Measurement and analysis of ionic leakage profiles in refrigerated human red blood cells using dielectrophoresis and inductively coupled mass spectroscopy
Bibliographic record
Abstract
Abstract Human red blood cells (RBCs) undergo ionic leakage through passive diffusion during refrigerated storage, affecting their quality and health. We investigated the dynamics of ionic leakage in human RBCs over a 20‐day refrigerated storage period using extracellular ion quantification and dielectrophoresis (DEP). Four type O− human blood donors were examined to assess the relationship between extracellular ion concentrations (Na + , K + , Mg 2+ , Ca 2+ , and Fe 2+ ), RBC cytoplasm conductivity, and membrane conductance. A consistent negative correlation between RBC cytoplasm conductivity and membrane conductance, termed the “ionic leakage profile” (ILP), was observed across the 20‐day storage period. Specifically, we noted a gradual decline in DEP‐measured RBC cytoplasm conductivity alongside an increase in membrane conductance. Further examination of the electrical origins of this ILP using inductively coupled plasma mass spectrometry revealed a relative decrease in extracellular Na + concentration and an increase in K + concentration over the storage period. Correlation of these extracellular ion concentrations with DEP‐measured RBC electrical properties demonstrated a direct link between changes in the cytoplasmic and membrane domains and the leakage and transport of K + and Na + ions across the cell membrane. Our analysis suggests that the inverse correlation between RBC cytoplasm and membrane conductance is primarily driven by the passive diffusion of K + from the cytoplasm and the concurrent diffusion of Na + from the extracellular buffer into the membrane, resulting in a conductive reduction in the cytoplasmic domain and a subsequent increase in the membrane. The ILP's consistent negative trend across all donors suggests that it could serve as a metric for quantifying blood bank storage age, predicting the quality and health of refrigerated RBCs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".