Evidence map›Paper›PMID 22116888›Full record

ReviewJournal of molecular cell biology2012

Harnessing memory adaptive regulatory T cells to control autoimmunity in type 1 diabetes.

Cheng-Rui Li, Bas J G Baaten, Linda M Bradley

Abstract readReview
In one paragraph

Review in Journal of molecular cell biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
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

7 citing papers in PubMed.

  1. Article
  2. Frontiers in immunology · 2017
    Article
  3. Article
  4. Article
  5. Article
  6. Regulatory T cells and B cells: implication on autoimmune diseases.International journal of clinical and experimental pathology · 2013
    Review
  7. 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

3 authors.

Cheng-Rui LiInfectious and Inflammatory Disease Center, Sanford-Burnham Medical Research Institute, La Jolla, CA 92037, USA.
Bas J G Baaten
Linda M Bradley

Funding

CD4 T Cell Subsets in Type 1 DiabetesR21AI081238 · NIAID · SANFORD BURNHAM PREBYS MEDICAL DISCOVERY INSTITUTE · PI BRADLEY, LINDA MAC PHERSON · 2009 to 2010
$525k
NIAID NIH HHS AI081238
6 · The paper itself

Abstract

Type 1 diabetes (T1D) results from autoimmune destruction of insulin-producing β-cells in the pancreatic islets. There is an immediate need to restore both β-cell function and immune tolerance to control disease progression and ultimately cure T1D. Currently, there is no effective treatment strategy to restore glucose regulation in patients with T1D. FoxP3-expressing CD4(+) regulatory T cells (Tregs) are potential candidates to control autoimmunity because they play a central role in maintaining self-tolerance. However, deficiencies in either naturally occurring Tregs (nTregs) themselves and/or their ability to control pathogenic effector T cells have been associated with T1D. Here, we hypothesize that nTregs can be replaced by FoxP3(+) adaptive Tregs (aTregs), which are uniquely equipped to combat autoreactivity in T1D. Unlike nTregs, aTregs are stable and provide long-lived protection. In this review, we summarize the current understanding of aTregs and their potential for use as an immunological intervention to treat T1D.

Indexed as

AutoimmunityAdoptive TransferAnimalsDiabetes Mellitus, Type 1Disease ProgressionForkhead Transcription FactorsHumansInsulin-Secreting CellsIntegrin beta ChainsInterleukin-2MiceSelf ToleranceT-Lymphocytes, RegulatoryTransforming Growth Factor betaForkhead Transcription FactorsFOXP3 protein, humanFoxp3 protein, mouseintegrin beta7Integrin beta ChainsInterleukin-2Transforming Growth Factor beta

Identifiers

PMID22116888
PMCPMC3269299

What OpenQuestion holds

Textmetadata
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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.