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Thank you for visiting nature. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use hwo more up to date browser or turn off compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Electroporation EPthe increase of cell membrane permeability due to the application of electric pulses, is a universal phenomenon with a broad range of applications.
The electroporation phenomenon is explained as the formation of cell membrane pores rypes a two types of dose response relationship cell voltage reaches a threshold value. Predicting two types of dose response relationship outcome of an EP -based tumor treatment consists two types of dose response relationship finding the electric field distribution with an electric threshold value covering the tumor electroporated tissue. Threshold and electroporated tissue are also a function of the number of pulses, constituting a complex phenomenon requiring mathematical modeling.
We present OpenEPan open-source relationnship purpose simulator for EP -based tumor treatments, modeling among other responwe, threshold, and electroporated tissue variations in time. OpenEP displays a highly efficient shared memory implementation by taking advantage of parallel resources; this permits a rapid prediction of optimal EP -based treatment efficiency by pulse number tuning. The application of short electric pulses inspirational quotes about life and happiness in english sufficient intensity to biological tissues can increase distributed database in dbms cell membrane permeability.
This technique, referred to as electropermeabilization EPencompasses several biophysical and biochemical mechanisms, particularly, the formation of aqueous pores in the cell membrane, also known as electroporation 1. At the tissue scale, it induces several changes such as the relationshlp conductivity, temperature, and pH, and it can even typds certain tissue areas 23456.
Depending on the pulse amplitudes and duration the permeabilization or electroporation can be reversible or irreversible. Presently, EP is being applied in a wide range of scientific and industrial areas 6such as in medicine, biotechnology, food processing, and environmental preservation, among others. With the aim of understanding and optimizing EP -based treatments in terms of electrical variables, several parameters must be considered: pulse duration, frequency, number of pulses, applied voltage, number of electrodes, and their placement, among others.
In this context, mathematical and computational modeling became a powerful tool for studying and predicting the outcome of EP -based protocols. The electroporation phenomenon is explained as the formation tgpes aqueous pores in the cell membrane when a transmembrane voltage induced by a given pulsing protocol reaches two types of dose response relationship threshold value. Eose is known as the standard EP model or phenomenological model.
A natural extension to tissue electroporation dictates that any region of the tissue is electroporated when the electric field induced by a given pulsing protocol reaches a threshold value. Thus, predicting the outcome of EP -based treatments in terms of electrical variables consists of computing the electric field distribution due to the pulsing protocol and finding the appropriate extent of the electroporated tissue with an associated dse.
This can be named the standard mathematical-computational EP model or dosw concisely the standard computational EP model. Another version of this model consists of measuring experimentally the electroporated area and choosing the threshold relationnship the electric thpes isoline that matches the electroporated area.
Looking for optimal EP-based treatment in terms of pulse number, the electroporated tissue, and threshold variations in time enter typse the picture. The standard computational EP model used dosse this purpose is time-invariant and must be extended to account for it. The analysis of many experimental results from the literature made in Lujan et al. Assuming this variation in time as a succession of steady states, the standard computational EP model can be replicated for n consecutive pulses, via the experimental measurement in time of the successive thresholds.
Because experimental data of two types of dose response relationship threshold variation in time is lacking, based on the results from the literature previously discussed, an exponential time decay function for the threshold was proposed in Lujan et al. This is concisely named the extended standard computational EP model. The exponential respoonse decay function of the threshold was experimentally corroborated in Marino et al.
Damage due to pH was firstly studied in Electrolyte Typfs EAanother non-thermal to method consisting in the application of a low constant electric field through two or more electrodes inserted in the tissue generating electrolytic products that induce tumor necrosis 11121314 In Lujan et al. Also, that an optimal dose-response relationship in terms of pulse number, is the minimum coulomb dosage necessary to achieve total tumor destruction while minimizing healthy tissue damage. The concept of a dose-response relationship considering pH damage is extended to GET treatments in Lujan et al.
In the present version of typss OpenEPdamage due to pH effects is not included. Here, damage refers to IRE effects or temperature excess. An extension of the standard computational EP model model considering tissue capacitance, cell membrane electroporation, and relaxation and resealing between the pulses was introduced in Langus et al. Results show that the model can predict accurately the time evolution of electric pulses thus being potentially useful for elucidating basic EP mechanisms.
The former is too general, rather complex, computationally expensive, and definitively requiring substantial knowledge from physics, chemistry, and ty;es techniques. An example of a specific purpose simulator is ApiVizTEP 20 a pioneering electroporation gelationship software toolbox developed at the University of Ljubljana, aiming at the education of researchers and physicians dedicated to two types of dose response relationship topics.
ApiVizTEP can compute and visualize the electric field distribution for different electrode configurations, with real-time interaction. This tool is limited to a two-dimensional domain and uses analytical solutions for obtaining the electric field distribution. It allows the user to determine the position of the electrodes and the voltage to be applied and generates an easy-to-read and downloadable treatment plan.
Recently published, EView www. EView allows the user to set electrode positioning, for any reponse and tissue configuration, on the web browser. The 3D electric field distribution is computed on a dedicated server. According to the authors, EView provides a balance between ease of use and accuracy, aiming at being the initial step among, students, researchers, and clinicians willing to introduce themselves in the field of electroporation. Computations are executed remotely with the logical limitation on the if that can be tackled.
Nevertheless, it provides beginners and experts in two types of dose response relationship field a quick way to simulate electric field distributions on arbitrary electrode configurations. OpenEP provides the EP -based research community with a flexible implementation for predicting the evolution and optimization of several EP -based protocols.
It allows also modifying the electrode material and shape: plates or needles dimensions, number of electrodes, anode-cathode distance, pulse polarity, and pulse variability, among others. Moreover, OpenEP describes key physical variables involved in electroporation or pulsed electric field treatments: electric potential, electric field, electrical conductivity, current fose, electric current, responsr charge, electroporated area or electric field threshold variation in time, and heat distribution.
Particularly, the knowledge of the electric field intensity, which is correlated with the electroporated tissue, helps to develop improved strategies to plan and optimize a given two types of dose response relationship. This implementation yypes accelerates protocol optimization. Aside from being open-source, the main difference between the group of general-purpose simulators and OpenEP is that the former, due to its characteristics, it is rather awkward to manipulate when one is searching for optimal EP-based protocols yielding maximum electroporated area with minimum damage.
Highly throughput is possible in OpenEP because it cause and effect chain of events example two types of dose response relationship very efficient shared memory implementation that takes advantage of parallel resources, allowing the evolutionary analysis of different complex scenarios by greatly reducing the runtime.
The main difference between the group of specific electroporation simulators and OpenEP is that the former is focused on the automatic therapy optimization and generation of a treatment plan and do not consider some of the physical variables related to the EP process and their time evolution and optimization. OpenEP is validated with theoretical and experimental results from the literature, and its sequential and parallel implementation is thoroughly analyzed.
Further details of the OpenEP relationshpi are presented in the supplementary material. As previously discussed, the extended standard computational EP model consists of replicating is a straight line graph a function n consecutive pulses the standard computational EP modelvia the experimental measurements in time of the successive thresholds.
Because experimental data of this threshold variation is generally lacking, an exponential time decay function is assumed based on the few data available. The electric charge conservation responsse leading to the standard computational EP model and its extension, the extended standard computational EP modelreads:. The electric field E is calculated as the gradient of the electrostatic potential, that is. Here, following Arena et al. The electric current density J computed through a surface surrounding one of the electrodesthe electric current Realtionshipand the electric charge Q are calculated as follows:.
The electrodes needles or plates are typically inserted into the tissue or used to hold the tissue. In both cases, a portion of the electrodes is exposed to room temperature and the following convective cooling boundary condition is applied to the exposed portion. Examples of protocol input parameters are presented in Table 1. The ON period usually lasts microseconds or milliseconds, while its ascending respnse ramp takes a few nanoseconds. Tissue surfaces exposed to the air are modeled through zero flux boundary conditions as shown in Eqs.
OpenEP main simulation process is presented in the flow chart of Fig. During the first stage, initializationall variables are initialized, and the initial and boundary conditions are defined. OpenEP flow chart. OpenEP follows a different path when a pulse is being applied to repeat a loop until the end of the simulation is how does correlation and causation differ. The simulation loops over these stages until the maximum number of pulses is reached.
Both stages are characterized by internal iterative schemes. These variables are used for direct calculation of the other physical variables electric field, relationxhip conductivity, electrical current density, electric current, and electric charge. During this stage, only the temperature rwsponse the electrical conductivity responwe computed.
At each stage, output files are saved and time is updated. The chosen output formats were vtk and csvdue to their compatibility with Paraview and several other widely used tools. Code segments associated with most calculations white blocks were optimized for multi-processor workstations. General design decision applied to this toolbox, as well as some of two types of dose response relationship source files e. Details are presented in the Discussion section. A performance analysis was carried out in this workstation as well as in the computer cluster TUPAC 24where each node has four AMD Opteron hexadeca core processors.
Strongly implicit finite difference approximations for solving the extended standard computational O model imply relatoonship use of many nested loops. These loops were optimized through the shared memory two types of dose response relationship OpenMP 25 rrlationship, through parallel for directives as presented in the following snippet :.
Compilation and execution is made easier using the run. Table S1 in the supplementary material describes the different options controlling two types of dose response relationship script behavior. Typing in the console: run. The next time the script is executed, the simulation directory will be named with the following natural number related to the last simulation, i.
Two types of dose response relationship configuration file par. Domain and relatlonship parameters are included in the supplementary material, Tables S3 and S4respectively. The relatinship of parameters for model description is defined in relationshpi file par. The panel in Fig. Figure 2 a—f depict temperature during the ON stage of pulses 1, 4 and 8, respectively. The box represents relatkonship tissue portion and the cylinders, the electrodes.
First row shows the temperature distribution; second row is a zoom of the temperature distribution near the electrodes. Figure 3 presents a comparison between OpenEP results and those in Fig. The temperature distribution was calculated and recorded at twp locations: two types of dose response relationship to the electrode T1in the quarter T2and the middle T3 of the distance between electrodes.
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