Blood bank storage of red blood cells increases RBC cytoplasmic membrane order and bending rigidity
Bibliographic record
Abstract
Blood banks around the world store blood components for several weeks ensuring its availability for transfusion medicine. Red blood cells (RBCs) are known to undergo compositional changes during storage, which may impact the cells' function and eventually the recipients' health. We extracted the RBC's cytoplasmic membrane (RBCcm) to study the effect of storage on the membranes' molecular structure and bending rigidity by a combination of X-ray diffraction (XRD), X-ray diffuse scattering (XDS) and coarse grained Molecular Dynamics (MD) simulations. Blood was stored in commercial blood bags for 2 and 5 weeks, respectively and compared to freshly drawn blood. Using mass spectrometry, we measured an increase of fatty acids together with a slight shift towards shorter tail lengths. We observe an increased fraction (6%) of liquid ordered (lo) domains in the RBCcms with storage time, and an increased lipid packing in these domains, leading to an increased membrane thickness and membrane order. The size of both, lo and liquid disordered (ld) lipid domains was found to decrease with increased storage time by up to 25%. XDS experiments reveal a storage dependent increase in the RBCcm's bending modulus κ by a factor of 2.8, from 1.9 kBT to 5.3 kBT. MD simulations were conducted in the absence of proteins. The results show that the membrane composition has a small contribution to the increased bending rigidity and suggests additional protein-driven mechanisms.
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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) | 0.002 | 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".