Title |
Modeling leukocyte trafficking at the human blood-nerve barrier in vitro and in vivo geared towards targeted molecular therapies for peripheral neuroinflammation
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Published in |
Journal of Neuroinflammation, January 2016
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DOI | 10.1186/s12974-015-0469-3 |
Pubmed ID | |
Authors |
Kelsey M. Greathouse, Steven P. Palladino, Chaoling Dong, Eric S. Helton, Eroboghene E. Ubogu |
Abstract |
Peripheral neuroinflammation is characterized by hematogenous mononuclear leukocyte infiltration into peripheral nerves. Despite significant clinical knowledge, advancements in molecular biology and progress in developing specific drugs for inflammatory disorders such as rheumatoid arthritis, inflammatory bowel disease, and multiple sclerosis, there are currently no specific therapies that modulate pathogenic peripheral nerve inflammation. Modeling leukocyte trafficking at the blood-nerve barrier using a reliable human in vitro model and potential intravital microscopy techniques in representative animal models guided by human observational data should facilitate the targeted modulation of the complex inflammatory cascade needed to develop safe and efficacious therapeutics for immune-mediated neuropathies and chronic neuropathic pain. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 48 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Other | 7 | 15% |
Student > Master | 6 | 13% |
Student > Bachelor | 6 | 13% |
Researcher | 5 | 10% |
Student > Doctoral Student | 4 | 8% |
Other | 11 | 23% |
Unknown | 9 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 8 | 17% |
Neuroscience | 8 | 17% |
Agricultural and Biological Sciences | 6 | 13% |
Biochemistry, Genetics and Molecular Biology | 4 | 8% |
Pharmacology, Toxicology and Pharmaceutical Science | 4 | 8% |
Other | 9 | 19% |
Unknown | 9 | 19% |