Abstract 15061: Role of Exosomal Microrna-21a-5p in the Modulation of Ischemia-Induced Angiogenesis in Hypercholesterolemic Conditions
Bibliographic record
Abstract
Introduction: Extracellular vesicles (EVs) and their MicroRNA (miR) content are involved in several physiological processes, including the response to ischemia and angiogenesis. Hypercholesterolemia (HC) is an important cardiovascular risk factor associated with impaired angiogenesis and ischemia-induced neovascularization. However, the effect of HC on the modulation of miR content in EVs in the setting of tissue ischemia is unknown. Hypothesis: We tested the hypothesis that HC causes alterations in the miR content of EVs related to ischemia/neovascularization, and that engineered EVs can be harnessed as angiogenic vectors to promote angiogenesis and therapeutic neovascularization in this situation. Methods: We used a mouse model of peripheral artery disease to induce severe ischemia in the hindlimbs of hypercholesterolemic ApoE -/- and control C57Bl/6J mice. Microvesicles (MVs) and exosomes (exo) were isolated from ischemic skeletal muscles by differential centrifugation. Total RNA was extracted from these 2 types of EVs, and the miR content was analyzed using next generation sequencing. Selected miRs were transfected in EVs and the angiogenic capacity of the engineered EVs was assessed in vitro using a Matrigel assay. Results:: Bioinformatic analysis of the 100 most expressed miRs in EVs showed an enrichment of several miRs in EVs compared to ischemic skeletal muscles. Interestingly the highly expressed miR-21a-5p, which has previously been shown to have angiogenic properties, is specifically enriched in exo. Moreover, we found that miR-21a-5p expression is reduced in exo isolated from ischemic skeletal muscles in hypercholesterolemic conditions. We next forced miR-21a-5p expression in exo, and found that these engineered exo significantly increase tube formation in HUVECs. Conclusions: We show that several angiogenic miRs are enriched in EVs in the setting of tissue ischemia, and that HC can alter EV miR profile in this situation. miR-21a-5p, which expression is reduced by HC, was identified as an important modulator of exo angiogenic activity. Exo engineered to overexpress miR-21a-5p could eventually constitute a novel therapeutic strategy to promote neovascularization and reduce ischemic damages in severe vascular diseases.
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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 | 0.000 |
| 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; 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".