There is growing interest in inflammation due to its involvement in many diverse medical conditions, including Alzheimer's disease, cancer, arthritis and asthma. The traditional view that resolution of inflammation is a passive process is now being superceded by an alternative hypothesis whereby its resolution is an active, anti-inflammatory process that can be manipulated therapeutically. This shift in mindset has stimulated a resurgence of interest in the biological mechanisms by which inflammation resolves. The anti-inflammatory processes central to the resolution of inflammation revolve around macrophages and are closely related to pro-inflammatory processes mediated by neutrophils and their ability to damage healthy tissue. We develop a spatially averaged model of inflammation centring on its resolution, accounting for populations of neutrophils and macrophages and incorporating both pro- and anti-inflammatory processes. Our ordinary differential equation model exhibits two outcomes that we relate to healthy and unhealthy states. We use bifurcation analysis to investigate how variation in the system parameters affects its outcome. We find that therapeutic manipulation of the rate of macrophage phagocytosis can aid in resolving inflammation but success is critically dependent on the rate of neutrophil apoptosis. Indeed our model predicts that an effective treatment protocol would take a dual approach, targeting macrophage phagocytosis alongside neutrophil apoptosis.

Hemostasis is a complex physiological mechanism that functions to maintain vascular integrity under any conditions. Its primary components are blood platelets and a coagulation network that interact to form the hemostatic plug, a combination of cell aggregate and gelatinous fibrin clot that stops bleeding upon vascular injury. Disorders of hemostasis result in bleeding or thrombosis, and are the major immediate cause of mortality and morbidity in the world. Regulation of hemostasis and thrombosis is immensely complex, as it depends on blood cell adhesion and mechanics, hydrodynamics and mass transport of various species, huge signal transduction networks in platelets, as well as spatiotemporal regulation of the blood coagulation network. Mathematical and computational modeling has been increasingly used to gain insight into this complexity over the last 30 years, but the limitations of the existing models remain profound. Here we review state-of-the-art-methods for computational modeling of thrombosis with the specific focus on the analysis of unresolved challenges. They include: a) fundamental issues related to physics of platelet aggregates and fibrin gels; b) computational challenges and limitations for solution of the models that combine cell adhesion, hydrodynamics and chemistry; c) biological mysteries and unknown parameters of processes; d) biophysical complexities of the spatiotemporal networks' regulation. Both relatively classical approaches and innovative computational techniques for their solution are considered; the subjects discussed with relation to thrombosis modeling include coarse-graining, continuum versus particle-based modeling, multiscale models, hybrid models, parameter estimation and others. Fundamental understanding gained from theoretical models are highlighted and a description of future prospects in the field and the nearest possible aims are given.

Macrophages are central to the inflammatory response and its ability to resolve effectively. They are complex cells that adopt a range of subtypes depending on the tissue type and stimulus that they find themselves under. This flexibility allows them to play multiple, sometimes opposing, roles in inflammation and tissue repair. Their central role in the inflammatory process is reflected in macrophage dysfunction being implicated in chronic inflammation and poorly healing wounds. In this study, we discuss recent attempts to model mathematically and computationally the macrophage and how it partakes in the complex processes of inflammation and tissue repair. There are increasing data describing the variety of macrophage phenotypes and their underlying transcriptional programs. Dynamic mathematical and computational models are an ideal way to test biological hypotheses against experimental data and could aid in understanding this multi-functional cell and its potential role as an attractive therapeutic target for inflammatory conditions and tissue repair.

We present a data-driven mathematical model of a key initiating step in platelet activation, a central process in the prevention of bleeding following Injury. In vascular disease, this process is activated inappropriately and causes thrombosis, heart attacks and stroke. The collagen receptor GPVI is the primary trigger for platelet activation at sites of injury. Understanding the complex molecular mechanisms initiated by this receptor is important for development of more effective antithrombotic medicines. In this work we developed a series of nonlinear ordinary differential equation models that are direct representations of biological hypotheses surrounding the initial steps in GPVI-stimulated signal transduction. At each stage model simulations were compared to our own quantitative, high-temporal experimental data that guides further experimental design, data collection and model refinement. Much is known about the linear forward reactions within platelet signalling pathways but knowledge of the roles of putative reverse reactions are poorly understood. An initial model, that includes a simple constitutively active phosphatase, was unable to explain experimental data. Model revisions, incorporating a complex pathway of interactions (and specifically the phosphatase TULA-2), provided a good description of the experimental data both based on observations of phosphorylation in samples from one donor and in those of a wider population. Our model was used to investigate the levels of proteins involved in regulating the pathway and the effect of low GPVI levels that have been associated with disease. Results indicate a clear separation in healthy and GPVI deficient states in respect of the signalling cascade dynamics associated with Syk tyrosine phosphorylation and activation. Our approach reveals the central importance of this negative feedback pathway that results in the temporal regulation of a specific class of protein tyrosine phosphatases in controlling the rate, and therefore extent, of GPVI-stimulated platelet activation.

The interindividual variation in the functional response of platelets to activation by agonists is heritable. Genome-wide association studies (GWAS) of quantitative measures of platelet function have thus far identified fewer than 20 distinctly associated variants, some with unknown mechanisms. Here, we report GWAS of pathway specific functional responses to agonism by ADP, a glycoprotein VI-specific collagen mimetic and thrombin receptor-agonist peptides, each specific to one of the G protein-coupled receptors PAR-1 and PAR-4, in subsets of 1,562 individuals. We identified an association (P=2.75x10-40) between a common intronic variant, rs10886430 in the G protein-coupled receptor kinase 5 gene (GRK5), and the sensitivity of platelets to activate through PAR-1. The variant resides in a megakaryocyte-specific enhancer bound by the transcription factors GATA1 and MEIS1. The minor allele (G) is associated with fewer GRK5 transcripts in platelets and greater sensitivity of platelets to activate through PAR-1. We show that thrombin mediated activation of human platelets causes binding of GRK5 to PAR-1 and that deletion of the mouse homologue Grk5 enhances thrombin induced platelet activation sensitivity and increases platelet accumulation at the site of vascular injury. This corroborates evidence that the human G-allele of rs10886430 associates with greater risks of cardiovascular diseases. In summary, by combining the results of pathway specific GWAS and eQTL studies in humans with the results of platelet function studies in Grk5-/- mice, we obtain evidence that GRK5 regulates the human platelet response to thrombin via the PAR-1 pathway.

Summary Antiplatelet drugs targeting G-protein-coupled receptors (GPCRs), used for the secondary prevention of arterial thrombosis, coincide with an increased bleeding risk. Targeting ITAM-linked receptors, such as the collagen receptor glycoprotein VI (GPVI), is expected to provide a better antithrombotic-hemostatic profile. Here, we developed and characterized an ultra-high-throughput (UHT) method based on intracellular [Ca 2+ ] i increases to differentiate GPVI and GPCR effects on platelets. In 96-, 384-, or 1,536-well formats, Calcium-6-loaded human platelets displayed a slow-prolonged or fast-transient [Ca 2+ ] i increase when stimulated with the GPVI agonist collagen-related peptide or with thrombin and other GPCR agonists, respectively. Semi-automated curve fitting revealed five parameters describing the Ca 2+ responses. Verification of the UHT assay was done with a robustness compound library and clinically relevant platelet inhibitors. Taken together, these results present proof of principle of distinct receptor-type-dependent Ca 2+ signaling curves in platelets, which allow identification of new inhibitors in a UHT way.

Platelets are blood cells responsible for vascular integrity preservation. The activation of platelet receptor C-type lectin-like receptor II-type (CLEC-2) could partially mediate the latter function. Although this receptor is considered to be of importance for hemostasis, the rate-limiting steps of CLEC-2-induced platelet activation are not clear. Here, we aimed to investigate CLEC-2-induced platelet signal transduction using computational modeling in combination with experimental approaches. We developed a stochastic multicompartmental computational model of CLEC-2 signaling. The model described platelet activation beginning with CLEC-2 receptor clustering, followed by Syk and Src family kinase phosphorylation, determined by the cluster size. Active Syk mediated linker adaptor for T cell protein phosphorylation and membrane signalosome formation, which resulted in the activation of Bruton's tyrosine kinase, phospholipase and phosphoinositide-3-kinase, calcium, and phosphoinositide signaling. The model parameters were assessed from published experimental data. Flow cytometry, total internal reflection fluorescence and confocal microscopy, and western blotting quantification of the protein phosphorylation were used for the assessment of the experimental dynamics of CLEC-2-induced platelet activation. Analysis of the model revealed that the CLEC-2 receptor clustering leading to the membrane-based signalosome formation is a critical element required for the accurate description of the experimental data. Both receptor clustering and signalosome formation are among the rate-limiting steps of CLEC-2-mediated platelet activation. In agreement with these predictions, the CLEC-2-induced platelet activation, but not activation mediated by G-protein-coupled receptors, was strongly dependent on temperature conditions and cholesterol depletion. Besides, the model predicted that CLEC-2-induced platelet activation results in cytosolic calcium spiking, which was confirmed by single-platelet total internal reflection fluorescence microscopy imaging. Our results suggest a refined picture of the platelet signal transduction network associated with CLEC-2. We show that tyrosine kinase activation is not the only rate-limiting step in CLEC-2-induced activation of platelets. Translocation of receptor-agonist complexes to the signaling region and linker adaptor for T cell signalosome formation in this region are limiting CLEC-2-induced activation as well.

Accurate and comprehensive assessment of platelet function across cohorts of donors may be key to understanding the risk of thrombotic events associated with cardiovascular disease, and hence help personalise the application of antiplatelet drugs. However, platelet function tests can be difficult to perform and analyse, unreliable or uninformative and poorly standardised across studies. The Platelet Phenomic Analysis (PPAnalysis) assay and associated open-source software platform was developed in response to these challenges. PPAnalysis utilises pre-prepared freeze-dried microtitre plates to provide a detailed characterisation of platelet function. The automated analysis of the high-dimensional data enables the identification of sub-populations of donors with distinct platelet function phenotypes. Using this approach we identified that the Sensitivity of a donor's platelets to an agonist and their Capacity to generate a functional response are distinct independent metrics of platelet reactivity. Hierarchical clustering of these metrics identified six subgroups with distinct platelet phenotypes within healthy cohorts, indicating that platelet reactivity does not fit into the traditional simple categories of 'high' and 'low' responders. These platelet phenotypes were found to exist in two independent cohorts of healthy donors and were stable on recall. PPAnalysis is a powerful tool for stratification of cohorts on the basis of platelet reactivity which will enable investigation of the causes and consequences of differences in platelet function and drive progress towards precision medicine.