The Effect of Liposome Treatment on the Quality of Hypothermically Stored Red Blood Cells
Bibliographic record
Abstract
Recent studies have demonstrated that liposome treatment of red blood cells (RBCs) leads to improved recovery and membrane integrity following cryopreservation protocols. However, the effect of liposome treatment on hypothermically stored RBCs has not been previously investigated. The current study has investigated whether liposome treatment could modify the membrane quality and deformability of hypothermically stored RBCs. Unilamellar liposomes were synthesized using an extrusion protocol. Three lipid bilayer compositions were investigated: 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC):PE:PS (8:1:1); 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC):PE:PS (8:1:1); and 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC):PE:PS (8:1:1). RBCs were treated with liposomes and subsequently stored for 42 days in HEPES-NaCl buffer and saline-adenine-glucose-mannitol. RBC quality was assessed by percent hemolysis, mean corpuscular volume (MCV), and RBC deformability (ektacytometry). DOPC and DMPC liposome treatment resulted in destabilization of the RBC membrane. Percent hemolysis values for DMPC-treated RBCs were higher than untreated controls throughout storage (P<0.05). DOPC-treated RBCs showed elevated levels of hemolysis compared to controls from day 21 of storage onward (P<0.05). In addition, DOPC and DMPC-treated RBCs were less deformable than untreated controls from days 21(P=0.02) and 14 (P<0.001) of storage onward respectively. [We suggest that these changes in RBC hemolysis and deformability are due to cholesterol extraction from the RBC membrane into the liposome fraction.] In contrast, DPPC-treated RBCs maintained hemolysis, MCV, and deformability values comparable to untreated controls. Future research addressing the optimal liposome composition for stabilizing the RBC membrane at cold temperatures could lead to effective strategies to combat the RBC membrane hypothermic storage lesion and ultimately improve the quality of hypothermically preserved blood.
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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) | 0.001 | 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".