A More Biomimetic Cell Migration Assay with High Reliability and Its Applications
Bibliographic record
Abstract
Cell migration refers to the directional movement of cells to the surrounding cell-free zone in response to chemical and mechanical stimuli. A cell migration assay is an essential device for studying pharmaceutical and medical problems. In this paper, we present a novel approach to a cell migration assay on a chip with two merits, namely (i) simultaneous creation of many cell samples on the same condition and (ii) cells migrating while being stressed in a fluidic environment. The first merit has addressed the problem of poor reproducibility in experimental studies for medical problems such as wound healing, and the second merit has made the cell migration device, which is an in vitro environment, more biomimetic. The two merits are attributed to a novel mechanical method to simultaneously create many cell-free zones and to the design of a microfluidic process to create shear stress in cells uniformly. Two applications were studied on our device to explore its effectiveness. The first application is regarding the combination chemotherapy of cisplatin and doxorubicin (Adriamycin) on cervical cancer cells (HeLa). The second application is regarding inhibiting the migration of endothelial cells (HUVEC) in the process of anti-angiogenesis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".