不可逆电穿孔
细胞内
电穿孔
线粒体
细胞生物学
生物物理学
化学
体内
细胞器
癌细胞
膜电位
癌症研究
A549电池
肺癌
线粒体内膜
癌症
生物
细胞膜
烧蚀
细胞
线粒体融合
内吞作用
材料科学
细胞室
生物医学工程
病理
医学
膜
转染
作者
Hong Bae Kim,Jin Young Youm,Joon-Mo Yang,Sung Bo Sim
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2026-04-22
卷期号:21 (4): e0346472-e0346472
标识
DOI:10.1371/journal.pone.0346472
摘要
This study aimed to optimize irreversible electroporation (IRE) parameters to enhance intracellular injury, specifically targeting nuclear and mitochondrial structures that are insufficiently affected by conventional protocols. To address limitations of standard 1000 ~ 2500 V/cm clinical settings, we experimentally and computationally evaluated both low- and high-electric-field conditions and identified pulse parameters capable of safely achieving electric field strengths exceeding 4,000 V/cm, values that remain below the predicted arcing threshold for our electrode configuration while permitting effective intracellular electroporation. In vitro studies using A549 lung cancer cells demonstrated that high-field IRE markedly intensified oxidative stress, resulting in a 30-fold increase in hydrogen peroxide production and pronounced disruption of mitochondrial membrane potential. Transmission electron microscopy further confirmed severe ultrastructural injury, including plasma membrane rupture, nuclear membrane deformation, and complete loss of mitochondrial cristae, culminating in irreversible cell death. In vivo experiments corroborated these findings: high-field IRE produced extensive and uniform tumor ablation, whereas conventional lower field strengths generated only localized and partial damage. These results indicate that elevating electric-field intensity in IRE protocols can overcome the inherent limitations of traditional approaches by reliably inducing intracellular organelle damage, suppressing cellular repair pathways, and enhancing overall ablation completeness. Further studies are warranted to evaluate long-term safety and therapeutic durability of high-field IRE in vivo.
科研通智能强力驱动
Strongly Powered by AbleSci AI