ReviewCurrent opinion in endocrinology, diabetes, and obesity2010
New technologies for autoimmune disease monitoring.
Review in Current opinion in endocrinology, diabetes, and obesity, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 23 citations in OpenAlex.
- The 10,000 Immunomes Project: Building a Resource for Human Immunology.Cell reports · 2018Article
- Elevated IgG4 in patient circulation is associated with the risk of disease progression in melanoma.Oncoimmunology · 2015Article
- Multiparameter flow cytometry for discovery of disease mechanisms in rheumatic diseases.Arthritis and rheumatism · 2013Article
- Measurement of Soluble Biomarkers by Flow Cytometry.EJIFCC · 2013Article
- Fluorescence-based multiplex protein detection using optically encoded microbeads.Molecules (Basel, Switzerland) · 2012Review
- Mechanisms of drug resistance in kinases.Expert opinion on investigational drugs · 2011Review
- Minimal information about T cell assays: the process of reaching the community of T cell immunologists in cancer and beyond.Cancer immunology, immunotherapy : CII · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
purpose of reviewThis article will review new technologies used to characterize the immune phenotype of cells and serum for potential use in studies of autoimmunity. RECENT
findingsOne area of recent development in studies of immune phenotyping is the contrast between cells of the immune system at rest and following activation. This simply involves comparing these cells at rest and following ligand-induced activation and measuring signaling system activation (phosphoepitope identification) or intracellular cytokine production or activation-induced gene expression. Preliminary data using these techniques have begun to identify signatures of disease (biomarkers) that are only seen when using these activation-induced assays. One of the most exciting new technologies, cytometry by time-of-flight mass spectrometry, couples a flow cytometer to a mass spectrometer, allowing many more parameters to be analyzed per cell, and without spillover between assay reagents, compared to conventional optical flow cytometry (heavy ions, mass, replaces fluorophore readout). Another new technology to analyze soluble proteins, bead-based immunoassays, can simultaneously measure up to 75 soluble analytes in a multiplexed array. Other technologies provide similar innovations in terms of analytical content, throughput, and miniaturization. SUMMARY: We believe that new cellular genomic and protein-based technologies can provide key insights into autoimmune disease pathogenesis, progression, and therapy, and that these assays need to be applied in a systematic way to samples from patients with autoimmune diseases.
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.