A Silicon-Based Porous Thin Membrane as a Cancer Cell Transmigration Assay
Bibliographic record
Abstract
This paper presents a novel microfabricated Boyden chamber in silicon with well-defined pore sizes and controlled membrane thickness for cell migration analysis. The chip-based chamber is fabricated employing lithography and deep reactive ion etching techniques on a double-sided polished silicon wafer. The device contains micro-pores with a silicon oxide layer at the top and a deep microfluidic channel at the bottom, which is anodically-bonded to a glass wafer for sealing and facilitating the imaging and chemoattractant feeding. The applicability of the chip has been demonstrated through the distinct migratory behaviors of highly metastatic breast cancer cells, MDA-MB-231, through pores with 8 μm in diameter, 50 μm in spacing, and 30 μm in thickness. Employing the above technique, the membrane thickness variation among different chips was below 10%. Utilizing this micro-Boyden chamber device, we have shown that MDA-MB-231 cells migrated distinctively in higher rate than the cells which had gone through sphingosine kinase inhibitor drug treatment or no chemoattractant feeding over a course of 12 hours. Furthermore, we validated the performance of the micro-Boyden chamber by quantifying the migration rate of the cancer cells under different chemoattractant gradient profiles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 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".