Evidence map›Paper›PMID 24580269›Full record

ArticlePhysical review. E, Statistical, nonlinear, and soft matter physics2014

Phase transitions in pancreatic islet cellular networks and implications for type-1 diabetes.

I J Stamper, Elais Jackson, Xujing Wang

Abstract read
In one paragraph

Article in Physical review. E, Statistical, nonlinear, and soft matter physics, 2014. 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. Review
  2. Multilevel synchronization of humanFrontiers in network physiology · 2023
    Article
  3. Article
  4. Article
  5. Article
  6. 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.

I J StamperDepartment of Physics, the University of Alabama at Birmingham, Birmingham, Alabama, USA and The Comprehensive Diabetes Center, the University of Alabama at Birmingham, Birmingham, Alabama, USA.
Elais JacksonDepartment of Computer and Information Sciences, the University of Alabama at Birmingham, Birmingham, Alabama, USA.
Xujing WangDepartment of Physics, the University of Alabama at Birmingham, Birmingham, Alabama, USA and The Comprehensive Diabetes Center, the University of Alabama at Birmingham, Birmingham, Alabama, USA and Systems Biology Center, the National Heart, Lung, and Blood Institute, the National Institutes of Health, Bethesda, Maryland, USA.

Funding

Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BARBARA A GOWER · 2000 to 2026
$31.9M
Systems Biology CoreZIAHL006192 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI WANG, XUJING · 2014 to 2016
$4.6M
Intramural NIH HHS Z99 HL999999NIDDK NIH HHS P30 DK056336
6 · The paper itself

Abstract

In many aspects the onset of a chronic disease resembles a phase transition in a complex dynamic system: Quantitative changes accumulate largely unnoticed until a critical threshold is reached, which causes abrupt qualitative changes of the system. In this study we examine a special case, the onset of type-1 diabetes (T1D), a disease that results from loss of the insulin-producing pancreatic islet β cells. Within each islet, the β cells are electrically coupled to each other via gap-junctional channels. This intercellular coupling enables the β cells to synchronize their insulin release, thereby generating the multiscale temporal rhythms in blood insulin that are critical to maintaining blood glucose homeostasis. Using percolation theory we show how normal islet function is intrinsically linked to network connectivity. In particular, the critical amount of β-cell death at which the islet cellular network loses site percolation is consistent with laboratory and clinical observations of the threshold loss of β cells that causes islet functional failure. In addition, numerical simulations confirm that the islet cellular network needs to be percolated for β cells to synchronize. Furthermore, the interplay between site percolation and bond strength predicts the existence of a transient phase of islet functional recovery after onset of T1D and introduction of treatment, potentially explaining the honeymoon phenomenon. Based on these results, we hypothesize that the onset of T1D may be the result of a phase transition of the islet β-cell network.

Indexed as

Cell CommunicationModels, BiologicalAnimalsComputer SimulationDiabetes Mellitus, Type 1HumansInsulinIslets of LangerhansPhase TransitionSignal TransductionInsulin

Identifiers

PMID24580269
PMCPMC4172977

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.