Evidence map›Paper›PMID 23705851›Full record

ArticleBMC systems biology2013

Computational modelling of the regulation of Insulin signalling by oxidative stress.

Graham R Smith, Daryl P Shanley

Open access · diamondAbstract read
In one paragraph

Article in BMC systems biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

16 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Computational toxicology (Amsterdam, Netherlands) · 2021
    Article
  6. Finding new edges: systems approaches to MTOR signaling.Biochemical Society transactions · 2021
    Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Review
  12. Computational Modeling in Liver Surgery.Frontiers in physiology · 2017
    Review
  13. Article
  14. Review
  15. Article
  16. 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

2 authors at 1 institution in 1 country.

Graham R SmithCentre for Integrated Systems Biology of Ageing & Nutrition (CISBAN), Institute for Ageing and Health, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK.
Daryl P Shanley
Newcastle University · GB

Funding

Biotechnology and Biological Sciences Research Council BBC0082001
6 · The paper itself

Abstract

backgroundExisting models of insulin signalling focus on short term dynamics, rather than the longer term dynamics necessary to understand many physiologically relevant behaviours. We have developed a model of insulin signalling in rodent adipocytes that includes both transcriptional feedback through the Forkhead box type O (FOXO) transcription factor, and interaction with oxidative stress, in addition to the core pathway. In the model Reactive Oxygen Species are both generated endogenously and can be applied externally. They regulate signalling though inhibition of phosphatases and induction of the activity of Stress Activated Protein Kinases, which themselves modulate feedbacks to insulin signalling and FOXO.

resultsInsulin and oxidative stress combined produce a lower degree of activation of insulin signalling than insulin alone. Fasting (nutrient withdrawal) and weak oxidative stress upregulate antioxidant defences while stronger oxidative stress leads to a short term activation of insulin signalling but if prolonged can have other effects including degradation of the insulin receptor substrate (IRS1) and FOXO. At high insulin the protective effect of moderate oxidative stress may disappear.

conclusionOur model is consistent with a wide range of experimental data, some of which is difficult to explain. Oxidative stress can have effects that are both up- and down-regulatory on insulin signalling. Our model therefore shows the complexity of the interaction between the two pathways and highlights the need for such integrated computational models to give insight into the dysregulation of insulin signalling along with more data at the individual level.A complete SBML model file can be downloaded from BIOMODELS (https://www.ebi.ac.uk/biomodels-main) with unique identifier MODEL1212210000.Other files and scripts are available as additional files with this journal article and can be downloaded from https://github.com/graham1034/Smith2012_insulin_signalling.

Indexed as

Computer SimulationOxidative StressSignal TransductionAnimalsCell LineFeedback, PhysiologicalForkhead Transcription FactorsHumansInsulinInsulin Receptor Substrate ProteinsModels, BiologicalRatsReactive Oxygen SpeciesForkhead Transcription FactorsInsulinInsulin Receptor Substrate ProteinsIRS1 protein, humanReactive Oxygen Species

Identifiers

PMID23705851
PMCPMC3668293
OpenAlexW2109320913

What OpenQuestion holds

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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.