Differential electronic detector to monitor apoptosis using dielectrophoresis-induced translation of flowing cells (dielectrophoresis cytometry)
Bibliographic record
Abstract
The instrument described here is an all-electronic dielectrophoresis (DEP) cytometer sensitive to changes in polarizability of single cells. The important novel feature of this work is the differential electrode array that allows independent detection and actuation of single cells within a short section ([Formula: see text]) of the microfluidic channel. DEP actuation modifies the altitude of the cells flowing between two altitude detection sites in proportion to cell polarizability; changes in altitude smaller than 0.25 μm can be detected electronically. Analysis of individual experimental signatures allows us to make a simple connection between the Clausius-Mossotti factor (CMF) and the amount of vertical cell deflection during actuation. This results in an all-electronic, label-free differential detector that monitors changes in physiological properties of the living cells and can be fully automated and miniaturized in order to be used in various online and offline probes and point-of-care medical applications. High sensitivity of the DEP cytometer facilitates observations of delicate changes in cell polarization that occur at the onset of apoptosis. We illustrate the application of this concept on a population of Chinese hamster ovary (CHO) cells that were followed in their rapid transition from a healthy viable to an early apoptotic state. DEP cytometer viability estimates closely match an Annexin V assay (an early apoptosis marker) on the same population of cells.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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".