• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 2
  • 2
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Cytokine regulation in rodents with experimental arthritis /

Boström Müssener, Åsa, January 1900 (has links)
Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 6 uppsatser.
2

Identifying immune biomarkers to predict treatment response to biologic drugs in rheumatoid arthritis

Mulhearn, Ben January 2018 (has links)
Rheumatoid arthritis (RA) is a chronic, heterogeneous, autoimmune disease that causes inflammation of synovial joints leading to pain, stiffness and swelling. If left untreated, RA results in irreversible joint destruction and long term disability. Initial treatment with glucocorticoids and other immunosuppressive agents suppresses inflammation. However, many of these drugs are not well-tolerated due to extensive side effects or are simply ineffective. The discovery of tumour necrosis factor-α (TNF) as a key mediator of inflammation in RA led to the development of monoclonal anti-TNF antibody therapy. Since then, other biologic drugs targeting immune pathways have been developed for RA, including interleukin-6 (IL-6) blockade, B cell depletion, and T cell co-stimulation blockade. Not all patients will respond to their first biologic drug and currently there is no way to predict which patient will respond to each different class of drug. Generally, 3 – 6 months are required to determine clinical efficacy, during which time joint inflammation proceeds. Therefore, discovering biomarkers to predict treatment response is a research priority. Biologic drugs target immune pathways. As single cell technology advances and has increasing capacity to identify subtle changes in many cell subsets, I hypothesise that studying the blood immune cell landscape will define cellular biomarker profiles relevant to each individual patient’s disease.

Page generated in 0.037 seconds