An In Vitro Experimental Study of the Pulse Delivery Method in Irreversible Electroporation
Bibliographic record
Abstract
The purpose of this study was to investigate the feasibility of generating larger ablation volumes using the pulse delivery method in irreversible electroporation (IRE) using a potato model. Ten types of pulse timing schemes and two pulse repetition rates (1 pulse per 200 ms and 1 pulse per 550 ms) were proposed in the study. Twenty in vitro experiments with five samples each were performed to check the effects on the ablation volumes for the ten pulse timing schemes and two pulse repetition rates. At the two pulse repetition rates (1 pulse per 200 ms and 1 pulse per 550 ms), the largest ablation volumes achieved were 1634.1 mm3± 122.6 and 1828.4 mm3±160.9, respectively. Compared with the baseline approach (no pulse delays), the ablation volume was increased approximately by 62.8% and 22.6% at the repetition rates of 1 pulse per 200 ms and 1 pulse per 550 ms, respectively, using the pulse timing approach (with pulse delays). With the pulse timing approach, the ablation volumes generated at the lower pulse repetition rate were significantly larger than those generated at the higher pulse repetition rate (P < 0.001). For the experiments with one pulse train (baseline approach), the current was 5.2 A±0.4. For the experiments with two pulse trains, the currents were 6.4 A±0.9 and 6.8 A±0.9, respectively (P = 0.191). For the experiments with three pulse trains, the currents were 6.6 A±0.6, 6.9 A±0.6, and 6.5 A±0.6, respectively (P = 0.216). For the experiments with five pulse trains, the currents were 6.6 A±0.9, 6.9 A±0.9, 6.5 A±1.0, 6.5 A±1.0, and 5.7 A±1.2, respectively (P = 0.09). This study concluded that: (1) compared with the baseline approach used clinically, the pulse timing approach is able to increase the volume of ablation; but, the pulse timing scheme with the best performance might be various with the tissue type; (2) the pulse timing approach is still effective in achieving larger ablation volumes when the pulse repetition rate changes; but, the best pulse timing scheme might be different with the pulse repletion rate; (3) the current in the base line approach was significantly smaller than that in the pulse timing approach.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".