Circulating Exosomes Isolated from Septic Mice Induce Cardiovascular Hyperpermeability Through Promoting Podosome Cluster Formation
Bibliographic record
Abstract
Septic shock increases vascular permeability, leading to multiple organ failure including cardiac dysfunction, a major contributor to septic death. Podosome, an actin-based dynamic membrane structure, plays critical roles in extracellular matrix degradation and angiogenesis. However, whether podosome contributes to endothelial barrier dysfunction during septic shock remains unknown. In this study, we found that the endothelial hyperpermeability, stimulated by phorbol 12-myristate 13-acetate and thrombin, was accompanied by increased formation of podosome clusters at the cell periphery, indicating a positive correlation between podosome clusters and endothelial leakage. Interestingly, we observed that circulating exosomes collected from septic mice were able to stimulate podosome cluster formation in cardiac endothelial cells, together with increased permeability in vitro/in vivo and cardiac dysfunction. Mechanistically, we identified that septic exosomes contained higher levels of reactive oxygen species (ROS) than normal ones, which were effectively transported to endothelial cells (ECs). Depletion of ROS in septic exosomes significantly reduced their capacity for promoting podosome cluster formation and thereby dampened vascular leakage. Finally, we elucidated that podosome cluster-induced endothelial hyperpermeability was associated with fragmentation/depletion of zonula occludens-1 (ZO-1) at the cell periphery. Our results demonstrate that septic exosomes were enriched with high amounts of ROS, which can be transported to ECs, leading to the generation of podosome clusters in target ECs and thereby, causing ZO-1 relocation, vascular leakage, and cardiac dysfunction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".