Evidence map›Paper›PMID 30989320›Full record

ReviewSeminars in immunopathology2019

Islet inflammation in type 2 diabetes.

Marianne Böni-Schnetzler, Daniel T Meier

Open access · hybridAbstract readReview
In one paragraph

Review in Seminars in immunopathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 118 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
118citing papers in PubMed, 5 pooled it
21.9field-weighted citation impact, top 1% 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

118 citing papers in PubMed, 5 syntheses or guidelines pooled it, 198 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Unlocking the potential ofFrontiers in nutrition · 2026
    Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Article

58 more citing papers are in PubMed but not listed here.

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 2 institutions in 1 country.

Marianne Böni-SchnetzlerEndocrinology, Diabetes and Metabolism, University Hospital of Basel, 4031, Basel, Switzerland. marianne.boeni@unibas.ch.
Daniel T MeierEndocrinology, Diabetes and Metabolism, University Hospital of Basel, 4031, Basel, Switzerland.
Department of Biomedicine Basel · CHUniversity Hospital of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolic diseases including type 2 diabetes are associated with meta-inflammation. β-Cell failure is a major component of the pathogenesis of type 2 diabetes. It is now well established that increased numbers of innate immune cells, cytokines, and chemokines have detrimental effects on islets in these chronic conditions. Recently, evidence emerged which points to initially adaptive and restorative functions of inflammatory factors and immune cells in metabolism. In the following review, we provide an overview on the features of islet inflammation in diabetes and models of prediabetes. We separately emphasize what is known on islet inflammation in humans and focus on in vivo animal models and how they are used to elucidate mechanistic aspects of islet inflammation. Further, we discuss the recently emerging physiologic signaling role of cytokines during adaptation and normal function of islet cells.

Indexed as

Signal TransductionCytokinesDiabetes Mellitus, Type 2HumansInflammationInsulin-Secreting CellsCytokinesCytokinesIL-1βInsulinIslet inflammationType 2 diabetesβ-Cell

Identifiers

PMID30989320
PMCPMC6592966
OpenAlexW2937993724

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.