Project description:Mathematical model of blood coagulation. Extension of Luan2007. New reactions, e.g., the activation of platelet by thrombin through PARs, the release of ADP and TXA2 from activated platelets, platelet activation by ADP and TXA2, the intrinsic pathway reactions, were added to the model.
Project description:Mathematical model of blood coagulation with platelet activation. Model includes factor XII, factor VIIIa fragments, meizothrombin, kallikrein, C1-inhibitor, alpha1-Antitrypsin, alpha2-Antiplasmin, fibrinogen and fibrillin.
Project description:Model listing the reactions of the intrinsic pathway as listed in Zarnitsina1996. Publication model is a spatio-termporal mathematical model of blood coagulation.
Model used as the example of the numerical intrinsic pathway in Braescu et al. (2011).
L. Braescu, M. Leretter, T. George, New direct inhibitors and their computed effect on the dynamics of thrombin formation in blood coagulation, in: T. F. George (Ed.), Computational Studies of New Materials II, World Scientific, 2011, 173–190. doi:10.3389/fphys.2012.00266.
Project description:Mathematical model of blood coagulation. Extended model of Mitrophanov2011 (which is an extension of Hockin2002). Additional reactions added involving thrombin. Modelling the effects of dilution and addition of recombinant factor VIIa, II, VII, IX, X, AT.
Project description:Blood coagulation model investigating effects of Xa-inhibitors (Rivaroxaban and Apixaban). Model is an extension of Pohl1994 and reduced from Wajima2009.
Encoding the model from the supplementary files results in 43 species, 82 reactions and 111 parameters. Including the drug (Xa-inhibitor) and drug-Xa complexes results in 46 species, 84 reactions and 115 parameters (+1 dummy variable to change inhibitory kinetic parameters depending on which drug is simulated). The publication lists there being 45 species, 84 reactions and 116 parameters. Publication figure 2 has 45 species present however the complex VIIa:Xa (reaction 51 involving Xa and VIIa) is not shown. This figure also has numerous small errors such as listing IXa:ATIII complex twice (instead of one being XIa:ATIII), not showing XIa:ATIII, typo ('Va' -> Va), typo (IXa + VIIIa -> IXA:'VIIa').
Rate laws for Xa-drug interactions were assumed to be mass action.
Project description:MicroRNAs (miRNAs) regulate cell physiology by altering protein expression, but the biology of platelet miRNAs is largely unexplored. We tested whether platelet miRNA levels were associated with platelet reactivity by genome-wide profiling using platelet RNA from 19 healthy subjects. We found that human platelets express 284 miRNAs. Unsupervised hierarchical clustering of miRNA profiles resulted in 2 groups of subjects that appeared to cluster by platelet aggregation phenotypes. Seventy-four miRNAs were differentially expressed (DE) between subjects grouped according to platelet aggregation to epinephrine, a subset of which predicted the platelet reactivity response. Using whole genome mRNA expression data on these same subjects, we computationally generated a high-priority list of miRNA-mRNA pairs in which the DE platelet miRNAs had binding sites in 3'UTRs of DE mRNAs, and the levels were negatively correlated. Three miRNA-mRNA pairs (miR-200b:PRKAR2B, miR-495:KLHL5 and miR-107:CLOCK) were selected from this list and all 3 miRNAs knocked down protein expression from the target mRNA. Reduced activation from platelets lacking PRKAR2B supported these findings. In summary, (1) platelet miRNAs are able to repress expression of platelet proteins, (2) miRNA profiles are associated with and may predict platelet reactivity, and (3) bioinformatic approaches can successfully identify functional miRNAs in platelets. Overall design: Total RNA from the platelets of 19 donors was harvested and labeled with Hy3. Reference RNA (a pool of all samples) was labeled with Hy5. This submission represents the miRNA expression component of the study.