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Tx, TqNet and Ttriang Values

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Tx, TqNet and Ttriang Values

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dc.contributor.author Llopis Lorente, Jordi es_ES
dc.contributor.author Gomis-Tena Dolz, Julio es_ES
dc.contributor.author Cano García, Jordi es_ES
dc.contributor.author Romero Pérez, Lucia es_ES
dc.contributor.author Saiz Rodríguez, Francisco Javier es_ES
dc.contributor.author Trénor Gomis, Beatriz Ana es_ES
dc.date.accessioned 2020-02-14T10:17:38Z
dc.date.available 2020-02-14T10:17:38Z
dc.date.issued 2020
dc.identifier.uri http://hdl.handle.net/10251/136919
dc.description Every sheet in described files contains a table of numbers (doubles), resulting from the transformation of a three-dimensional matrix. To do so, the first three columns of each table contain the Coordinates x, y and z or z' of the original matrix respectively (no units). They range from -3 to 1.5. Coordinates were calculated as the logarithm of the ratio of a drug concentration (C) over the concentration that is required to inhibit a 50% of a given ion channel current (Half inhibitory concentration or IC50). They represent the block effect of such drug on four main currents which control the Action Potential shape and duration, namely, the rapid component of the potassium delayed rectifier current (IKr), the slow component of the potassium delayed rectifier current (IKs), the late sodium current (INaL) and the calcium type L current (ICaL). The following formulae can be used to deduce mentioned Coordinates: x = log_10(C/(IC_50 (I_Kr))) ; y = log_10(C/(IC_50 (I_CaL ) )); z = log_10(C/(IC_50 (I_CaL)); and z' = log_10(C/(IC_50 (I_NaL)). These are indeed part of the Hill equation (Hill coefficient set to 1), where G is the channel’s resulting conductance and G0 is the channel’s control conductance: G_[x || y || z || z'] = G_0·1/(1+C/(IC_(50, [x || y || z || z'] ) )) = G_0·1/(1+10^([x || y || z || z']) ). Conductances of the four main currents are thus translated into cardiac cellular or tissue models to study the effect of a wide range of drug concentrations. The following parameters were obtained and summarized in currently described files. Detailed methods of the performed simulations, as well as biomarker calculations, can be consulted in [1]. es_ES
dc.description.abstract This repository contains six Excel files named “Tx matrix KrKsCaL.xlsx”, “Tx matix KrNaLCaL.xlsx”, “TqNet matrix KrKsCaL.xlsx”, “TqNet matrix KrNaLCaL.xlsx”, "Ttirang matrix KrKsCaL.xlsx" and “Ttirang matrix KrNaLCaL.xlsx”. These files contain the value of three arrhythmogenic indices proposed in [1] (Tx, TqNet and Ttriang) resulting from simulations of drug effects on the action potential. The simulations were performed in a modified version of the O’Hara-Rudy model (ORd) [2] of human endocardial ventricular cells (492.536 simulations). References: [1]. Llopis J., Gomis-Tena J., Cano J., Romero L., Saiz J., Trenor B. In-Silico Classifiers for Assessment of Drug Proarrhythmicity. 2020 (Currently under revision) [2]. O’Hara, T.; Virág, L.; Varró, A.; Rudy, Y. Simulation of the Undiseased Human Cardiac Ventricular Action Potential: Model Formulation and Experimental Validation. PLoS Comput. Biol. 2011, 7 (5), e1002061. es_ES
dc.description.sponsorship The authors would like to strongly thank Dr. Manuel Pastor from Research Programme on Biomedical Informatics (GRIB), at Universitat Pompeu Fabra (Barcelona, Spain) for its review of the manuscript and expert opinions and suggestions. This work was partially supported by the Dirección general de Política Científica de la Generalitat Valencia (PROMETEU2016/088), Primeros Proyectos de Investigación (PAID-06-18), Vicerrectorado de Investigación, Innovación y Transferencia de la Universitat Politècnica de València (UPV), València, Spain as well as Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016 from the Ministerio de Economía, Industria y Competitividad of Spain (DPI2016-75799-R) and AEI/FEDER, UE. JL is being funded by the Ministerio de Ciencia, Innovación y Universidades for the Formación de Profesorado Universitario (grant reference: FPU18/01659). es_ES
dc.language Inglés es_ES
dc.relation GV/PROMETEU2016/088
dc.relation UPV/PAID-06-18
dc.relation MINECO/DPI2016-75799-R
dc.relation Ministerio de Ciencia, Innovación y Universidades/FPU18/01659
dc.rights Reconocimiento - No comercial (by-nc) es_ES
dc.subject drug-induced Torsade de Pointes es_ES
dc.subject cardiac safety es_ES
dc.subject Tx es_ES
dc.subject TqNet es_ES
dc.subject Ttriang es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Tx, TqNet and Ttriang Values es_ES
dc.title.alternative In-Silico Classifiers for Assessment of Drug Proarrhytmicity es_ES
dc.type Dataset es_ES
dc.identifier.doi 10.4995/Dataset/10251/136919 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Centro de Investigación e Innovación en Bioingeniería es_ES
dc.description.bibliographicCitation Llopis Lorente, J.; Gomis-Tena Dolz, J.; Cano García, J.; Romero Pérez, L.; Saiz Rodríguez, FJ.; Trénor Gomis, BA. (2020). Tx, TqNet and Ttriang Values. https://doi.org/10.4995/Dataset/10251/136919 es_ES
dc.type.version info:eu-repo/semantics/submittedVersion es_ES
dc.contributor.funder Generalitat Valenciana
dc.contributor.funder Universitat Politècnica de València
dc.contributor.funder Ministerio de Economía, Industria y Competitividad
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades
dc.contributor.funder Agencia Estatal de Investigación
dc.contributor.funder European Regional Development Fund


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