Lipidomic analysis of differently prepared platelet concentrates in additive solution during storage.
Bibliographic record
Abstract
BACKGROUND: Structural and biochemical changes in stored platelets are influenced by collection and processing methods. Lesions may appear during platelet concentrate storage, some of which may be involved in adverse transfusion reactions. The preparation and storage of platelet concentrates (PC) may modify and even damage the lipid mediator content. The aim of this study was to investigate the lipidomic profile identified in the supernatants of PCs according to processing and storage conditions, both after leukocyte filtration and contained in platelet additive solution (PAS), comparing single donor apheresis (SDA) products with pooled buffy coat (BC) products. MATERIALS AND METHODS: We investigated the accumulation of various lipid mediators including lysophospholipids (LP) and eicosanoids in SDA and BC products stored for 0-5 days. All products were processed following French Blood Establishment (EFS) procedures in accordance with EDQM/GTS European Standards. Both SDA and BC were leukocyte reduced and conserved in 35% autologous donor plasma and 65% platelet additive solution. Lipidomic analysis was performed on PC supernatants using LS/MS spectrometry. RESULTS: Our data demonstrate that lysophosphatidylcholine (LPC) levels were higher in BCs compared to SDAs, with no difference in lysophosphatidic acid (LPA) expression between the two preparation methods. Results for other eicosanoids showed greater similarity; indeed, no clear pattern emerged from analysis of eicosanoids in terms of storage time and process. In general, we observed longitudinal lipid mediator modulation for both SDAs and BCs, particularly at later time points. DISCUSSION: The expression of LPC and some eicosanoids in BCs could be used as novel biomarkers of PC quality. Future studies are needed to explore their impact on adverse transfusion reactions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".