Releasates of riboflavin/<scp>UV</scp>‐treated platelets: Microvesicles suppress cytokine‐mediated endothelial cell migration/proliferation
Bibliographic record
Abstract
BACKGROUND: Accelerated development of the platelet (PLT) storage lesion upon pathogen inactivation (PI) is associated with the release of proteins from granules and platelet microvesicles (PMVs). Whether PI treatments alter the interaction between PLT factors and the vessel endothelium is of interest in understanding the risk profile of these technologies. STUDY DESIGN AND METHODS: In a pool-and-split study, one platelet concentrate (PC) was treated with riboflavin/UV (RF/UV) light, while the other one was kept as an untreated control. Releasates and PMV-depleted releasates were prepared by differential centrifugation steps on days 0, 1, 5, and 7 of storage. Cytokine/chemokine release following PI treatment was analyzed by an antibody array, and results were verified by the enzyme-linked immunosorbent assay. PMVs were enumerated by CD41 labeling and flow cytometry. Wound scratch assays were performed using cultured Ea.hy926 cells exposed to the differently prepared releasates. Effects of releasates on the phosphorylation levels of kinases ERK and p38 expressed by endothelial cells were analyzed by immunoblot. RESULTS: Cytokine/chemokine assays identified a 2-fold increase in epidermal growth factor released from PCs treated with RF/UV light compared with control. PMV count increased ~100-fold following PI treatment. Unmodified releasates and PMV-depleted releasates displayed different contributions to the kinetics of endothelial cell wound closure. This observation was associated with an increased ERK versus unaltered p38 activation in the endothelial cells. CONCLUSION: This study identified an inhibitory impact of PMVs on endothelial cell migration/proliferation upon stimulation by released cytokines and PMVs from PLTs treated with RF/UV light for endothelial cell wound closure.
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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".