Abstract 158: Bioactive Lipids As Biomarkers Of Severe Adverse Reaction Associated With Apheresis Platelet Concentrate Transfusion
Bibliographic record
Abstract
Blood transfusion is a life-saving procedure in which whole blood, or blood components are provided to a patient. Platelet concentrates (PC) may sometimes induce adverse reactions, that are occasionally severe. PC comprise active biomolecules such as cytokines and lipid mediators. Platelet storage lesions are structural and biochemical changes in PC and vary in collection and processing conditions. We investigated lipid mediators as bioactive molecules along storage conditions and in adverse reactions after transfusion. The PC left over were analysed after transfusion, classified with/out severe reaction. Our data presented a decrease of lysophosphatidylcholine species to produce lysophosphatidic acid species. This balance could lead and be correlated with complication symptoms, as other lipids. Lysophosphatidic acid increased with primarily platelet-inhibitor-lipids when single donor apheresis platelet upon storage. Anti-inflammatory and platelet-induced-inhibition lipids were weakly expressed in case of severe adverse reaction. Thus, a decrease in lysophosphatidylcholine and an increase in lysophosphatidic acid could be reliable predictors of serious adverse transfusion reactions transfusion. These data highlighted the importance of PC manufacturing and storage processing, not only to maximize clinical efficacy but also to minimize adverse reactions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".