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1.
Haemophilia ; 25(2): 343-348, 2019 Mar.
Article in English | MEDLINE | ID: mdl-30690836

ABSTRACT

The thrombin generation (TG) assay evaluates haemostatic balance, which is influenced by the levels of many coagulation factors and inhibitors. Our objective was to identify the determinant factors of TG in haemophilia A (HA) and haemophilia B (HB) patients and to compare them to those in healthy controls. Coagulation factor and inhibitor levels, and TG, were measured in platelet-poor plasma from 40 patients with HA, 32 patients with HB and 40 healthy subjects. Data were analysed using multiple regression models. In HA patients, factor VIII was a positive determinant of endogenous thrombin potential (ETP) and peak, whereas tissue factor pathway inhibitor (TFPI) and factor V were negative determinants of ETP and peak. In HB patients, FIX was a positive determinant of ETP and peak, FVII being a positive determinant of peak. Antithrombin and protein S (PS) were negative determinants of ETP while FX was a negative determinant of peak. Above all, in HB patients, TFPI was a negative determinant of ETP and peak. In healthy subjects, FVIII was a positive determinant of ETP and peak, whereas FX and protein S were negative determinants of these parameters. TFPI was not a negative determinant of either peak or ETP. In haemophilic patients, the determinant factors of TG are all implicated in FXa generation and inhibition, the crucial determinant factor being TFPI whatever the type of haemophilia, A or B. These findings contribute to the rationale that recently place TFPI as a target for innovative therapies of haemophilia.


Subject(s)
Blood Coagulation Tests/methods , Hemophilia A/diagnosis , Hemophilia B/diagnosis , Lipoproteins/analysis , Thrombin/metabolism , Adolescent , Adult , Aged , Blood Coagulation Factors/analysis , Case-Control Studies , Fibrinogen/analysis , Hemophilia A/pathology , Hemophilia B/pathology , Humans , Male , Middle Aged , Severity of Illness Index , Young Adult
2.
Bull Math Biol ; 80(8): 1989-2025, 2018 08.
Article in English | MEDLINE | ID: mdl-29948884

ABSTRACT

The coagulation cascade comprises numerous chemical reactions between many proteins, that finally lead to the formation of a clot to stop bleeding. Many numerical models have attempted to translate understanding of this cascade into mathematical equations that simulate the chain reactions. However, their predictions have not been validated against clinical data stemming from patients. In this paper, we propose an extensive validation of five available models, by comparing in healthy and haemophilic subjects, thrombin generation measured in vitro to thrombin generation predicted by the models in silico. In order to render the models more predictive, we calibrated the models to have an acceptable agreement between the experimental and estimated data. Optimization processes based on genetic algorithms were developed to search for those calibrated kinetic parameters. Our results show that the thrombin generation kinetics are so complex that they cannot be predicted by a unique set of kinetic parameters for all patients: the calibration of only three parameters in a subject-specific way allows reaching good model estimations for different experimental conditions realized on the same patient.


Subject(s)
Hemophilia A/blood , Models, Biological , Thrombin/biosynthesis , Algorithms , Blood Coagulation/physiology , Calibration , Computer Simulation , Healthy Volunteers , Hemophilia B/blood , Humans , In Vitro Techniques , Kinetics , Male , Mathematical Concepts
3.
J Colloid Interface Sci ; 284(2): 548-59, 2005 Apr 15.
Article in English | MEDLINE | ID: mdl-15780294

ABSTRACT

The aim of this work was to determine and to interpret the influence of nonwetting on the aggregation dynamics of micronic solid particles in a turbulent medium. Two silica granular samples were studied: one was naturally hydrophilic; the other was made hydrophobic. Aggregation in an aqueous ethanol solution was followed by in situ turbidimetry. The influence of stirring rate and deaeration was determined. Aggregates of hydrophilic particles were small and fragile, whereas aggregates of hydrophobic particles were large and solid. Moreover, they differred greatly in optical properties. Within the proposed approach, different features of the aggregate morphology were identified: fractal dimension, maximum size, and gas content of the hydrophobic clusters. These elements are taken into account in the models of aggregation dynamics proposed here.

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