In vitro exposure of whole blood to a cannabinoid mixture impairs the quality of red blood cells and platelets.
Bibliographic record
Abstract
BACKGROUND: In a recent study, 13.8% of blood donors had reported cannabis use in the 72 hours preceding their donation, and these donors are not deferred under existing criteria in Canada. This high prevalence raises concerns about the potential impact of cannabis use on the quality of blood products. The current study assessed the impact of a cannabinoid mixture on the quality of red blood cells and platelets, from the time of collection and processing to their storage. MATERIALS AND METHODS: To mimic pre-donation cannabis use, whole blood was collected and exposed (in vitro) to varying concentrations (range: 1-24 μg/mL) of a cannabinoid mixture (CM) overnight. Whole blood was then separated into red blood cells (RBCs) and platelets-rich plasma (PRP), which were stored at 4°C (for RBCs) or at room temperature (for PRP). Flow cytometry analyses, hemolysis measurements and biochemical analyses were performed during the processing stage and throughout storage. RESULTS: In the RBC fraction, free hemoglobin levels were increased in a dose-dependent manner after the addition of a cannabinoid mixture to whole blood. Hemolysis and methemoglobin levels were significantly higher in CM-exposed RBCs than CM-free controls, after processing and throughout storage. Furthermore, platelet counts and CD62P expression (on day 7 post-separation) were significantly lower in CM-exposed PRP than cannabinoid-free PRP controls. The aggregation potential of CM-exposed platelets was significantly lower than that of cannabinoid-free controls, after the processing and throughout storage. DISCUSSION: An in vitro exposure to a cannabinoid mixture hemolyzed RBCs, impaired oxygen transport by RBCs, reduced platelet counts, and impaired platelet function. These results suggest that pre-donation cannabis use might impair the quality of blood products.
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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 | 0.001 |
| 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".