Evidence map›Paper›PMID 28878738›Full record

ReviewFrontiers in endocrinology2017

Overlooked Mechanisms in Type 1 Diabetes Etiology: How Unique Costimulatory Molecules Contribute to Diabetogenesis.

David H Wagner

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. The diabetes pandemic and associated infections: suggestions for clinical microbiology.Reviews in medical microbiology : a journal of the Pathological Society of Great Britain and Ireland · 2019
    Article
  7. Article
  8. Article
  9. 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

1 author at 1 institution in 1 country.

David H WagnerThe Program in Integrated Immunology, Department of Medicine, Webb-Waring Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
University of Colorado Anschutz Medical Campus · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type 1 Diabetes (T1D) develops when immune cells invade the pancreatic islets resulting in loss of insulin production in beta cells. T cells have been proven to be central players in that process. What is surprising, however, is that classic mechanisms of tolerance cannot explain diabetogenesis; alternate mechanisms must now be considered. T cell receptor (TCR) revision is the process whereby T cells in the periphery alter TCR expression, outside the safety-net of thymic selection pressures. This process results in an expanded T cell repertoire, capable of responding to a universe of pathogens, but limitations are that increased risk for autoimmune disease development occurs. Classic T cell costimulators including the CD28 family have long been thought to be the major drivers for full T cell activation. In actuality, CD28 and its family member counterparts, ICOS and CTLA-4, all drive regulatory responses. Inflammation is driven by CD40, not CD28. CD40 as a costimulus has been largely overlooked. When naïve T cells interact with antigen presenting cell CD154, the major ligand for CD40, is induced. This creates a milieu for T cell (CD40)-T cell (CD154) interaction, leading to inflammation. Finally, defined pathogenic effector cells including TH40 (CD4

Indexed as

autoimmunitycostimulationetiology of willful actsT cell receptor revisiontype 1 diabetes

Identifiers

PMID28878738
PMCPMC5572340
OpenAlexW2746757175

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.