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David A. Lutz
Researcher at Dartmouth College
Publications - 50
Citations - 948
David A. Lutz is an academic researcher from Dartmouth College. The author has contributed to research in topics: Forest management & Neurite. The author has an hindex of 17, co-authored 43 publications receiving 648 citations. Previous affiliations of David A. Lutz include Wake Forest University & University of Virginia.
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Polysialic acid enters the cell nucleus attached to a fragment of the neural cell adhesion molecule NCAM to regulate the circadian rhythm in mouse brain
TL;DR: PSA attached to a transmembrane proteolytic NCAM fragment containing part of the extracellular domain enters the cell nucleus, where PSA-carrying NCAM contributes to the regulation of clock-related gene expression and of the circadian rhythm.
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Sensitivity of Russian forest timber harvest and carbon storage to temperature increase
TL;DR: In this article, the forest gap model FAREAST was used to derive biological growth parameters of several forest types; these data were then used within an economic model to discern the response from both a timber harvest and carbon sequestration perspective.
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Nonyloxytryptamine mimics polysialic acid and modulates neuronal and glial functions in cell culture
Gabriele Loers,Vedangana Saini,Bibhudatta Mishra,Florentia Papastefanaki,David A. Lutz,Sidhartha Chaudhury,Daniel R. Ripoll,Anders Wallqvist,Sheraz Gul,Melitta Schachner,Gurcharan Kaur +10 more
TL;DR: Results demonstrate that 5‐nonyloxytryptamine mimics PSA and triggers PSA‐mediated functions, thus contributing to the repertoire of molecules with the potential to improve recovery in acute and chronic injuries of the mammalian peripheral and central nervous systems.
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Written accounts of an Amazonian landscape over the last 450 years.
Nigel C. A. Pitman,María Del Carmen Loyola Azáldegui,Karina Salas,Gabriela Vigo,David A. Lutz +4 more
TL;DR: Recommendations include investing in syntheses, translations, popular summaries, and peer-reviewed journals in tropical countries, providing incentives for management-relevant research in tropical protected areas, and reinforcing training of scientific reading and writing in tropical universities.
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Change Detection of Amazonian Alluvial Gold Mining Using Deep Learning and Sentinel-2 Imagery
Seda Camalan,Kangning Cui,V. Paul Pauca,Sarra Alqahtani,Miles R. Silman,Raymond Chan,Robert Jame Plemmons,Evan N. Dethier,Luis E. Fernandez,David A. Lutz +9 more
TL;DR: E-ReCNN is capable of accurately detecting specific and object-oriented environmental changes related to ASGM and is a method of change detection that can be extended to other forms of land-use modification.