Chemical Enhancement of Irreversible Electroporation: A Review and Future Suggestions
Bibliographic record
Abstract
Irreversible electroporation has raised great interest in the past decade as a means of destroying cancers in a way that does not involve heat. Irreversible electroporation is a novel ablation technology that uses short high-voltage electrical pulses to enhance the permeability of tumor cell membranes and generate irreversible nano-sized structural defects or pores, thus leading to cell death. Irreversible electroporation has many advantages over thermal therapies due to its nonthermal mechanism: (1) reduced risk of injury to surrounding organs and (2) no "heat-sink" effect due to nearby blood vessels. However, so far, it has been difficult for irreversible electroporation to completely ablate large tumors (eg, >3 cm in diameter). In order to overcome this problem, many preclinical and clinical studies have been performed to improve the efficacy of IRE in the treatment of large size of tumors through a chemical perspective. Due to the distribution of electric field, irreversible electroporation region, reversible electroporation region, and intact region can be found in the treatment of irreversible electroporation. Thus, 2 types of chemical enhancements of irreversible electroporation were discussed in the article, such as the reversible electroporation region enhanced and the irreversible electroporation region enhanced. Specifically, the state-of-the-art results regarding the following approaches that have the potential to be used in the enhancement of irreversible electroporation were systematically reviewed in the article, including (1) combination with cytotoxic drugs, (2) calcium electroporation, (3) modification of cell membrane, and (4) modification of the tumor cell microenvironment. In the end, we concluded with 4 issues that should be addressed in the future for improving irreversible electroporation further in a chemical way.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".