Virtual microwells for three-dimensional cell culture on a digital microfluidic platform
Bibliographic record
Abstract
Three-dimensional hydrogel based cell culture has increased in prominence as a function of the in vivo-like phenotypes observed for cells cultured in this way. Unfortunately, cost and challenges in the physical manipulation of delicate hydrogel materials has impeded widespread use of these methods. Here we report the first digital microfluidic platform for the on-demand formation of hydrogel structures in virtual microwells. Moreover, we use the device to automate seeding of cells in hydrogels, exchange media at regular intervals, and perform fixing and staining of cells for on-device light and confocal microscopy. Further we apply this method for the recapitulation of higher-order tissue formation in a model of kidney epithelialization. These findings demonstrate the potential of digital microfluidics as a useful tool for a broad range of hydrogel based technologies.
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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 | 0.000 | 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 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".