Receptor-Ligand Interaction Mediates Targeting of Endothelial Colony Forming Cell-derived Exosomes to the Kidney after Ischemic Injury
Bibliographic record
Abstract
Endothelial colony forming cell (ECFC)-derived exosomes protect mice against ischemic kidney injury, via transfer of microRNA-(miR)-486-5p. Mechanisms mediating exosome recruitment to tissues are unclear. We hypothesized that ECFC exosomes target ischemic kidneys, involving interaction between exosomal CXC chemokine receptor type 4 (CXCR4) and stromal cell-derived factor (SDF)-1α. Ischemia-reperfusion was induced in mice by bilateral renal vascular clamp, with intravenous infusion of exosomes at reperfusion. Optical imaging determined exosome biodistribution, and miR-486-5p was measured by real-time PCR. Human umbilical vein endothelial cells (HUVECs) were cultured to study the CXCR4/SDF-1α interaction. Targeting of administered exosomes to ischemic kidneys was detected 30 min and 4 hrs after reperfusion. Exosomes increased miR-486-5p levels only in kidneys, within proximal tubules, glomeruli, and endothelial cells. Uptake of fluorescently-labeled exosomes into HUVECs, and exosomal transfer of miR-486-5p were enhanced by hypoxia, effects blocked by neutralizing antibody to SDF-1α or by the CXCR4 inhibitor plerixafor. Infusion of ECFC exosomes prevented ischemic kidney injury in vivo, an effect that was not observed when exosomes were pre-incubated with plerixafor. These data indicate that ECFC exosomes selectively target the kidneys after ischemic injury, with rapid cellular transfer of miR486-5p. Targeting of exosomes may involve interaction of CXCR4 with endothelial cell SDF-1α.
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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 | 0.001 |
| 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) | 0.000 | 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 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".