Evidence map›Paper›PMID 26330803›Full record

ReviewImmune network2015

Proteomics in Rheumatoid Arthritis Research.

Yune-Jung Park, Min Kyung Chung, Daehee Hwang, Wan-Uk Kim

Abstract readReview
In one paragraph

Review in Immune network, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yune-Jung ParkDivision of Rheumatology, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon 16247, Korea. ; POSTECH-CATHOLIC Biomedical Engineering Institute, The Catholic University of Korea, Seoul 06591, Korea.
Min Kyung ChungDivision of Rheumatology, Department of Internal Medicine, St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Daehee HwangDepartment of New Biology and Center for Plant Aging Research, Institute for Basic Science, Daegu Gyeongbuk Institute of Science and Technology, Daegu 43014, Korea.
Wan-Uk KimPOSTECH-CATHOLIC Biomedical Engineering Institute, The Catholic University of Korea, Seoul 06591, Korea. ; Division of Rheumatology, Department of Internal Medicine, St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although rheumatoid arthritis (RA) is the most common chronic inflammatory autoimmune disease, diagnosis of RA is currently based on clinical manifestations, and there is no simple, practical assessment tool in the clinical field to assess disease activity and severity. Recently, there has been increasing interest in the discovery of new diagnostic RA biomarkers that can assist in evaluating disease activity, severity, and treatment response. Proteomics, the large-scale study of the proteome, has emerged as a powerful technique for protein identification and characterization. For the past 10 years, proteomic techniques have been applied to different biological samples (synovial tissue/fluid, blood, and urine) from RA patients and experimental animal models. In this review, we summarize the current state of the application of proteomics in RA and its importance in identifying biomarkers and treatment targets.

Indexed as

BiomarkerProteomicsRheumatoid arthritis

Identifiers

PMID26330803
PMCPMC4553255

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.