The Relationship of Circulating Extracellular Vesicles to Small Vessel Disease in Acute Ischemic Stroke
Bibliographic record
Abstract
The association between Extracellular Vesicles (EVs) and Small Vessel Disease (SVD) might aid in the accurate early diagnosis and prognosis of acute ischemic stroke (AIS). This may be crucial for implementing the appropriate care plan and follow-up measures to limit the risk of permanent damage and prevent future occurrences. The purpose of the present study was to investigate the connection between circulating levels of EVs from various cellular origins and AIS severity biomarkers, established risk factors, and the presence of SVD as determined by noninvasive MRI imaging.The count of total circulating medium-size EVs and their phenotyping according to cellular origins were determined by flow cytometry analysis in platelet-free plasma from healthy volunteers and patients with AIS. Then, the relationship between the circulating of EVs to SVD and other risk factors was studied.When compared with controls, AIS patients exhibited a significantly higher number of circulating EVs originating from the endothelial cells, platelets, activated platelets, erythrocytes, and granulocytes. Multinomial logistic regression analysis showed a strong association between increased numbers of EVs derived from activated platelets (CD62P+) and erythrocytes (CD235a+) and the odds risk of AIS. However, it was found that a one-unit increase in CD235a+ EVs is associated with a 0.77-unit decrease in the odds of having SVD. Most AIS patients with SVD had hypertension, white matter ischemia, silent infarct, Basis Pontis ischemia, and cerebral microbleeds. However, the most significant risk for SVD was found in patients with hypertension on admission. Patients with hypertension on admission were 9.33 times more likely to have SVD than patients without hypertension on admission.Our findings underscore the value of circulating EVs as biomarkers of cell activation and thrombosis in AIS. Furthermore, our findings suggest a potential pathophysiological role for EVs in the onset and development of SVD and an interrelationship with major risk factors for AIS such as hypertension. Altogether, the association of EVs and non-invasive MRI imaging assessment of SVD presence may represent a novel combined approach for the identification of individuals with the highest risk of AIS and patients with the highest odds of recurrent stroke. This study was made possible by Qatar National Research Fund [grant No. NPRP11S-0114-180289]. The statements made herein are solely the responsibility of the authors. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.
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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 | 0.000 | 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".