Monitoring Motility, Spreading, and Mortality of Adherent Insect Cells Using an Impedance Sensor
Bibliographic record
Abstract
An emerging sensor technology referred to as electric cell-substrate impedance sensing (ECIS) has been extended for monitoring the behavior of insect cells including attachment, motility, and mortality. In ECIS, adherent cells were cultured on an array of eight small gold electrodes deposited on the bottom of tissue culture wells and immersed in a culture medium. Upon the attachment and spreading of cells on the gold electrode, the impedance increased because the cells acted as insulating particles to restrict the current flow. Experimental data revealed that insect cells interacted differently with various proteins used to precoat the gold electrode with concanavalin A as the best promoter to accelerate the rate of cell attachment. After the cells were fully spread, the measured impedance continued to fluctuate to reflect the constant motion and metabolic activity of the cells. As the cell behavior was sensitive to external chemicals, the applicability of ECIS for inhibition assays was demonstrated with HgCl2, trinitrotoluene, trinitrobenzene (TNB), and 2-amino-4,6-dinitrotoluene as model systems. Unlike conventional assays, the quantitative data obtained in this study are taken in real time and in a continuous fashion to depict cell motility and mortality.
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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 | 0.000 | 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 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".