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DC Field | Value | Language |
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dc.contributor.advisor | KIKKERI, RAGHAVENDRA | en_US |
dc.contributor.author | CHERUKURI, KESAVA PHANEENDRA | en_US |
dc.date.accessioned | 2016-05-06T11:49:16Z | |
dc.date.available | 2016-05-06T11:49:16Z | |
dc.date.issued | 2016-05 | en_US |
dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/643 | - |
dc.description.abstract | The adhesion of leukocytes to vascular endothelium is a hallmark of the inflammatory process, which play a crucial role in multiple sclerosis (MS), ischemic stroke, and HIV-related dementia. Consequently, diagnoses of this activation are highly desirable. The conventional imaging techniques fail to diagnose the symptom, due to the weak permeability of the molecules through blood brain barrier (BBB). Hence, the delivery of imaging molecules across the BBB is still a major challenging aspect for presymptomatic diagnosis. Herein, we present the design and synthesis of sulfate-lewisx functionalized nanoparticles that allow direct detection of endothelial marker E and P-selectin in acute inflammation. We designed silica-coated iron oxide core, which exhibits superparamagnetic and also provided multiple copies of carbohydrate to increase the avidity during specific carbohydrate-protein interactions. Magnetic resonance imaging studies of these nanoparticles are expected to target E and P selectin in the ischemic brain and potential for translation into the clinic. | en_US |
dc.language.iso | en | en_US |
dc.subject | 2016 | |
dc.subject | Inflammation | en_US |
dc.subject | Iron nanoparticles | en_US |
dc.subject | Carbohydrates | en_US |
dc.subject | Imaging | en_US |
dc.subject | MRI | en_US |
dc.title | Targeting Endothelial Inflammation by Superparamagnetic Iron Glyco-Nano Particles. | en_US |
dc.type | Thesis | en_US |
dc.type.degree | BS-MS | en_US |
dc.contributor.department | Dept. of Chemistry | en_US |
dc.contributor.registration | 20111076 | en_US |
Appears in Collections: | MS THESES |
Files in This Item:
File | Description | Size | Format | |
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Final Thesis_20111076_Kesava.pdf | 4.73 MB | Adobe PDF | View/Open |
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