An electroporation cytometry system for long-term, live cell cycle analysis
Bibliographic record
Abstract
Electric fields are used in biology to address a broad range of questions and through a variety of techniques, including electroporation, gene electrotransfer (GET), electrostimulation (ES), and electrochemotherapy. Each of these modalities requires specific conditions and has drastically different target outcomes on the cell. ES has demonstrated that non-pore forming electric fields alter cell cycle progression. However, pore forming electric fields such as with GET have not been as widely explored despite major clinical advancements. Additionally, the real-time visual analysis of electrical field effects on mammalian cell culture is currently lacking among most commercial systems. To facilitate investigations into these research areas, an electroporation cytometry system was developed including a custom chamber compatible with live cell imaging and exponential decay pulse generator for live cell analysis. The functionality of the system was demonstrated using a recombinant cell line using U-2 OS cells and FUCCI(CA)5 cell cycle reporter. The exposure of the cells to a 180 V pulse in both unsynchronized and synchronized populations revealed an effect on the cell cycle.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".