Electrical Lysis: Dynamics Revisited and Advances in On-chip Operation
Bibliographic record
Abstract
Electrical lysis (EL) is the process of breaking the cell membrane to expose the internal contents under an applied high electric field. Lysis is an important phenomenon for cellular analysis, medical treatment, and biofouling control. This paper aims to review, summarize, and analyze recent advancements on EL. Major databases including PubMed, Ei Engineering Village, IEEE Xplore, and Scholars Portal were searched using relevant keywords. More than 50 articles published in English since 1997 are cited in this article. EL has several key advantages compared to other lysis techniques such as chemical, mechanical, sonication, or laser, including rapid speed of operation, ability to control, miniaturization, low cost, and low power requirement. A variety of cell types have been investigated for including protoplasts, E. coli, yeasts, blood cells, and cancer cells. EL has been developed and applied for decontamination, cytology, genetics, single-cell analysis, cancer treatment, and other applications. On-chip EL is a promising technology for multiplexed automated implementation of cell-sample preparation and processing with micro- or nanoliter reagents.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".