0000000000619832

AUTHOR

Carlo Napolitano

0000-0002-7643-4628

showing 2 related works from this author

Paradoxical effect of increased diastolic Ca(2+) release and decreased sinoatrial node activity in a mouse model of catecholaminergic polymorphic ven…

2012

Background— Catecholaminergic polymorphic ventricular tachycardia is characterized by stress-triggered syncope and sudden death. Patients with catecholaminergic polymorphic ventricular tachycardia manifest sinoatrial node (SAN) dysfunction, the mechanisms of which remain unexplored. Methods and Results— We investigated SAN [Ca 2+ ] i handling in mice carrying the catecholaminergic polymorphic ventricular tachycardia–linked mutation of ryanodine receptor (RyR2 R4496C ) and their wild-type (WT) littermates. In vivo telemetric recordings showed impaired SAN automaticity in RyR2 R4496C mice after isoproterenol injection, analogous to what was observed in catecholaminergic polymorphic ventricul…

ChronotropicTachycardiaMalePatch-Clamp TechniquesAction Potentials030204 cardiovascular system & hematologyVentricular tachycardiaMice0302 clinical medicineSinoatrial NodeCatecholaminergic0303 health sciencesRyanodine receptorAdrenergic beta-AgonistsMiddle AgedSarcoplasmic Reticulummedicine.anatomical_structurecardiovascular systemCardiologyFemalemedicine.symptomCardiology and Cardiovascular MedicineAdultmedicine.medical_specialtyIn Vitro TechniquesCatecholaminergic polymorphic ventricular tachycardiaSudden deathArticle03 medical and health sciencesPhysiology (medical)Internal medicinemedicineAnimalsHumansCalcium SignalingExercise030304 developmental biologyAgedbusiness.industrySinoatrial nodeIsoproterenolRyanodine Receptor Calcium Release Channelmedicine.diseaseMice Mutant StrainsMice Inbred C57BLDisease Models AnimalEndocrinologyMutationTachycardia VentricularCalciumbusinessCirculation
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Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

2018

Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrh…

Decision support systemProcess (engineering)Computer scienceBig datacomputer.software_genre01 natural sciencesClinical decision support systemlcsh:QA75.5-76.9503 medical and health sciences0302 clinical medicinebig datalcsh:AZ20-999Health care030212 general & internal medicine0101 mathematicsdata analyticsdata integrationImplementationbusiness.industry010102 general mathematicslearning health care cyclelcsh:History of scholarship and learning. The humanitiesData scienceData warehousedata warehouseslcsh:Electronic computers. Computer sciencebusinesscomputerData integrationFrontiers in Digital Humanities
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