Evidence map›Paper›PMID 41026787›Full record

ArticlePLoS computational biology2025

A computational framework for the investigation of phosphoinositide regulation.

Hilaire Yam Fung Cheung, Chukiat Tantiwong, Dipali Kale, Jonathan M Gibbins, Steve P Watson, Johan W M Heemskerk, Albert Sickmann, Robert Ahrends, Joanne L Dunster

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Hilaire Yam Fung CheungDepartment of Cardiovascular Sciences, College of Medicine and Health, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0003-0917-5918
Chukiat TantiwongInstitute for Cardiovascular and Metabolic Research, School of Biological Sciences, University of Reading, Reading, United Kingdom.
Dipali KaleLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V, Dortmund, Germany.
Jonathan M GibbinsInstitute for Cardiovascular and Metabolic Research, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0002-0372-5352
Steve P WatsonDepartment of Cardiovascular Sciences, College of Medicine and Health, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0002-7846-7423
Johan W M HeemskerkDepartment of Biochemistry, Cardiovascular Research Institute Maastricht (CARIM), Maastricht University, Maastricht, The Netherlands.
Albert SickmannLeibniz-Institut für Analytische Wissenschaften-ISAS-e.V, Dortmund, Germany.
Robert AhrendsDepartment of Analytical Chemistry, University of Vienna, Vienna, Austria.
Joanne L DunsterInstitute for Cardiovascular and Metabolic Research, School of Biological Sciences, University of Reading, Reading, United Kingdom.ORCID 0000-0001-8986-4902

Funding

British Heart Foundation RG/20/7/34866European Union’s Horizon 2020 research and innovation
6 · The paper itself

Abstract

Phosphoinositides are a group of interconvertible lipids that are located in the membrane of eukaryotic cells. They turnover via complex network of reactions (called the phosphoinositide pathway) that respond rapidly to regulate many aspects of a cell's response to their environment. Given their low-abundance they are difficult to characterise experimentally. Here we utilise a new experimental method to generate an unusually large dataset that characterises the time-dependent changes in five membrane bound phospoinositides and a soluble inositide in platelet, downstream of its GPVI receptor, where we know the phosphoinositide pathway is particularly active. To shed light on regulatotory steps that are often opaque to experimentation we use this data within a mathematical and computational framework. We construct and assess eleven mathematical models that represent competing interpretations of the dominant mechanisms that regulate the pathway. We find that while four of the models can generate the available data only one model, that incorporates an additional pool of PtdIns, is consistent with the data and is able to successfully predict the effects of an inhibitor. We publish all models openly in a form that is easily usable and adaptable for other researchers to use alongside our or their own data. We studied how changes in the shape and magnitude of events that stimulate the phosphoinositide pathway affect its dynamics. Despite these perturbations, the abundance of Phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) remained stable, consistent with findings reported in the literature.

Indexed as

Computational BiologyModels, BiologicalPhosphatidylinositolsBlood PlateletsComputer SimulationHumansSignal TransductionPhosphatidylinositols

Identifiers

PMID41026787
PMCPMC12510658

What Socratic holds

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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 Socratic graph.