A simple, low cost and reusable microfluidic gradient strategy and its application in modeling cancer invasion
Bibliographic record
Abstract
Microfluidic chemical gradient generators enable precise spatiotemporal control of chemotactic signals to study cellular behavior with high resolution and reliability. However, time and cost consuming preparation steps for cell adhesion in microchannels as well as requirement of pumping facilities usually complicate the application of the microfluidic assays. Here, we introduce a simple strategy for preparation of a reusable and stand-alone microfluidic gradient generator to study cellular behavior. Polydimethylsiloxane (PDMS) is directly mounted on the commercial polystyrene-based cell culture surfaces by manipulating the PDMS curing time to optimize bonding strength. The stand-alone strategy not only offers pumpless application of this microfluidic device but also ensures minimal fluidic pressure and consequently a leakage-free system. Elimination of any surface treatment or coating significantly facilitates the preparation of the microfluidic assay and offers a detachable PDMS microchip which can be reused following to a simple cleaning and sterilization step. The chemotactic signal in our microchip is further characterized using numerical and experimental evaluations and it is demonstrated that the device can generate both linear and polynomial signals. Finally, the feasibility of the strategy in deciphering cellular behavior is demonstrated by exploring cancer cell migration and invasion in response to chemical stimuli. The introduced strategy can significantly decrease the complexity of the microfluidic chemotaxis assays and increase their throughput for various cellular and molecular studies.
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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 | 0.001 |
| 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 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".