The impact of biological age of red blood cell on in vitro endothelial activation markers
Bibliographic record
Abstract
Introduction: Blood donor characteristics influence red blood cell transfusion outcomes. As donor sex affects the distribution of young to old RBCs in the circulation, we hypothesized that the amount of circulating young RBCs in the blood product are associated with immune suppression. Materials and Methods: Blood samples were collected from healthy volunteers and density fractionated into young and old subpopulations. In an activated endothelial cell model, RBC adhesion to endothelium and secretion of endothelial activation markers were assessed. The impact of RBC biological age was also assessed in a T cell proliferation assay and in a whole blood stimulation assay. Results: After Percoll fractionation, young RBCs contained more reticulocytes compared to old RBCs. Young RBCs associated with lower levels of E-selectin, ICAM-1, and vWF from activated endothelial cells compared to old RBCs. RBC subpopulations did not affect T cell proliferation or cytokine responses following whole blood stimulation. Conclusion: Young RBCs contain more reticulocytes which are associated with lower levels of endothelial activation markers compared to old RBCs.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".