A digital microfluidic method for multiplexed cell-based apoptosis assays
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Bibliographic record
Abstract
Digital microfluidics (DMF), a fluid-handling technique in which picolitre-microlitre droplets are manipulated electrostatically on an array of electrodes, has recently become popular for applications in chemistry and biology. DMF devices are reconfigurable, have no moving parts, and are compatible with conventional high-throughput screening infrastructure (e.g., multiwell plate readers). For these and other reasons, digital microfluidics has been touted as being a potentially useful new tool for applications in multiplexed screening. Here, we introduce the first digital microfluidic platform used to implement parallel-scale cell-based assays. A fluorogenic apoptosis assay for caspase-3 activity was chosen as a model system because of the popularity of apoptosis as a target for anti-cancer drug discovery research. Dose-response profiles of caspase-3 activity as a function of staurosporine concentration were generated using both the digital microfluidic method and conventional techniques (i.e., pipetting, aspiration, and 96-well plates.) As expected, the digital microfluidic method had a 33-fold reduction in reagent consumption relative to the conventional technique. Although both types of methods used the same detector (a benchtop multiwell plate reader), the data generated by the digital microfluidic method had lower detection limits and greater dynamic range because apoptotic cells were much less likely to de-laminate when exposed to droplet manipulation by DMF relative to pipetting/aspiration in multiwell plates. We propose that the techniques described here represent an important milestone in the development of digital microfluidics as a useful tool for parallel cell-based screening and other applications.
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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 it