Characterization of red blood cell deformability change during blood storage
Bibliographic record
Abstract
Stored red blood cells (RBCs) show progressive deformability changes during blood banking/storage. Their deformability changes over an 8 weeks' storage period were measured using a microfluidic device. Hydrodynamic focusing controls the orientation and position of individual RBCs within the microchannel. High-speed imaging (5000 frames s(-1)) captures the dynamic deformation behavior of the cells, and together with automated image analysis, enables the characterization of over 1000 RBCs within 3 minutes. Multiple parameters including deformation index (DI), time constant (shape recovery rate), and RBC circularity were quantified. Compared to previous studies on stored RBC deformability, our results include a significantly higher number of cells (>1000 cells per sample vs. a few to tens of cells per sample) and, for the first time, reveal deformation changes of stored RBCs when traveling through human-capillary-like microchannels. Contrary to existing knowledge, our results demonstrate that the deformation index of RBCs under folding does not change significantly over blood storage. However, significant differences exist in time constants and circularity distribution widths, which can be used to quantify stored RBC quality or age.
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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 | 0.001 |
| 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".