A microwave interferometric system for simultaneous actuation and detection of single biological cells
Bibliographic record
Abstract
In biomedical applications ranging from the study of pathogen invasion to drug efficacy assays, there is a growing need to develop minimally invasive techniques for single-cell analysis. This has inspired researchers to develop optical, electrical, microelectromechanical and microfluidic devices for exploring phenomena at the single-cell level. In this work, we demonstrate an electrical approach for single-cell analysis wherein a 1.6 GHz microwave interferometer detects the capacitance changes (DeltaC) produced by single cells flowing past a coplanar interdigitated electrode pair. The experimental and simulated capacitance changes generated by yeast cells are in close agreement. By using the capacitance changes of uniform polystyrene spheres (diameter = 5.7 microm) for calibration purposes, we demonstrate a 0.65 aF sensitivity in a 10 ms response time. Using an RC circuit, a low frequency sinusoidal potential is simultaneously superimposed on the electrode pair to generate a dielectrophoretic force that translates cells. Specifically, when yeast cells suspended in a solution of 90 ppm NaCl in deionized water are exposed to 10 kHz and 3 MHz potentials (ranging from 1-3 V(pp)), they experience negative and positive dielectrophoresis, respectively. The corresponding changes in cell elevation above the interdigitated electrodes are detected using the asymmetry of the capacitance signature produced by the cell. Cell elevation changes can be detected in less than 80 ms. The minimum detectable change in elevation is estimated to be 0.22 microm. This approach will have applications in rapid single-cell dielectrophoretic analysis, and may also prove useful in conjunction with impedance spectroscopy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".