Literature DB >> 16706979

The limits of simulation of the clotting system.

R Wagenvoord1, P W Hemker, H C Hemker.   

Abstract

OBJECTIVE: To investigate in how far successful simulation of a thrombin generation (TG) curve gives information about the underlying biochemical reaction mechanism.
RESULTS: The large majority of TG curves do not contain more information than can be expressed by four parameters. A limited kinetic mechanism of six reactions, comprising proteolytic activation of factor (F) X and FII, feedback activation of FV, a cofactor function of FVa and thrombin inactivation by antithrombin can simulate any TG curve in a number of different ways. The information content of a TG curve is thus much smaller than the information required to describe a physiologically realistic reaction scheme of TG. Consequently, much of the input information is irrelevant for the output. FVIII deficiency or activation of protein C can, for example, be simulated by a reaction mechanism in which these factors do not occur.
CONCLUSION: A model that comprises not more than six reactions can simulate the same TG curve in a number of possible ways. The possibilities increase exponentially as the model grows more realistic. Successful simulation of experimental data therefore does not validate the underlying assumptions. A fortiori, simulation that is not checked against experimental data lacks any probative force. Simulation can be of use, however, to detect mistaken hypotheses and for parameter estimation in systems with fewer than five free parameters.

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Year:  2006        PMID: 16706979     DOI: 10.1111/j.1538-7836.2006.01967.x

Source DB:  PubMed          Journal:  J Thromb Haemost        ISSN: 1538-7836            Impact factor:   5.824


  12 in total

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2.  The impact of uncertainty in a blood coagulation model.

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4.  Use of population PK/PD approach to model the thrombin generation assay: assessment in haemophilia A plasma samples spiked by a TFPI antibody.

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5.  Modeling of human factor Va inactivation by activated protein C.

Authors:  Maria Cristina Bravo; Thomas Orfeo; Kenneth G Mann; Stephen J Everse
Journal:  BMC Syst Biol       Date:  2012-05-20

6.  Hypoxia Induces a Prothrombotic State Independently of the Physical Activity.

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Journal:  PLoS One       Date:  2015-10-30       Impact factor: 3.240

Review 7.  Thrombosis in Cerebral Aneurysms and the Computational Modeling Thereof: A Review.

Authors:  Malebogo N Ngoepe; Alejandro F Frangi; James V Byrne; Yiannis Ventikos
Journal:  Front Physiol       Date:  2018-04-04       Impact factor: 4.566

8.  Modeling Thrombin Generation in Plasma under Diffusion and Flow.

Authors:  Christian J C Biscombe; Steven K Dower; Ineke L Muir; Dalton J E Harvie
Journal:  Biophys J       Date:  2020-05-19       Impact factor: 4.033

9.  Antiplatelet agents can promote two-peaked thrombin generation in platelet rich plasma: mechanism and possible applications.

Authors:  Ivan D Tarandovskiy; Elena O Artemenko; Mikhail A Panteleev; Elena I Sinauridze; Fazoil I Ataullakhanov
Journal:  PLoS One       Date:  2013-02-06       Impact factor: 3.240

10.  Mathematical Modeling of Intravascular Blood Coagulation under Wall Shear Stress.

Authors:  Oleksii S Rukhlenko; Olga A Dudchenko; Ksenia E Zlobina; Georgy Th Guria
Journal:  PLoS One       Date:  2015-07-29       Impact factor: 3.240

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