ReviewCurrent opinion in rheumatology2014
New autoantibody detection technologies yield novel insights into autoimmune disease.
Review in Current opinion in rheumatology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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.
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.
Who cites it
10 citing papers in PubMed, 16 citations in OpenAlex.
- Comparison of circulating and excreted metals and of autoimmunity between two Great Plains Tribal communities.Journal of autoimmunity · 2024Article
- Membrane Proteome-Wide Screening of Autoantibodies in CIDP Using Human Cell Microarray Technology.Neurology(R) neuroimmunology & neuroinflammation · 2024Article
- Recent Advances in Biosensors for Diagnosis of Autoimmune Diseases.Sensors (Basel, Switzerland) · 2024Review
- The mosaic of autoimmunity - Finally discussing in person. The 13Autoimmunity reviews · 2022Article
- Detection of leucine-rich alpha-2-glycoprotein 1 containing immunocomplexes in the plasma of lung cancer patients with epitope-specific mAbs.Cancer biomarkers : section A of Disease markers · 2022Article
- Biosensors and nanobiosensors for rapid detection of autoimmune diseases: a review.Mikrochimica acta · 2019Review
- High-Definition Medicine.Cell · 2017Review
- AAgAtlas 1.0: a human autoantigen database.Nucleic acids research · 2017Article
- Transcriptomic Segregation of Human Autoantigens Useful for the Diagnosis of Autoimmune Diseases.Molecular diagnosis & therapy · 2016Review
- Identification of disease-specific motifs in the antibody specificity repertoire via next-generation sequencing.Scientific reports · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
purpose of reviewThe purpose of this review is to highlight recent progress in autoantibody detection technologies and describe how these methods are providing novel information and insights into autoimmune disorders. RECENT
findingsIn recent years, alternative methods such as comprehensive phage display, fluid-phase immunoassays, and antigen microarrays have been developed for autoantigen discovery and profiling autoantibody responses. Compared with classic approaches such as Western blot and ELISA, these methods show improved diagnostic performance, the ability to measure antibody responses to multiple targets, and/or allow more quantitative analyses. Specific notable findings include uncovering previously unrecognized autoantigens, the improved classification of patient clinical phenotypes, and the discovery of pathogenic autoantibodies promoting disease. SUMMARY: Advances in immunoassay technologies offer many opportunities for understanding the relationship between autoantibody detection and the myriad complex, clinical phenotypes characteristic of most autoimmune diseases. Further simplification and standardization of these technologies may allow routine integration into clinical practice with improved diagnostic and therapeutic outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.