M
Michael Levitt
Researcher at Stanford University
Publications - 422
Citations - 43139
Michael Levitt is an academic researcher from Stanford University. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 99, co-authored 349 publications receiving 41423 citations. Previous affiliations of Michael Levitt include Laboratory of Molecular Biology & Bar-Ilan University.
Papers
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Journal ArticleDOI
Does countercurrent exchange influence small-bowel function?
TL;DR: In this paper, it was shown how a shunt could function if a bolus of an exchanging substance entered the villus in arteriolar blood and the material diffused through the wall of the arteriole and then into the venous blood, which is flowing in the opposite direction.
Proceedings ArticleDOI
Modeling the Mechanical Microenvironment of Coiled Cerebral Aneurysms.
David I. Bass,Laurel Marsh,Patrick Fillingham,Do H Lim,Venkat Keshav Chivukula,Louis J. Kim,Alberto Aliseda,Michael Levitt +7 more
TL;DR: The results of this study suggest that coil embolization triggers clot formation within the aneurysm dome via a low shear stress-mediated pathway, and links independently observed findings from several benchtop and clinical studies, furthering the understanding of this treatment strategy.
Journal ArticleDOI
Mechanical thrombectomy for large vessel occlusion strokes beyond 24 hours
Amir Shaban,Sami Al Kasab,Reda M. Chalhoub,Eric Bass,Ilko Maier,Marios-Nikos Psychogios,Ali Alawieh,Stacey Q Wolfe,Adam S Arthur,Travis M. Dumont,Peter Kan,Joon-Tae Kim,Reade De Leacy,Joshua W. Osbun,Ansaar T Rai,Pascal Jabbour,Min S. Park,Roberto Crosa,Justin R Mascitelli,Michael Levitt,Adam J. Polifka,Walter Casagrande,Shinichi Yoshimura,Charles C. Matouk,Richard Williamson,Benjamin Gory,Maxim Mokin,Isabel Fragata,Daniele Giuseppe Romano,Shakeel Chowdry,M. Moss,Daniel Behme,Kaustubh Limaye,Alejandro M Spiotta,Edgar A. Samaniego +34 more
TL;DR: In this paper , the safety and efficacy of mechanical thrombectomy beyond the standard of care window was examined, and the authors used functional independence at 3 months as their primary outcome measure.
Journal ArticleDOI
International controlled study of revascularization and outcomes following COVID‐positive mechanical thrombectomy
Adam A Dmytriw,Sherief Ghozy,Ahmad Sweid,Michel Piotin,Kimon Bekelis,Nader Sourour,Eytan Raz,Daniel Vela-Duarte,Italo Linfante,Guilherme Dabus,Max Kole,Mario Martínez-Galdámez,Shahid M Nimjee,Demetrius K. Lopes,Ameer E Hassan,Peter Kan,Mohammad Ghorbani,Michael Levitt,Simon Escalard,Symeon Missios,Maksim Shapiro,Frédéric Clarençon,Mahmoud Elhorany,Rizwan Tahir,Patrick Youssef,Aditya S. Pandey,Robert M. Starke,Kareem El Naamani,Rawad Abbas,Ossama Mansour,Jorge Galván,Joshua T. Billingsley,Abolghasem Mortazavi,Melanie Walker,Mahmoud Dibas,Fabio Settecase,Manraj K.S. Heran,Anna L. Kuhn,Ajit S. Puri,Bijoy K Menon,Sanjeev Sivakumar,Ashkan Mowla,Salvatore A. D’Amato,Alicia M Zha,Daniel L Cooke,Justin E Vranic,Robert W. Regenhardt,James D. Rabinov,Christopher J Stapleton,Mayank Goyal,Han-Siong Kuan-Ying Wu,Jake Morgan Cohen,David Turkel-Parella,Andrew R. Xavier,Muhammad Waqas,Vincent M. Tutino,Adnan H. Siddiqui,Gaurav Gupta,Anil Nanda,Priyank Khandelwal,Cristina Tiu,Pere Cardona Portela,Natalia Pérez de la Ossa,Xabier Urra,Mercedes de Lera,Juan F. Arenillas,Marc Ribó,Manuel Requena,Mariangela Piano,Guglielmo Pero,K. De Sousa,Fawaz Al-Mufti,Zafar Hashim,S. Dinesh Nayak,Leonardo Renieri,Rose Du,M. Aziz-Sultan,David S Liebeskind,Raul G Nogueira,Mohamad Abdalkader,Thanh N. Nguyen,Nicholas Vigilante,James E. Siegler,Jonathan A. Grossberg,Hassan Saad,M. Reid Gooch,Nabeel Herial,Robert H. Rosenwasser,Stavropoula Tjoumakaris,Aman B. Patel,Ambooj Tiwari,Pascal Jabbour +91 more
TL;DR: If a significant association exists between COVID‐19 status with revascularization and functional outcomes following thrombectomy for large vessel occlusion (LVO), after adjustment for potential confounding factors is determined.
Book
Comparing and modeling protein structure
TL;DR: The first part of this work focuses on protein structural alignment, namely, the comparison of two structures and formalizes this problem as the optimization of a geometric similarity score over the space of rigid body transformations, leading to an approximate polynomial time alignment algorithm.