Hypoxia-preconditioned mesenchymal stem cells ameliorate ischemia/reperfusion-induced lung injury
Bibliographic record
Abstract
BACKGROUND: Hypoxia preconditioning has been proven to be an effective method to enhance the therapeutic action of mesenchymal stem cells (MSCs). However, the beneficial effects of hypoxic MSCs in ischemia/reperfusion (I/R) lung injury have yet to be investigated. In this study, we hypothesized that the administration of hypoxic MSCs would have a positive therapeutic impact on I/R lung injury at molecular, cellular, and functional levels. METHODS: I/R lung injury was induced in isolated and perfused rat lungs. Hypoxic MSCs were administered in perfusate at a low (2.5×105 cells) and high (1×106 cells) dose. Rats ventilated with a low tidal volume of 6 ml/kg served as controls. Hemodynamics, lung injury indices, inflammatory responses and activation of apoptotic pathways were determined. RESULTS: I/R induced permeability pulmonary edema with capillary leakage and increased levels of reactive oxygen species (ROS), pro-inflammatory cytokines, adhesion molecules, cytosolic cytochrome C, and activated MAPK, NF-κB, and apoptotic pathways. The administration of a low dose of hypoxic MSCs effectively attenuated I/R pathologic lung injury score by inhibiting inflammatory responses associated with the generation of ROS and anti-apoptosis effect, however this effect was not observed with a high dose of hypoxic MSCs. Mechanistically, a low dose of hypoxic MSCs down-regulated P38 MAPK and NF-κB signaling but upregulated glutathione, prostaglandin E2, IL-10, mitochondrial cytochrome C and Bcl-2. MSCs infused at a low dose migrated into interstitial and alveolar spaces and bronchial trees, while MSCs infused at a high dose aggregated in the microcirculation and induced pulmonary embolism. CONCLUSIONS: Hypoxic MSCs can quickly migrate into extravascular lung tissue and adhere to other inflammatory or structure cells and attenuate I/R lung injury through anti-oxidant, anti-inflammatory and anti-apoptotic mechanisms. However, the dose of MSCs needs to be optimized to prevent pulmonary embolism and thrombosis.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.002 |
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".