Evidence map›Paper›PMID 25506104›Full record

ArticleComputers & chemical engineering2014

Quantitative Analysis of Robustness of Dynamic Response and Signal Transfer in Insulin mediated PI3K/AKT Pathway.

Shibin Mathew, Ipsita Banerjee

Abstract read
In one paragraph

Article in Computers & chemical engineering, 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. Article
  2. Article
  3. PI3K in stemness regulation: from development to cancer.Biochemical Society transactions · 2020
    Review
  4. Article
  5. Crosstalk in transition: the translocation of Akt.Journal of mathematical biology · 2019
    Article
  6. Article
  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

2 authors.

Shibin MathewDepartment of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, USA.
Ipsita BanerjeeDepartment of Chemical and Petroleum Engineering, University of Pittsburgh, PA 15261, USA ; Department of Bioengineering, University of Pittsburgh, PA 15219, USA ; McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
Defining Mechanisms Controlling Stem Cell Fate During DifferentiationDP2OD006491 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BANERJEE, IPSITA · 2009 to 2009
$2.3M
NCATS NIH HHS UL1 TR000005NIH HHS DP2 OD006491
6 · The paper itself

Abstract

Robustness is a critical feature of signaling pathways ensuring signal propagation with high fidelity in the event of perturbations. Here we present a detailed quantitative analysis of robustness in insulin mediated PI3K/AKT pathway, a critical signaling pathway maintaining self-renewal in human embryonic stem cells. Using global sensitivity analysis, we identified robustness promoting mechanisms that ensure (1) maintenance of a first order or overshoot dynamics of self-renewal molecule, p-AKT and (2) robust transfer of signals from oscillatory insulin stimulus to p-AKT in the presence of noise. Our results indicate that negative feedback controls the robustness to most perturbations. Faithful transfer of signal from the stimulating ligand to p-AKT occurs even in the presence of noise, albeit with signal attenuation and high frequency cut-off. Negative feedback contributes to signal attenuation, while positive regulators upstream of PIP

Indexed as

Global sensitivity analysisPI3K/AKT pathwayRobust dynamicsSelf-renewalSignal transfer efficiency

Identifiers

PMID25506104
PMCPMC4261235

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Registered trials

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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.