Ischemia-Reperfusion Lung Injury Is Attenuated in MyD88-Deficient Mice
Bibliographic record
Abstract
Ischemia-reperfusion lung injury is a common cause of acute morbidity and mortality in lung transplant recipients and has been associated with subsequent development of bronchiolitis obliterans syndrome. Recognition of endogenous ligands released during cellular injury (damage-associated molecular patterns; DAMPs) by Toll-like receptors (TLRs), especially TLR4, has increasingly been recognized as a mechanism for inflammation resulting from tissue damage. TLR4 is implicated in the pathogenesis of ischemia-reperfusion injury of multiple organs including heart, liver, kidney and lung. Additionally, activation of TLRs other than TLR4 by DAMPs has been identified in tissues other than the lung. Because all known TLRs, with the exception of TLR3, signal via the MyD88 adapter protein, we hypothesized that lung ischemia-reperfusion injury was mediated by MyD88-dependent signaling. To test this hypothesis, we subjected C57BL/6 wildtype, Myd88(-/-), and Tlr4(-/-) mice to 1 hr of left lung warm ischemia followed by 4 hr of reperfusion. We found that Myd88(-/-) mice had significantly less MCP-1/CCL2 in the left lung following ischemia-reperfusion as compared with wildtype mice. This difference was associated with dramatically reduced lung permeability. Interestingly, Tlr4(-/-) mice had only partial protection from ischemia-reperfusion as compared to Myd88(-/-) mice, implicating other MyD88-dependent pathways in lung injury following ischemia-reperfusion. We also found that left lung ischemia-reperfusion caused remote inflammation in the right lung. Finally, using chimeric mice with MyD88 expression restricted to either myeloid or non-myeloid cells, we found that MyD88-dependent signaling in myeloid cells was necessary for ischemia-reperfusion induced lung permeability. We conclude that MyD88-dependent signaling through multiple receptors is important in the pathogenesis of acute lung inflammation and injury following ischemia and reperfusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".