Multiplexed actuation using ultra dielectrophoresis for proteomics applications: a comprehensive electrical and electrothermal design methodology
Bibliographic record
Abstract
In this work, we present a methodological approach to analyze an enhanced dielectrophoresis (DEP) system from both a circuit analysis and electrothermal view points. In our developed model, we have taken into account various phenomena and constraints such as voltage degradation (due to the presence of the protecting oxide layer), oxide breakdown, instrumentation limitations, and thermal effects. The results from this analysis are applicable generally to a wide variety of geometries and high voltage microsystems. Here, these design guidelines were applied to develop a robust electronic actuation system to perform a multiplexed bead-based protein assay. To carry out the multiplexed functionality, along a single microfluidic channel, an array of proteins is patterned, where each element is targeting a specific secondary protein coated on micron-sized beads in the subsequently introduced sample solution. Below each element of the array, we have a pair of addressable interdigitated electrodes. By selectively applying voltage at the terminals of each interdigitated electrode pair, the enhanced DEP, or equivalently 'ultra'-DEP (uDEP) force detaches protein-bound beads from each element of the array, one by one, without disturbing the bound beads in the neighboring regions. The detached beads can be quantified optically or electrically downstream. For proof of concept, we illustrated 16-plex actuation capability of our device to elute micron-sized beads that are bound to the surface through anti-IgG and IgG interaction which is on the same order of magnitude in strength as typical antibody-antigen interactions. In addition to its application in multiplexed protein analysis, our platform can be potentially utilized to statistically characterize the strength profile of biological bonds, since the multiplexed format allows for high throughput force spectroscopy using the array of uDEP devices, under the same buffer and assay preparation conditions.
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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".