L
Leslie M. Loew
Researcher at University of Connecticut
Publications - 288
Citations - 19918
Leslie M. Loew is an academic researcher from University of Connecticut. The author has contributed to research in topics: Membrane & Membrane potential. The author has an hindex of 68, co-authored 276 publications receiving 18813 citations. Previous affiliations of Leslie M. Loew include Cornell University & University of Connecticut Health Center.
Papers
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Journal ArticleDOI
Convolution and Deconvolution For 3D Imaging Of Cell Physiology
TL;DR: In this article, the authors used deconvolution and convolution techniques to extend the utility of quantitative fluorescence to the measurement of analyte concentrations inside cells and their organelles.
Proceedings ArticleDOI
Simultaneous recording of t-tubular electrical activity and Ca2+-release in heart failure
Claudia Crocini,Raffaele Coppini,Cecilia Ferrantini,Ping Yan,Leslie M. Loew,Chiara Tesi,Corrado Poggesi,Elisabetta Cerbai,Francesco S. Pavone,Leonardo Sacconi +9 more
TL;DR: This work employed the advantages of an ultrafast random access multi-photon (RAMP) microscope with a double staining approach to optically record t-tubular AP and, simultaneously, the corresponding local Ca2+-release in different positions across the cardiomyocytes to probe the spatio-temporal variability of Ca2-release.
Journal ArticleDOI
Optogenetic manipulation of cardiac repolarization gradients using sub-threshold illumination
Gerard A Marchal,Valentina Biasci,Leslie M. Loew,Annibale Biggeri,Marina Campione,Leonardo Sacconi +5 more
TL;DR: In this article , the authors employ an approach based on optogenetic stimulation in a low-intensity fashion (sub-threshold illumination), to selectively manipulate cardiac electrical activity in defined areas of the heart.
Physiological cytosolic Ca2+transients evokeconcurrent mitochondrial depolarizations (membrane potential/fluorescence/bioenergetics/image
Leslie M. Loew,Fredric S. Fay +1 more
Proceedings ArticleDOI
Parallel techniques for Virtual Cell
TL;DR: A parallel implementation of a model that is inspired by the one-dimensional version of the Virtual Cell is presented, showing that this parallelization is quite effective and the speedups obtained are good implying that the parallel techniques employed could improve the performance of the virtual cell.