Development of a flow standard to enable highly reproducible measurements of deformability of stored red blood cells in a microfluidic device
Bibliographic record
Abstract
BACKGROUND: Great deformability allows red blood cells (RBCs) to flow through narrow capillaries in tissues. A number of microfluidic devices with capillary-like microchannels have been developed to monitor storage-related impairment of RBC deformability during blood banking operations. This proof-of-concept study describes a new method to standardize and improve reproducibility of the RBC deformability measurements using one of these devices. STUDY DESIGN AND METHODS: The rate of RBC flow through the microfluidic capillary network of the microvascular analyzer (MVA) device made of polydimethylsiloxane was measured to assess RBC deformability. A suspension of microbeads in a solution of glycerol in phosphate-buffered saline was developed to be used as an internal flow rate reference alongside RBC samples in the same device. RBC deformability and other in vitro quality markers were assessed weekly in six leukoreduced RBC concentrates (RCCs) dispersed in saline-adenine-glucose-mannitol additive solution and stored over 42 days at 4°C. RESULTS: The use of flow reference reduced device-to-device measurement variability from 10% to 2%. Repeated-measure analysis using the generalized estimating equation (GEE) method showed a significant monotonic decrease in relative RBC flow rate with storage from Week 0. By the end of storage, relative RBC flow rate decreased by 22 ± 6% on average. CONCLUSIONS: The suspension of microbeads was successfully used as a flow reference to increase reproducibility of RBC deformability measurements using the MVA. Deformability results suggest an early and late aging phase for stored RCCs, with significant decreases between successive weeks suggesting a highly sensitive measurement method.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".