Irreversible Electroporation Ablation: Creation of Large-Volume Ablation Zones in in Vivo Porcine Liver with Four-Electrode Arrays

Radiology ◽  
2014 ◽  
Vol 270 (2) ◽  
pp. 416-424 ◽  
Author(s):  
Liat Appelbaum ◽  
Eliel Ben-David ◽  
Mohammad Faroja ◽  
Yizhak Nissenbaum ◽  
Jacob Sosna ◽  
...  
Author(s):  
Paulo A. Garcia ◽  
Christopher B. Arena ◽  
Robert E. Neal ◽  
S. Nahum Goldberg ◽  
Eliel Ben-David ◽  
...  

Irreversible electroporation (IRE) is a new minimally invasive non-thermal focal ablation technique that has been used for the treatment of spontaneous tumors in canine and human patients [1, 2]. The procedure typically involves placing two electrodes into or around a tumor and delivering a series of low energy electric pulses to kill tumor tissue with sub-millimeter resolution. The pulses generate an electric field that alters the resting transmembrane potential (TMP) of the cells. Depending on the magnitude of the induced TMP, the electric pulses can have no effect, reversibly increase membrane permeability, or cause cell death in the case of IRE.


2012 ◽  
Vol 198 (1) ◽  
pp. W62-W68 ◽  
Author(s):  
Eliel Ben-David ◽  
Liat Appelbaum ◽  
Jacob Sosna ◽  
Isaac Nissenbaum ◽  
S. Nahum Goldberg

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.


2021 ◽  
Vol 129 (5) ◽  
pp. 053301
Author(s):  
Eric Freund ◽  
Lea Miebach ◽  
Ramona Clemen ◽  
Michael Schmidt ◽  
Amanda Heidecke ◽  
...  

2015 ◽  
Vol 26 (2) ◽  
pp. 279-287.e3 ◽  
Author(s):  
Katsutoshi Sugimoto ◽  
Fuminori Moriyasu ◽  
Yoshiyuki Kobayashi ◽  
Kazuhiko Kasuya ◽  
Yuichi Nagakawa ◽  
...  

Antioxidants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 27
Author(s):  
María López-Pedrouso ◽  
José M. Lorenzo ◽  
Paula Borrajo ◽  
Daniel Franco

The search for antioxidant peptides as health-promoting agents is of great scientific interest for their biotechnological applications. Thus, the main goal of this study was to identify antioxidant peptides from pork liver using alcalase, bromelain, flavourzyme, and papain enzymes. All liver hydrolysates proved to be of adequate quality regarding the ratio EAA/NEAA, particularly flavourzyme hydrolysates. The peptidomic profiles were significantly different for each enzyme and their characterizations were performed, resulting in forty-four differentially abundant peptides among the four treatments. Porcine liver hydrolysates from alcalase and bromelain are demonstrated to have the most antioxidant capacity. On the other hand, hydrophobic amino acid residues (serine, threonine, histidine and aspartic acid) might be reducing the hydrolysates antioxidant capacity. Seventeen peptides from collagen, albumin, globin domain-containing protein, cytochrome β, fructose-bisphosphate aldolase, dihydropyrimidinase, argininosuccinate synthase, and ATP synthase seem to be antioxidant. Further studies are necessary to isolate these peptides and test them in in vivo experiments.


BMC Cancer ◽  
2015 ◽  
Vol 15 (1) ◽  
Author(s):  
Peter GK Wagstaff ◽  
Daniel M de Bruin ◽  
Patricia J Zondervan ◽  
C Dilara Savci Heijink ◽  
Marc RW Engelbrecht ◽  
...  

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