Microfluidic Wound-Healing Assay for Comparative Study on Fluid Dynamic, Chemical and Mechanical Wounding on Microglia BV2 Migration
Bibliographic record
Abstract
Microglial cells, or brain immune cells, are highly dynamic and continuously migrate in pathophysiological conditions. Their adhesion, as a physical characteristic, plays a key role in migration. In this study, we presented a microfluidic chip combination of two assays: a microglial BV2 adhesion assay and a wound-healing migration assay. The chip could create the cell-free area (wound) under chemical stimuli with trypsin (chemical assay) and also mechanical stimuli with the PBS flow (mechanical assay). The microfluidic chip functioned as the cell adhesion assay during wounding, when the cell adhesion of microglia BV2 cells was characterized by the cell removal time under various shear stress ranges. The cell detachment pattern on the glass substrate was found under physiological conditions. After wounding, the chip operated as a migration assay; it was shown that cell migration in the cell-free area generated chemically with trypsin was highly improved compared to mechanical cell-free area creations with PBS flow and the scratch assay. Our findings indicated that the increase in inlet flow rate in the mechanical assay led to a reduced experiment time and mechanical force on the cells, which could improve cell migration. Furthermore, the study on the effect of the device geometry showed that the increased channel width had an inhibitory effect on cell migration. The bi-functional chip offers an opportunity for the development of new models for a better understanding of cellular adhesion and migration in in vitro microenvironments.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".