Deciphering the canonical blockade of activated Hageman factor (FXIIa) by benzamidine in the coagulation cascade: A thorough dynamical perspective

2019 ◽  
Vol 94 (5) ◽  
pp. 1905-1918
Author(s):  
Elliasu Y. Salifu ◽  
Clement Agoni ◽  
Fisayo A. Olotu ◽  
Yussif M. Dokurugu ◽  
Mahmoud E. S. Soliman
Keyword(s):  
Coagulation Cascade ◽  
Hageman Factor

The uncalibrated prothrombinase-induced clotting time test

2010 ◽  
Vol 30 (04) ◽  
pp. 212-216 ◽  
Author(s):  
R. Jovic ◽  
M. Hollenstein ◽  
P. Degiacomi ◽  
M. Gautschi ◽  
A. Ferrández ◽  
...  
Keyword(s):  
Factor Xa ◽  
Heparin Therapy ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Diagnostic Tools ◽  
Direct Thrombin Inhibitors ◽  
Functional Assay ◽  
Clotting Time ◽  
Coagulation Time ◽  
Time Test

SummaryThe activated partial thromboplastin time test (aPTT) represents one of the most commonly used diagnostic tools in order to monitor patients undergoing heparin therapy. Expression of aPTT coagulation time in seconds represents common practice in order to evaluate the integrity of the coagulation cascade. The prolongation of the aPTT thus can indicate whether or not the heparin level is likely to be within therapeutic range. Unfortunately aPTT results are highly variable depending on patient properties, manufacturer, different reagents and instruments among others but most importantly aPTT’s dose response curve to heparin often lacks linearity. Furthermore, aPTT assays are insensitive to drugs such as, for example, low molecular weight heparin (LMWH) and direct factor Xa (FXa) inhibitors among others. On the other hand, the protrombinase-induced clotting time assay (PiCT®) has been show to be a reliable functional assay sensitive to all heparinoids as well as direct thrombin inhibitors (DTIs). So far, the commercially available PiCT assay (Pefakit®-PiCT®, DSM Nutritional Products Ltd. Branch Pentapharm, Basel, Switzerland) is designed to express results in terms of units with the help of specific calibrators, while aPTT results are most commonly expressed as coagulation time in seconds. In this report, we describe the results of a pilot study indicating that the Pefakit PiCT UC assay is superior to the aPTT for the efficient monitoring of patients undergoing UFH therapy; it is also suitable to determine and quantitate the effect of LMWH therapy. This indicates a distinct benefit when using this new approach over the use of aPPT for heparin monitoring.

Effects of Ellagic Acid upon the Rabbit Fibrinolytic System

1972 ◽  
Vol 27 (01) ◽  
pp. 063-071
Author(s):  
S. G Iatridis ◽  
P. G Iatridis
Keyword(s):  
Continuous Infusion ◽  
Ellagic Acid ◽  
Animal Experimentation ◽  
Inhibitory Effect ◽  
In Vivo Studies ◽  
Clot Lysis ◽  
Hageman Factor ◽  
Lysis Activity ◽  
Site Of Action

SummaryThe present investigation deals with in vivo studies of possible relations of active Hageman factor (HFa) to the problems of thrombolysis. The study is based upon animal experimentation in which 40 normal, 5 dicumarolized and 5 heparinized rabbits each received ellagic acid (Elac 10-2 M) by intravenous continuous infusion at a rate of 1 ml/min for a period of 25 min. The data suggest that the Elac infusion induced in vivo activation of HF. Streptokinase (SK) injection 25 min from the start of Elac i. v. infusion failed to induce clot lysis in blood drawn one min after its injection. The phenomenon was more prominent with low (SK 250 U or 500 U) concentrations of SK. With higher concentrations, SK-induced clot lysis activity was not affected by Elac infusion.In dicumarolized and heparinized rabbits Elac infusion still counteracted the fibrinolysis activating effect of low concentration of SK. The possibility that the above described phenomenon was due to either hypercoagulability or to a non-specific inhibitory effect of Elac upon SK was explored and excluded.It is concluded that HFa and SK have the same site of action. Thus it seems that HFa may block the precursor upon which SK acts by forming a complex with it. It is stressed that activation of this precursor by HFa requires a suitable surface.

The Formation of Intermediate Product I in a Purified System The Role of Factor IX or of its Precursor and of a Hageman Factor-PTA Fraction

1961 ◽  
Vol 6 (02) ◽  
pp. 224-234 ◽  
Author(s):  
E. T Yin ◽  
F Duckert
Keyword(s):  
Intermediate Product ◽  
Factor Ix ◽  
Assay Method ◽  
Lag Phase ◽  
Factor X ◽  
Haemophilia B ◽  
Hageman Factor ◽  
One Stage ◽  
The One

Summary1. The role of two clot promoting fractions isolated from either plasma or serum is studied in a purified system for the generation of intermediate product I in which the serum is replaced by factor X and the investigated fractions.2. Optimal generation of intermediate product I is possible in the purified system utilizing fractions devoid of factor IX one-stage activity. Prothrombin and thrombin are not necessary in this system.3. The fraction containing factor IX or its precursor, no measurable activity by the one-stage assay method, controls the yield of intermediate product I. No similar fraction can be isolated from haemophilia B plasma or serum.4. The Hageman factor — PTA fraction shortens the lag phase of intermediate product I formation and has no influence on the yield. This fraction can also be prepared from haemophilia B plasma or serum.

Activation of Hageman Factor by α-Adrenergic Stimulation

1970 ◽  
Vol 23 (03) ◽  
pp. 417-422 ◽  
Author(s):  
D. G McKay ◽  
J.-G Latour ◽  
Mary H. Parrish
Keyword(s):  
Disseminated Intravascular Coagulation ◽  
Adrenergic Receptor ◽  
Adrenergic Stimulation ◽  
Hageman Factor ◽  
Intravascular Coagulation ◽  
Receptor Sites ◽  
High Doses ◽  
Stimulation Of

SummaryThe infusion of epinephrine in high doses produces disseminated intravascular coagulation by activation of Hageman factor. The effect is blocked by phenoxybenz-amine and is therefore due to stimulation of α-adrenergic receptor sites.

Consumption of Hageman Factor Activity in the Generalized Shwartzman Reaction Induced by Liquoid

1970 ◽  
Vol 23 (02) ◽  
pp. 386-404 ◽  
Author(s):  
G Müller-Berghaus ◽  
H. G Lasch
Keyword(s):  
Partial Thromboplastin Time ◽  
Lethal Dose ◽  
Control Group ◽  
Factor V ◽  
Consumption Coagulopathy ◽  
Factor Activity ◽  
Hageman Factor ◽  
Intravascular Coagulation ◽  
Shwartzman Reaction

SummaryThe role of Hageman factor in triggering intravascular coagulation has been studied in rabbits injected intravenously with Liquoid. Besides changes of coagulation parameters characteristic of consumption coagulopathy (e.g. decrease in platelet counts, fibrinogen levels, factor V activity), a pronounced drop in Hageman factor activity was observed after injection of Liquoid. Likewise, the partial thromboplastin time became prolonged.The activation of Hageman factor in vivo could be prevented by intravenous infusion of lysozyme. Twenty min after starting the lysozyme infusion, the partial thromboplastin time became prolonged from a mean of 29 sec to 108 sec. Animals infused with lysozyme and injected with a lethal dose of Liquoid did not develop a consumption coagulopathy. In the same manner, none of 10 animals treated with lysozyme developed the generalized Shwartzman reaction, whereas in the control group 19 out of 20 animals showed fibrin thrombi in the glomerular capillaries.From the present study it may be concluded that the intravascular coagulation process after intravenous injection of Liquoid is triggered by Hageman factor activation.

REPEATED LONG-TERM SPACE FLIGHTS: PROTEOMIC INVESTIGATIONS OF COSMONAUTS' BLOOD

2020 ◽  
Vol 54 (5) ◽  
pp. 15-22
Author(s):  
I.M. Larina ◽  
◽  
D.N. Kashirina ◽  
K.S. Kireev ◽  
A.I. Grigoriev ◽  
...  
Keyword(s):  
Bone Structure ◽  
Space Station ◽  
The Body ◽  
Coagulation Cascade ◽  
Chemical Components ◽  
Blood Proteins ◽  
Blood Indices ◽  
Before And After ◽  
Biochemical Indices

We performed the first ever comparative analysis of modifications in the proteome, ionogram and some other blood plasma biochemical indices of 18 male cosmonauts (44 ± 6 years of age) before and after maiden or repeated long-term missions to the Russian segment of the International space station (ISS RS). Levels of proteins, substrates and ions as well as chemical components were measured using the LC-MS-based proteomics and routine biochemical techniques. A total of 256 to 281 indices were investigated with the methods of descriptive statistic, regression analysis, and access to bioinformatics resources. It was shown that blood indices recovery from the maiden and repeated missions reflects changes in the body systems and goes at a various speed. The results of measurements made prior to launch and on day 7 after landing are dependent on the number of missions. The bioinformatics techniques showed that after maiden missions both the mediator proteins of alkaline phosphatase (AP) and blood proteins with reliably changing concentrations are associated with the bio-processes including stress, metabolism and DNA reparation, apoptosis, catabolism and proteolysis. During early re-adaptation from repeated missions the AP level was affected by bone remodeling, phosphorylation, angiogenesis and coagulation cascade suggesting a distinct and urgent trigger of the processes of bone structure and mineralization.

Differential Drug Target Selection in Blood Coagulation: What can we get from Computational Systems Biology Models?

2020 ◽  
Vol 26 (18) ◽  
pp. 2109-2115 ◽  
Author(s):  
Mikhail A. Panteleev ◽  
Anna A. Andreeva ◽  
Alexey I. Lobanov
Keyword(s):  
Blood Coagulation ◽  
Biological Network ◽  
Target Selection ◽  
Anticoagulation Therapy ◽  
Differential Regulation ◽  
Coagulation Cascade ◽  
Computational Systems Biology ◽  
Analysis Strategies ◽  
Optimal Target ◽  
Computational Systems

Discovery and selection of the potential targets are some of the important issues in pharmacology. Even when all the reactions and the proteins in a biological network are known, how does one choose the optimal target? Here, we review and discuss the application of the computational methods to address this problem using the blood coagulation cascade as an example. The problem of correct antithrombotic targeting is critical for this system because, although several anticoagulants are currently available, all of them are associated with bleeding risks. The advantages and the drawbacks of different sensitivity analysis strategies are considered, focusing on the approaches that emphasize: 1) the functional modularity and the multi-tasking nature of this biological network; and 2) the need to normalize hemostasis during the anticoagulation therapy rather than completely suppress it. To illustrate this effect, we show the possibility of the differential regulation of lag time and endogenous thrombin potential in the thrombin generation. These methods allow to identify the elements in the blood coagulation cascade that may serve as the targets for the differential regulation of this system.

Diabetes and Vascular Disease: Is It All About Glycemia?

2019 ◽  
Vol 25 (29) ◽  
pp. 3112-3127 ◽  
Author(s):  
Alessandra Vecchié ◽  
Fabrizio Montecucco ◽  
Federico Carbone ◽  
Franco Dallegri ◽  
Aldo Bonaventura
Keyword(s):  
Vascular Disease ◽  
Inflammatory Cell ◽  
Vascular Dysfunction ◽  
Microvascular Complications ◽  
Coagulation Cascade ◽  
Inflammatory Cell Infiltrate ◽  
Extracellular Traps ◽  
Thrombotic Complications ◽  
Independent Entity ◽  
Complications And Mortality

Background: Diabetes is increasing over time, mainly driven by obesity, aging, and urbanization. Classical macro- and microvascular complications represent the final result of a complex interplay involving atherosclerosis at all stages. Methods: In this review, we aim at focusing on current updates in the pathophysiology of vascular disease in diabetes and discussing how new therapies might influence the management of these patients at high cardiovascular risk. Diabetes shows accelerated atherosclerosis with a larger inflammatory cell infiltrate, thus favoring the development of heart failure. ‘Diabetic cardiomyopathy’ perfectly describes a specific ischemia- and hypertension- independent entity due to diabetes-related metabolic alterations on myocardial function. Moreover, platelets from subjects with diabetes display a typical hyperreactivity explaining the stronger adhesion, activation, and aggregation. Additionally, diabetes provokes an exaggerated stimulation of the endothelium, with an increased release of reactive oxygen species and a reduced release of nitric oxide, both key elements of the endothelial dysfunction. Also, the coagulation cascade and leukocytes activate contributing to this pro-thrombotic environment. Neutrophils have been recently recognized to play a pivotal role by releasing neutrophil extracellular traps. Finally, microparticles from platelets, neutrophils or monocytes are detrimental effectors on the vessel wall and are involved both in vascular dysfunction and in thrombotic complications. Conclusion: In light of these findings, the therapeutic management of diabetes needs to be mostly focused on limiting the progression of complications by targeting precise pathophysiological mechanisms rather than the mere glycemic control, which failed to markedly reduce the risk for macrovascular complications and mortality.

In silico Prediction of Inhibitory Constant of Thrombin Inhibitors Using Machine Learning

2019 ◽  
Vol 21 (9) ◽  
pp. 662-669 ◽  
Author(s):  
Junnan Zhao ◽  
Lu Zhu ◽  
Weineng Zhou ◽  
Lingfeng Yin ◽  
Yuchen Wang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Regression Tree ◽  
Large Data ◽  
Thrombin Inhibitors ◽  
Coagulation Cascade ◽  
Gradient Boosting ◽  
Support Vector ◽  
Data Set ◽  
Descriptor Selection

Background: Thrombin is the central protease of the vertebrate blood coagulation cascade, which is closely related to cardiovascular diseases. The inhibitory constant Ki is the most significant property of thrombin inhibitors. Method: This study was carried out to predict Ki values of thrombin inhibitors based on a large data set by using machine learning methods. Taking advantage of finding non-intuitive regularities on high-dimensional datasets, machine learning can be used to build effective predictive models. A total of 6554 descriptors for each compound were collected and an efficient descriptor selection method was chosen to find the appropriate descriptors. Four different methods including multiple linear regression (MLR), K Nearest Neighbors (KNN), Gradient Boosting Regression Tree (GBRT) and Support Vector Machine (SVM) were implemented to build prediction models with these selected descriptors. Results: The SVM model was the best one among these methods with R2=0.84, MSE=0.55 for the training set and R2=0.83, MSE=0.56 for the test set. Several validation methods such as yrandomization test and applicability domain evaluation, were adopted to assess the robustness and generalization ability of the model. The final model shows excellent stability and predictive ability and can be employed for rapid estimation of the inhibitory constant, which is full of help for designing novel thrombin inhibitors.

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