Using Nonuniform Electric Fields To Accelerate the Transport of Viruses to Surfaces from Media of Physiological Ionic Strength
Bibliographic record
Abstract
Nonuniform ac (alternating current) electric fields created by microelectrodes are investigated for their influence on the transport of the vesicular stomatitis virus (VSV) from aqueous suspensions of physiological ionic strength to surfaces on which the VSV is captured. Whereas passive diffusion did not lead to detectable levels of virus captured on a surface when using titers of VSV as high as 107 PFU/mL, nonuniform electric field-mediated transport led to the detection of 105 PFU/mL of virus in 2 min. An order-of-magnitude analysis of the time scales associated with virus transport to the microelectrodes inside media of physiological relevance indicates that electrothermal fluid flow (and the resulting viscous drag forces on the virus) rather than dielectrophoresis likely constitutes the major mechanism for virus transport far from the electrodes. The influence of dielectrophoresis was calculated to be confined to a region within a few micrometers of the electrodes and to lead to collection patterns of both virus and fluorescently labeled particles near the electrodes that were found to be in qualitative agreement with experiments. These observations and conclusions are discussed within a theoretical framework presented in the paper. The results presented in this work, when combined, suggest that ac electrokinetic phenomena can be used to expeditiously transport and capture viruses onto surfaces from solutions of high ionic strength, thus providing a potentially useful approach to addressing a bottleneck in the development of devices that allow for rapid sampling and detection of infectious biological agents.
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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) | 0.000 | 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".