Evidence map›Paper›PMID 23401699›Full record

ReviewClinical & developmental immunology2013

An innovative method to identify autoantigens expressed on the endothelial cell surface: serological identification system for autoantigens using a retroviral vector and flow cytometry (SARF).

Tsuyoshi Shirai, Hiroshi Fujii, Masao Ono, Ryu Watanabe, Tomonori Ishii, Hideo Harigae

Open access · goldAbstract readReview
In one paragraph

Review in Clinical & developmental immunology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
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

7 citing papers in PubMed, 17 citations in OpenAlex.

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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

6 authors at 1 institution in 1 country.

Tsuyoshi ShiraiDepartment of Hematology and Rheumatology, Tohoku University Graduate School of Medicine, Sendai, Miyagi 980-8574, Japan.
Hiroshi Fujii
Masao Ono
Ryu Watanabe
Tomonori Ishii
Hideo Harigae
Tohoku University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Autoantibodies against integral membrane proteins are usually pathogenic. Although anti-endothelial cell antibodies (AECAs) are considered to be critical, especially for vascular lesions in collagen diseases, most molecules identified as autoantigens for AECAs are localized within the cell and not expressed on the cell surface. For identification of autoantigens, proteomics and expression library analyses have been performed for many years with some success. To specifically target cell-surface molecules in identification of autoantigens, we constructed a serological identification system for autoantigens using a retroviral vector and flow cytometry (SARF). Here, we present an overview of recent research in AECAs and their target molecules and discuss the principle and the application of SARF. Using SARF, we successfully identified three different membrane proteins: fibronectin leucine-rich transmembrane protein 2 (FLRT2) from patients with systemic lupus erythematosus (SLE), intercellular adhesion molecule 1 (ICAM-1) from a patient with rheumatoid arthritis, and Pk (Gb3/CD77) from an SLE patient with hemolytic anemia, as targets for AECAs. SARF is useful for specific identification of autoantigens expressed on the cell surface, and identification of such interactions of the cell-surface autoantigens and pathogenic autoantibodies may enable the development of more specific intervention strategies in autoimmune diseases.

Indexed as

Anemia, HemolyticArthritis, RheumatoidAutoantigensCell SeparationEpithelial CellsFlow CytometryGenetic VectorsHumansLupus Erythematosus, SystemicProteomicsRetroviridaeSerologyAutoantigens

Identifiers

PMID23401699
PMCPMC3562638
OpenAlexW2102115660

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.