Dielectrophoretic Detection of Electrical Property Changes of Stored Human Red Blood Cells
Bibliographic record
Abstract
The ability to transport and store a large human blood inventory for transfusions is an essential requirement for medical institutions. Thus, there is an important need for rapid and low-cost characterization tools for analyzing the properties of human red blood cells (RBCs) while in storage. In this study, we investigate the ability to use dielectrophoresis (DEP) for measuring the storage-induced changes in RBC electrical properties. Fresh human blood was collected, suspended in K2-EDTA anticoagulant and stored in a blood bank refrigerator for a period of 20 days. Cells were removed from storage at 5-day intervals and subjected to a glutaraldehyde crosslinking reaction to “freeze” cells at their ionic equilibrium at that point in time and prevent ion leakage during DEP analysis. The DEP behavior of RBCs was analyzed in a high permittivity DEP buffer using a three-dimensional DEP chip (3DEP) and also compared to measurements taken with a 2D quadrupole electrode array. The DEP analysis confirms that RBC electrical property changes occur during storage and are only discernable with the use of the cell crosslinking reaction above a glutaraldehyde fixation concentration of 1.0 w/v%. In particular, cytoplasm conductivity was observed to decrease by more than 75% while the RBC membrane conductance was observed to increase by more than 1000% over a period of 20 days. These results show that the presented combination of chemical crosslinking and DEP can be used as rapid characterization tool for monitoring electrical properties changes of human red blood cells while subjected to refrigeration in blood bank storage.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".