Effect of Liposome Treatment on Hemorheology and Metabolic Profile of Human Red Blood Cells During Hypothermic Storage
Bibliographic record
Abstract
BACKGROUND: Ex vivo cold storage of red blood cells (RBCs) for transfusion has long been associated with hypothermic storage lesions. It has been proposed that liposomes can be used to mitigate hemorheological elements of RBC membrane storage lesions. This study aimed to determine the appropriate liposome treatment time and assess the effects of liposome treatment on RBC's hemorheological and metabolic profiles. MATERIALS AND METHODS: Unilamellar liposomes were synthesized to contain a bilayer of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC):cholesterol (7:3 mol%). Packed human RBCs (n = 4) were divided into untreated control (HEPES-NaCl solution) and liposome-treated samples (2 mM DOPC liposomes) and treated at days 2, 21, and 42 of hypothermic storage. RBC quality assessment included percent hemolysis, deformability, aggregation, hematological indices, microvesiculation, supernatant potassium, adenosine triphosphate (ATP), and 2,3-diphosphoglycerate (2,3-DPG). RESULTS: Among the parameters affected by liposome treatment time were deformability, aggregation amplitude (Amp), mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, and microparticle mean fluorescence intensity. After 6 weeks of storage, aggregation index (AI) and Amp were significantly increased in liposome-treated RBCs (AI: 45.38 ± 1.92% vs. 41.54 ± 4.10%, p = 0.020; Amp: 16.38 ± 2.17 arbitrary units [au] vs. 12.22 ± 3.29 au, p = 0.019). Despite comparable hemolysis levels at 3 and 6 weeks, DOPC-treated RBCs showed significantly increased potassium levels for the same time points (3 weeks: 31.2 ± 2.7 mmol/L vs. 30.8 ± 2.7 mmol/L, p = 0.007; 6 weeks: 45.0 ± 3.0 mmol/L vs. 43.8 ± 3.4 mmol/L, p = 0.013). ATP and 2,3-DPG levels were comparable throughout storage. CONCLUSIONS: Liposome treatment seemed to be more beneficial when performed at the beginning of storage up to day 21. DOPC liposome treatment resulted in an improvement in human RBC hemorheology upon storage, with no significant impact on metabolic profile.
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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 | 0.000 |
| 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 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".