Platelet-derived microvesicles modulate the bioenergetic and inflammatory phenotype of human polymorphonuclear leukocytes
Bibliographic record
Abstract
Platelets release microvesicles (PMVs) into the extracellular milieu upon activation. PMVs retain various platelet components, including functional mitochondria, and actively participate in intercellular communication with immune cells such as polymorphonuclear leukocytes (PMNs). PMVs have been known to modulate the inflammatory response of PMNs under normal physiological condition. Despite growing interest in the transfer of biological material between immune cells, the mitochondrial content shuttling from PMVs to PMNs and the resulting effects have remained unclear. Using freshly isolated PMVs from healthy and consenting donors, we demonstrate that PMVs modulate both the bioenergetic and inflammatory phenotypes of the recipient immune cell. We first confirmed the mitochondrial content transfer and then measured cell viability, mitochondrial respiration, and ATP production. Platelet-derived mitochondria were found associated with PMNs, consequently decreasing caspase-3 activity. PMVs increased mitochondrial activity and ATP levels in the recipient cell. Incubation of PMNs with PMVs containing nonfunctional mitochondria did not affect respiration and caspase-3 activity. This demonstrates that functional and active mitochondria are required for the PMVs to modulate the bioenergenetic phenotype of human PMNs. Finally, we detected the transfer of active 12-lipoxygenase and of cyclooxygenase-1 in the recipient cells, enzymes found specifically in PMVs, and an increase in the production of their respective inflammatory products. These findings suggest that platelet-derived mitochondria play a key role in enhancing the survival and inflammatory function of PMNs in inflammatory conditions.
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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) | 0.001 | 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".