The effect of dielectrophoresis on living cells: crossover frequencies and deregulation in gene expression
Bibliographic record
Abstract
This article documents the effect of dielectrophoresis on living cells. Given the longer duration procedures performed on microfluidic platforms, the influence of electric fields of high intensity may be of interest in manipulations other than dielectrophoresis. The crossover frequencies of several cell lines were experimentally determined using a microfluidic device. The crossover frequencies are investigated at different medium conductivities for red blood cells, white blood cells-Jurkat, 92.1 and OCM melanoma, and MDA-MB-231 breast cancer cell lines. The effect of dielectrophoresis on the cells at the gene level was also investigated by studying the alteration in gene expressions using microarray analysis. The alterations in genes due to the manipulation of cells at 10 kHz and 100 kHz with a sinusoidal 10 V peak signal for 60 minutes are explored. The two frequencies correspond to negative and positive dielectrophoresis, respectively. The cell line MDA-MB-231 is used as a model for studying the genes in this work. The dielectrophoresis was found to alter genes related to apoptosis, rRNA transcription, cellular respiration, energy production, cellular transcriptional activity, and other cellular functions.
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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 | 0.001 |
| 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) | 0.001 | 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".