Evidence map›Paper›PMID 29650017›Full record

ReviewJournal of biomedical science2018

Toll-like receptors in lupus nephritis.

Satish Kumar Devarapu, Hans-Joachim Anders

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of biomedical science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

51 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Lupus Nephritis from Pathogenesis to New Therapies: An Update.International journal of molecular sciences · 2024
    Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Review
  20. Article
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

2 authors at 1 institution in 1 country.

Satish Kumar DevarapuNephrologisches Zentrum, Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig Maximilians Universität München, Ziemssenstr, 1&Schillerstr, 42, 80336, Munich, Germany.
Hans-Joachim AndersNephrologisches Zentrum, Medizinische Klinik und Poliklinik IV, Klinikum der Ludwig Maximilians Universität München, Ziemssenstr, 1&Schillerstr, 42, 80336, Munich, Germany. hjanders@med.uni-muenchen.de.ORCID http://orcid.org/0000-0003-2434-2956
LMU Klinikum · DE

Funding

Deutsche Forschungsgemeinschaft AN372/24-1Horizon 2020 Framework Programme 668036
6 · The paper itself

Abstract

The pathogenesis of systemic autoimmune diseases such as systemic lupus erythematosus (SLE) is based on the loss of self-tolerance against ubiquitous autoantigens involving all mechanisms of adaptive immunity. However, data accumulating over the last decade imply an important role also for numerous elements of innate immunity, namely the Toll-like receptors in the pathogenesis of SLE. Here we discuss their role in the most common organ complication of SLE, i.e. lupus nephritis. We summarize experimental and clinical data on the expression and functional contribution of the Toll-like receptors in immune complex glomerulonephritis, and intrarenal inflammation. Based on these discoveries Toll-like receptors are evolving as therapeutic targets for the treatment of SLE and lupus nephritis.

Indexed as

HumansInflammationLupus NephritisToll-Like ReceptorsToll-Like ReceptorsGlomerulonephritisImmune complexInflammasomeInnate immunityInterferon

Identifiers

PMID29650017
PMCPMC5898010
OpenAlexW2805529518

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.