An <i>in vivo</i> study of a custom-made high-frequency irreversible electroporation generator on different tissues for clinically relevant ablation zones
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: for a custom-made high-frequency irreversible electroporation (H-FIRE) generator. MATERIALS AND METHODS: = 3) for the performance of the designed H-FIRE device in both liver and kidney tissues. The ablation zone was determined by using histological analysis 72 h after treatment. The extent of muscle contractions and temperature change during the application of pulse energy were measured by a commercial accelerometer attached to animals and fiber optic temperature probe inserted into organs with IRE electrodes, respectively. RESULTS: All H-FIRE protocols were able to generate visible ablation zones without muscle contractions, for both liver and kidney tissues. The area of ablation zone generated in H-FIRE pulse protocols (e.g., 0.3-1 μs, 2000 V, and 90-195 bursts) appears similar to that of IRE protocol (100 μs, 1000 V, and 90 pulses) in both liver and kidney tissues. No significant temperature increase was noticed except for the protocol with the highest pulse energy (e.g., 1 μs, 2000 V, and 180 bursts). CONCLUSION: Our work serves to complement the current H-FIRE pulse waveforms, which can be optimized to significantly improve the quality of ablation zone in terms of precision for liver and kidney tumors in clinical setting.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 it