Evidence map›Paper›PMID 26292621›Full record

ReviewSeminars in immunopathology2015

Functional autoantibodies in systemic sclerosis.

Jeannine Günther, Judith Rademacher, Jakob M van Laar, Elise Siegert, Gabriela Riemekasten

Abstract readReview
PubMed Publisher
In one paragraph

Review in Seminars in immunopathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. A broad look into the future of systemic sclerosis.Therapeutic advances in musculoskeletal disease · 2022
    Review
  6. Article
  7. Review
  8. Antinuclear Antibodies in Systemic Sclerosis: an Update.Clinical reviews in allergy & immunology · 2020
    Review
  9. Article
  10. Review
  11. Shared and distinct mechanisms of fibrosis.Nature reviews. Rheumatology · 2019
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Mechanisms of Autoantibody-Induced Pathology.Frontiers in immunology · 2017
    Review
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

5 authors at 3 institutions in 2 countries.

Jeannine GüntherDepartment of Rheumatology and Clinical Immunology, University Hospital Charité, Berlin, Germany, guenther@drfz.de.
Judith Rademacher
Jakob M van Laar
Elise Siegert
Gabriela Riemekasten
Charité - Universitätsmedizin Berlin · DEUniversity Medical Center Utrecht · NLUniversity of Lübeck · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional autoantibodies are an emerging field of research that focuses on the effects of these immunoglobulins when they bind to their target molecules. Accumulating information now exists about the molecular targets and precise binding mechanisms of functional autoantibodies as well as about their downstream effects. These data raise the need to distinguish functional autoantibodies from non-functional autoantibodies with regard to their ability to stimulate or to inhibit their target protein via binding. The presence of autoantibodies has been documented in autoimmune disorders decades ago, but meanwhile, more and more autoantibodies have been identified as functional, acting as pathogenic drivers involved in the induction of organ-specific damage in systemic sclerosis as well as in other autoimmune disorders. These findings offer new opportunities for the development of novel therapeutic strategies.

Indexed as

AutoantibodiesHumansScleroderma, SystemicAutoantibodies

Identifiers

PMID26292621
OpenAlexW1129174588

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.