The platelets’ perspective to pathogen reduction technologies
Bibliographic record
Abstract
A wide variety of clinical conditions, associated with low circulating platelet counts, require platelet transfusion in order to normalize hemostatic function. Although single-donor apheresis platelets bear the lowest risk of transfusion-transmitted infections, pathogen reduction technologies (PRT) are being implemented worldwide to reduce this risk further through inactivation of known, emergent and as yet to be discovered nucleic acid-based pathogens. Human blood platelets are now known to harbor a diverse transcriptome, important to their function and comprised of >5000 protein-coding messenger RNAs and different classes of non-coding RNAs, including microRNAs. Our appreciation of the nucleic acid-dependent functions of platelets is likely to increase. On the other hand, the side effects of PRT on platelet function are underappreciated. Recent evidences suggest that PRT may compromise platelets' responsiveness to agonists, and induce platelet activation. For instance, platelets have the propensity to release proinflammatory microparticles (MPs) upon activation, and the possibility that PRT may enhance the production of platelet MPs in platelet concentrates (PCs) appears likely. With this in mind, it would be timely and appropriate to investigate other means to inactivate pathogens more specifically, or to modify the currently available PRT so to better preserve the platelet function and improve the safety of PCs; platelets' perspective to PRT deserves to be considered.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".