Calibrated automated thrombography displays the concentration of thrombin in clotting plasma with or without platelets (platelet-rich plasma/platelet-poor plasma, PRP/PPP) in up to 48 samples by monitoring the splitting of a fluorogenic substrate and comparing it to a constant known thrombin activity in a parallel, non-clotting sample. Thus, the non-linearity of the reaction rate with thrombin concentration is compensated for, and adding an excess of substrate can be avoided. Standard conditions were established at which acceptable experimental variation accompanies sensitivity to pathological changes. The coefficients of variation of the surface under the curve (endogenous thrombin potential) are: within experiment ∼3%; intra-individual: <5% in PPP, <8% in PRP; interindividual 15% in PPP and 19% in PRP. In PPP, calibrated automated thrombography shows all clotting factor deficiencies (except factor XIII) and the effect of all anticoagulants [AVK, heparin(-likes), direct inhibitors]. In PRP, it is diminished in von Willebrand’s disease, but it also shows the effect of platelet inhibitors (e.g. aspirin and abciximab). Addition of activated protein C (APC) or thrombomodulin inhibits thrombin generation and reflects disorders of the APC system (congenital and acquired resistance, deficiencies and lupus antibodies) independent of concomitant inhibition of the procoagulant pathway as for example by anticoagulants.

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Brown-adipose-tissue mitochondria possess an energy-dissipating ion uniport which is inhibited by purine nucleotides. The regulatory nucleotides bind to a high-affinity site on the outer face of the inncr membrane which is independent of the adenine nucleotide translocator. A direct correlation between affinity for the regulatory site and ability to inhibit the ion uniport is demonstrated for a numbcr of nucleotidc analogues. 8-Azido-adenosine 5'-triphosphate, a photoaffinity label, also competes with GDP f o r thc binding site and induces respiratory control. 8-Azido-adenosine [~-"'P]tripliospl~ate was prepared and covalcntly bound to hamster brown-adipose-tissue niitochondria by neur-ultraviolet irradiation. Two major radioactive bands were identified of apparent molecular weight 30000 and 32000, representing 6'%, and 10~

To cite this article: Kremers RMW, Peters TC, Wagenvoord RJ, Hemker HC. The balance of pro-and anticoagulant processes underlying thrombin generation. J Thromb Haemost 2015; 13: 437-47.Summary. Background: The generation of thrombin in time is the combined effect of the processes of prothrombin conversion and thrombin inactivation. Measurement of prothrombin consumption used to provide valuable information on hemostatic disorders, but is no longer used, due to its elaborate nature. Objectives: Because thrombin generation (TG) curves are easily obtained with modern techniques, we developed a method to extract the prothrombin conversion curve from the TG curve, using a computational model for thrombin inactivation. Methods: Thrombin inactivation was modelled computationally by a reaction scheme with antithrombin, a 2 Macroglobulin and fibrinogen, taking into account the presence of the thrombin substrate ZGGR-AMC used to obtain the experimental data. The model was validated by comparison with data obtained from plasma as well as from a reaction mixture containing the same reactants as plasma. Results: The computational model fitted experimental data within the limits of experimental error. Thrombin inactivation curves were predicted within 2 SD in 96% of healthy subjects. Prothrombin conversion was calculated in 24 healthy subjects and validated by comparison with the experimental consumption of prothrombin during TG. The endogenous thrombin potential (ETP) mainly depends on the total amount of prothrombin converted and the thrombin decay capacity, and the peak height is determined by the maximum prothrombin conversion rate and the thrombin decay capacity. Conclusions: Thrombin inactivation can be accurately predicted by the proposed computational model and prothrombin conversion can be extracted from a TG curve using this computational prediction. This additional computational analysis of TG facilitates the analysis of the process of disturbed TG.