ON THE DETERMINANTS OF FIBRE THICKNESS AND FIBRIN NETWORK CHARACTERISTICS.

1987 ◽  
Author(s):  
C H Nair ◽  
G A Shah ◽  
D P Dhall
Keyword(s):  
Network Structure ◽  
Plasma Proteins ◽  
Antithrombin Iii ◽  
Network Development ◽  
Network Characteristics ◽  
Fibrin Network ◽  
Fibre Growth ◽  
Network Properties ◽  
Kinetics Of ◽  
Lower Tensile Strength

Spectacular differences are found between characteristics of networks developed in plasma and those developed in pure fibrinogen solution. Networks in plasma have thicker fibres, are more permeable and have lower tensile strength. In this investigation determinants of network structure under "hycio-logical conditions of clotting have been examined in an attempt to account for differences in network structure in plasma and in fibrinogen solution.Two independent variations of mass-length ratio ( µp and µr-.) from permeability and turbidity respectively were used. Effect of varying fibrinogen and thrombin concentrations and the effect of physiological concentrations of Antithrombin III, fibronectin, albumin, γ-globulin and platelet extract on fibrin network structure was examined.Fibrinogen and thrombin alter network characteristics through the modification of kinetics of network development.In these and several other studies it has been found that the kinetics of fibrin formation ultimately determine the final network structure through events preceding the appearance of visible fibrin. In separate experiments it was found that spectacular differences in network structure developed in plasma and fibrinogen were not entirely accounted for by alterations induced in network properties by albumin, y-globulin, fibronectin, ATIII and platelet extract.It is concluded that the final network structure is determined by kinetics of fibrin fibre growth and is highly responsive to the presence of plasma proteins and platelets.The findings may have fundamental applications to haemostasis and thrombosis.

The effect of glycaemic control on fibrin network structure of type 2 diabetic subjects

2006 ◽  
Vol 96 (11) ◽  
pp. 623-629 ◽  
Author(s):  
Namukolo Covic ◽  
Du Toit Loots ◽  
Francois van der Westhuizen ◽  
Danie van Zyl ◽  
Paul Rheeder ◽  
...  
Keyword(s):  
Glycaemic Control ◽  
Network Structure ◽  
Glucose Control ◽  
Clot Formation ◽  
Fibrinogen Concentration ◽  
Blood Samples ◽  
Fibrin Network ◽  
Kinetics Of ◽  
Fibrin Network Structure

SummaryDiabetic subjects have been shown to have altered fibrin network structures. One possible cause may be fibrinogen glycation resulting in altered structure/function properties. We investigated the effect of glucose control on fibrinogen glycation and fibrin network structure in type 2 diabetes. Blood samples were taken from twenty uncontrolled diabetic subjects at baseline to determine the levels of fibrinogen glycation and fibrin network structures. The subjects were then treated with insulin until blood glucose control was achieved before end blood samples were taken. Twenty age- and BMI-matched non-diabetic subjects were included as a reference group. The diabetic subjects had significantly higher mean fibrinogen glycation at baseline than the non-diabetic subjects (7.84 vs. 3.89 mol glucose / mol fibrinogen;p < 0.001).This was significantly reduced during the intervention (7.84 to 5.24 mol glucose / mol fibrinogen; p< 0.0002) in the diabetic group. Both groups had high mean fibrinogen concentrations (4.25 and 4.02 g/l, diabetic and non-diabetic subjects respectively). There was no difference in fibrinogen concentration, porosity, compaction and kinetics of clot formation between the diabetic subjects and non-diabetic subjects at baseline, nor were there any changes during the intervention despite the reduced fibrinogen glycation. Fibrin network characteristics correlated well with fibrinogen but not with any markers of glycaemic control. Improved glycaemic control resulted in decreased fibrinogen glycation but not fibrinogen concentration. It seems as though porosity, compaction and kinetics of clot formation are more related to fibrinogen concentration than fibrinogen glycation in this model.

Antithrombin III and Heparin Cofactor II in Patients with Chronic Renal Failure Undergoing Regular Hemodialysis

1987 ◽  
Vol 57 (03) ◽  
pp. 263-268 ◽  
Author(s):  
P Toulon ◽  
C Jacquot ◽  
L Capron ◽  
M -O Frydman ◽  
D Vignon ◽  
...  
Keyword(s):  
Renal Failure ◽  
Chronic Renal Failure ◽  
Plasma Proteins ◽  
Antithrombin Iii ◽  
Vascular Wall ◽  
Relative Increase ◽  
Heparin Cofactor Ii ◽  
Normal Ranges ◽  
At Iii ◽  
Regular Hemodialysis

SummaryHeparin enhances the inhibition rate of thrombin by both antithrombin III (AT III) and heparin cofactor II (HC II). We studied the activity of these two plasma proteins in patients with chronic renal failure (CRF) undergoing regular hemodialysis as their heparin requirements varied widely. In 77 normal blood donors, normal ranges (mean ± 2 SD) were 82-122% for AT III and 65-145% for HC II. When compared with these controls 82 dialyzed CRF patients had a subnormal AT III activity and a significantly (p <0.001) lower HC II activity. To evaluate the effect of hemodialysis we compared AT III, HC II and total proteins in plasma before and after dialysis in. 24 patients (12 with normal and 12 with low basal HC II activity). AT III and HC II activities significantly (p <0.001) increased in absolute value. When related to total plasma proteins, in order to suppress the influence of hemoconcentration induced by dialysis, AT III decreased significantly (p <0.01) whereas HC II increased slightly but significantly (p <0.01) in the 12 patients with low initial HC II activity. The decrease of AT III induced by heparin administrated during dialysis is likely to account for this relative decrease of AT III activity. A modification of the distribution of both HC II and heparin between the vascular wall and the circulating blood is evoked to explain the relative increase in HC II activity and the need for higher heparin dosage in patients with low HC II levels.

Use of a Trophic Structure Test Bed to Validate a New Systems-of-Systems Resilience Metric

2020 ◽  
Author(s):  
Bryan C. Watson ◽  
Sanaya Kriplani ◽  
Marc J. Weissburg ◽  
Bert Bras
Keyword(s):  
Network Structure ◽  
Trophic Structure ◽  
Design Tool ◽  
Natural Ecosystem ◽  
Test Bed ◽  
Systems Of Systems ◽  
Network Characteristics ◽  
Biologically Inspired Design ◽  
Future Work ◽  
Structure Test

Abstract Systems of Systems (SoS) combine complex systems such as financial, transportation, energy, and healthcare systems to provide greater functionality. A failure in a constituent system, however, can render the entire SoS ineffective by causing cascading faults. One method to prevent constituent faults from compromising SoS performance is to increase the SoS’s “resilience,” a measure of the SoS’s ability to cope with these faults and efficiently recover. Attempts to engineer improved resilience require a metric to measure resilience across different SoS architectures (network arrangements). In a previous work, the System of System Resilience Metric (SoSRM) was presented as a possible solution, but this new metric requires additional testing. This work examines the key question: “How can natural ecosystem characteristics be used to validate the SoSRM metric?” We hypothesize that the analysis of a test bed of generic ecosystems will produce SoSRM values that will positively correlate with a triangular trophic structure (wide base), validating SoSRM as a useful design metric. First principles for test bed creation are presented including biodiversity, trophic structure, and the role of detritus. SoSRM is measured for 31 case studies in a trophic structure test bed. Ecosystem network structure is quantified with graph theory. SoSRM correlates as expected with ecosystem network structure (r2 = .5016, n = 31), thus providing a validation of SoSRM as a design tool. As a final check, tests are conducted to ensure SoSRM is independent of trivial network characteristics (i.e. the number of nodes or links). By validating SoSRM, we provide a foundation for future work that focuses on increasing SoS resilience with biologically inspired design heuristics.

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