co-culture experiments using transwell systems revealed that EMSCs improved the viability and proliferation of A549 cells, while also suppressing LPS-induced inflammation and apoptosis. Moreover, the administration of EMSCs not only improved pulmonary microvascular permeability and alleviated histopathological damage, but also exerted downregulatory effects on the levels of pro-inflammatory cytokines, including TNFα, IL6, and IL-1β, while concurrently upregulating the expression of anti-inflammatory cytokine IL-10 in both bronchoalveolar lavage fluid (BALF) and plasma. Immunohistochemistry analysis further revealed an elevated expression of proliferation marker Ki67 and anti-apoptotic protein Bcl2, accompanied by a reduction in the expression of pro-apoptotic protein Bax, thus indicating the beneficial outcomes of EMSCs. Collectively, these findings underscore the potential of EMSC-based therapies as promising and effective strategies for the treatment of lung injury.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".