Hydrogel discs for digital microfluidics
Bibliographic record
Abstract
Hydrogels are networks of hydrophilic polymer chains that are swollen with water, and they are useful for a wide range of applications because they provide stable niches for immobilizing proteins and cells. We report here the marriage of hydrogels with digital microfluidic devices. Until recently, digital microfluidics, a fluid handling technique in which discrete droplets are manipulated electromechanically on the surface of an array of electrodes, has been used only for homogeneous systems involving liquid reagents. Here, we demonstrate for the first time that the cylindrical hydrogel discs can be incorporated into digital microfluidic systems and that these discs can be systematically addressed by droplets of reagents. Droplet movement is observed to be unimpeded by interaction with the gel discs, and gel discs remain stationary when droplets pass through them. Analyte transport into gel discs is observed to be identical to diffusion in cases in which droplets are incubated with gels passively, but transport is enhanced when droplets are continually actuated through the gels. The system is useful for generating integrated enzymatic microreactors and for three-dimensional cell culture. This paper demonstrates a new combination of techniques for lab-on-a-chip systems which we propose will be useful for a wide range of applications.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".