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Gurmukh Sahota

Researcher at University of Pennsylvania

Publications -  11
Citations -  1117

Gurmukh Sahota is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Atrial fibrillation & Left atrial appendage occlusion. The author has an hindex of 6, co-authored 10 publications receiving 1045 citations. Previous affiliations of Gurmukh Sahota include Washington University in St. Louis & University of Illinois at Urbana–Champaign.

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The AP-1 transcription factor Batf controls TH17 differentiation

TL;DR: It is shown that Batf is required for the differentiation of IL17-producing T helper (TH17) cells, and it is demonstrated that the AP-1 protein BATF has a critical role in TH17 differentiation.
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Magic-Angle Spinning Solid-State NMR Spectroscopy of the β1 Immunoglobulin Binding Domain of Protein G (GB1): 15N and 13C Chemical Shift Assignments and Conformational Analysis

TL;DR: Main isotropic chemical shifts report on conformation, enabling a detailed comparison of the microcrystalline state with the conformation of single crystals and the protein in solution; the consistency of backbone conformation is the best among proteins studied so far.
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Regulation of the Drosophila Enhancer of split and invected-engrailed gene complexes by sister chromatid cohesion proteins

TL;DR: It is shown that transcription is hypersensitive to cohesin levels in two exceptional cases where cohesIn and the E(z)-mediated histone methylation simultaneously coat the entire Enhancer of split and invected-engrailed gene complexes in cells derived from Drosophila central nervous system.
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Bisphosphonate inhibitors of Toxoplasma gondi growth: in vitro, QSAR, and in vivo investigations.

TL;DR: The three most active compounds found in vitro were tested in vivo in a Smith-Webster mouse model and the two most active bisphosphonates were found to provide up to an 80% protection from death, a considerable improvement over that found previously with nitrogen-containing bisph phosphate compounds.
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Novel sequence-based method for identifying transcription factor binding sites in prokaryotic genomes

TL;DR: This work has developed a method that will primarily use available sequence data in order to determine prokaryotic transcription factor (TF) binding specificities and found putative motifs within each separate class.