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Proteomic analysis of human osteoarthritis synovial fluid

Overview of attention for article published in Clinical Proteomics, February 2014
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Title
Proteomic analysis of human osteoarthritis synovial fluid
Published in
Clinical Proteomics, February 2014
DOI 10.1186/1559-0275-11-6
Pubmed ID
Authors

Lavanya Balakrishnan, Raja Sekhar Nirujogi, Sartaj Ahmad, Mitali Bhattacharjee, Srikanth S Manda, Santosh Renuse, Dhanashree S Kelkar, Yashwanth Subbannayya, Rajesh Raju, Renu Goel, Joji Kurian Thomas, Navjyot Kaur, Mukesh Dhillon, Shantal Gupta Tankala, Ramesh Jois, Vivek Vasdev, YL Ramachandra, Nandini A Sahasrabuddhe, TS Keshava Prasad, Sujatha Mohan, Harsha Gowda, Subramanian Shankar, Akhilesh Pandey

Abstract

Osteoarthritis is a chronic musculoskeletal disorder characterized mainly by progressive degradation of the hyaline cartilage. Patients with osteoarthritis often postpone seeking medical help, which results in the diagnosis being made at an advanced stage of cartilage destruction. Sustained efforts are needed to identify specific markers that might help in early diagnosis, monitoring disease progression and in improving therapeutic outcomes. We employed a multipronged proteomic approach, which included multiple fractionation strategies followed by high resolution mass spectrometry analysis to explore the proteome of synovial fluid obtained from osteoarthritis patients. In addition to the total proteome, we also enriched glycoproteins from synovial fluid using lectin affinity chromatography.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 153 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Cuba 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Denmark 1 <1%
Unknown 148 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 22%
Researcher 28 18%
Student > Master 13 8%
Student > Bachelor 11 7%
Student > Doctoral Student 10 7%
Other 30 20%
Unknown 27 18%
Readers by discipline Count As %
Medicine and Dentistry 29 19%
Biochemistry, Genetics and Molecular Biology 24 16%
Agricultural and Biological Sciences 19 12%
Engineering 12 8%
Veterinary Science and Veterinary Medicine 8 5%
Other 25 16%
Unknown 36 24%