Assessing the Vascular Deformability of Erythrocytes and Leukocytes: From Micropipettes to Microfluidics
Bibliographic record
Abstract
Among the most crucial rheological characteristics of blood cells within the vasculature is their ability to undergo the shape change (i.e., deform). The significance of cellular deformability is readily apparent based solely on the disparate mean size of human erythrocytes (~8 μm) and leukocytes (10–25 μm) compared to the minimum luminal size of capillaries (4–5 μm) and splenic interendothelial clefts (0.5–1.0 μm) they must transit. Changes in the deformability of either cell will result in their premature mechanical clearance as well as an enhanced possibility of intravascular lysis. In this chapter, we will demonstrate how microfluidic devices can be used to examine the vascular deformability of erythrocytes and agranular leukocytes. Moreover, we will compare microfluidic assays with previous studies utilizing micropipettes, ektacytometry and micropore cell transit times. As will be discussed, microfluidics-based devices offer a low-cost, high throughput alternative to these previous, and now rather ancient, technologies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".