Evidence map›Paper›PMID 33613453›Full record

ReviewFrontiers in endocrinology2020

Cell Heterogeneity and Paracrine Interactions in Human Islet Function: A Perspective Focused in β-Cell Regeneration Strategies.

Eva Bru-Tari, Daniel Oropeza, Pedro L Herrera

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in endocrinology, 2020. 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
2.1field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Role of the Pancreatic Islet Microvasculature in Health and Disease.The journal of histochemistry and cytochemistry : official journal of the Histochemistry Society
    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

3 authors at 1 institution in 1 country.

Eva Bru-TariDepartment of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Daniel OropezaDepartment of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Pedro L HerreraDepartment of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
University of Geneva · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The β-cell regeneration field has shown a strong knowledge boost in the last 10 years. Pluripotent stem cell differentiation and direct reprogramming from other adult cell types are becoming more tangible long-term diabetes therapies. Newly generated β-like-cells consistently show hallmarks of native β-cells and can restore normoglycemia in diabetic mice in virtually all recent studies. Nonetheless, these cells still show important compromises in insulin secretion, cell metabolism, electrical activity, and overall survival, perhaps due to a lack of signal integration from other islet cells. Mounting data suggest that diabetes is not only a β-cell disease, as the other islet cell types also contribute to its physiopathology. Here, we present an update on the most recent studies of islet cell heterogeneity and paracrine interactions in the context of restoring an integrated islet function to improve β-cell replacement therapies.

Indexed as

AnimalsCell DifferentiationCell SurvivalDiabetes MellitusHumansInsulin-Secreting CellsIslets of LangerhansParacrine CommunicationRegenerationbeta-cell regenerationcell heterogeneityglucose homeostasishuman isletparacrine signaling

Identifiers

PMID33613453
PMCPMC7888438
OpenAlexW3128900766

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.