Multiplexed fluidic plunger mechanism for the measurement of red blood cell deformability
Bibliographic record
Abstract
The extraordinary deformability of red blood cells gives them the ability to repeatedly transit through the microvasculature of the human body. The loss of this capability is part of the pathology of a wide range of diseases including malaria, hemoglobinopathies, and micronutrient deficiencies. We report on a technique for multiplexed measurements of the pressure required to deform individual red blood cell through micrometer-scale constrictions. This measurement is performed by first infusing single red blood cells into a parallel array of ~1.7 μm funnel-shaped constrictions. Next, a saw-tooth pressure waveform is applied across the constrictions to squeeze each cell through its constriction. The threshold deformation pressure is then determined by relating the pressure-time data with the video of the deformation process. Our key innovation is a self-compensating fluidic network that ensures identical pressures are applied to each cell regardless of its position, as well as the presence of cells in neighboring constrictions. These characteristics ensure the consistency of the measurement process and robustness against blockages of the constrictions by rigid cells and debris. We evaluate this technique using in vitro cultures of RBCs infected with P. falciparum, the parasite that causes malaria, to demonstrate the ability to profile the deformability signature of a heterogeneous sample.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".