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	2020-02-14
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 the Matlab functions used in [1] and 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.publisher	Universitat Politècnica de València	es_ES
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.relation.projectID	info:eu-repo/grantAgreement/GVA//PROMETEO%2F2016%2F088/ES/MODELOS COMPUTACIONALES PERSONALIZADOS MULTI-ESCALA PARA LA OPTIMIZACION DEL DIAGNOSTICO Y TRATAMIENTO DE ARRITMIAS CARDIACAS (PERSONALISED DIGITAL HEART)/
dc.relation.projectID	info:eu-repo/grantAgreement/UPV//PAID-06-18/
dc.relation.projectID	info:eu-repo/grantAgreement/MINECO//DPI2016-75799-R/ES/TECNOLOGIAS COMPUTACIONALES PARA LA OPTIMIZACION DE TERAPIAS PERSONALIZADAS DE PATOLOGIAS AURICULARES Y VENTRICULARES/
dc.relation.projectID	info:eu-repo/grantAgreement/MCIU//FPU18%2F01659/
dc.rights.accessRights	Abierto	es_ES
dc.contributor.affiliation	Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica	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. Universitat Politècnica de València. 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 Ciencia, Innovación y Universidades
dc.contributor.funder	Ministerio de Economía y Competitividad	es_ES

Tx, TqNet and Ttriang Values

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