Numerical Simulation of Separation of Circulating Tumor Cells from Blood Stream in Deterministic Lateral Displacement (DLD) Microfluidic Channel
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Bibliographic record
Abstract
Abstract Deterministic Lateral Displacement (DLD) microfluidic devices provide a reliable label-free separation method for detection of circulating tumor cells (CTCs) in blood samples based on their biophysical properties. In this paper, we proposed an effective design of the DLD microfluidic device for the CTC separation in the blood stream. A typical DLD array is designed and numerical simulations are performed to separate the CTC and leukocyte (white blood cells) in different fluid flow conditions. Fluid-Solid Interaction method is used to investigate the behaviour of these deformable cells in fluid flow. In this study, the effects of critical parameters affecting cell separation in the DLD microfluidic devices ( e.g. flow condition, cell deformability, and stress) have been investigated. The obtained results show that unlike leukocytes, the CTC’s motion is independent of the flow condition and is laterally displaced even in higher Reynolds number. Larger cells (CTCs) cannot intercept the low-velocity fluid near the wall of the posts; thus, they move faster and become separated from leukocytes. To reduce the cellular stress during separation process, which causes increase of cell viability and more effective design of microfluidic device, the results obtained here may be used as a significant design parameter for the DLD fabrication.
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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) | 0.000 | 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) | 0.000 | 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 it