Characterization of Microvesicles in Septic Shock Using High-Sensitivity Flow Cytometry
Bibliographic record
Abstract
PURPOSE: Endothelial pathology is considered to play a key role in septic shock. Since endothelial-derived microvesicles (MV) are elevated in various diseases associated with endothelial pathology, they are considered surrogate markers of the endothelial state. By analyzing the signature of circulating MV with high-sensitivity flow cytometry (hsFC), we wanted to test the hypothesis whether endothelial-derived MV are increased in septic shock. METHODS: MV in blood from healthy volunteers and patients with septic shock treated in a medical intensive care unit were quantified by hsFC, which has an improved detection limit of approximately 0.3 μm. RESULTS: Patients with septic shock (n = 30) showed 3-fold higher levels of CD31+/CD41- MV (58.5 (26.4-101.2) [median (25th-75th percentile)] vs. 19.5 (12.8-25.4) MV/μL; P <0.001) compared with healthy volunteers (n = 18). Absolute counts of CD144+, CD62E+, and CD106+ MV, specific for endothelial-derived MV, were low in all groups. The number of CD31+/CD41- MV correlated significantly with leukocyte count (rs = 0.64; P <0.001). Platelet-derived CD41+ MV were significantly elevated in the group dying within 48 h after inclusion (639.1 (321.3-969.7) vs. 221.5 (119.5-456.9) MV/μL; P = 0.037). Patients dying within 48 h had also significantly higher levels of CD31+/CD41-/AnnexinV- MV (51.9 (24.9-259.8) vs. 18.9 (9.7-31) MV/μL; P = 0.028). CONCLUSIONS: Despite an improved detection limit for MV by using hsFC, counts of endothelial-specific MV are unexpectedly low in patients with septic shock. Increased amounts of CD41+ and CD31+/CD41-/AnnexinV- MV indicate release by activated platelets and possibly leukocytes correlating with unfavorable outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".