Platelets mediate arterial thrombosis, a leading cause of myocardial infarction and stroke. During injury, platelets adhere and spread over exposed subendothelial matrix substrates of the damaged ...blood vessel wall. The mechanisms which govern platelet activation and their interaction with a range of substrates are therefore regularly investigated using platelet spreading assays. These assays often use differential interference contrast (DIC) microscopy to assess platelet morphology and analysis performed using manual annotation. Here, a convolutional neural network (CNN) allowed fully automated analysis of platelet spreading assays captured by DIC microscopy. The CNN was trained using 120 generalised training images. Increasing the number of training images increases the mean average precision of the CNN. The CNN performance was compared to six manual annotators. Significant variation was observed between annotators, highlighting bias when manual analysis is performed. The CNN effectively analysed platelet morphology when platelets spread over a range of substrates (CRP-XL, vWF and fibrinogen), in the presence and absence of inhibitors (dasatinib, ibrutinib and PRT-060318) and agonist (thrombin), with results consistent in quantifying spread platelet area which is comparable to published literature. The application of a CNN enables, for the first time, automated analysis of platelet spreading assays captured by DIC microscopy.
Abstract
Background
Monocyte–platelet aggregates (MPAs) represent the crossroads between thrombosis and inflammation, and targeting this axis may suppress thromboinflammation. While antiplatelet ...therapy (APT) reduces platelet–platelet aggregation and thrombosis, its effects on MPA and platelet effector properties on monocytes are uncertain.
Objectives
To analyze the effect of platelets on monocyte activation and APT on MPA and platelet-induced monocyte activation.
Methods
Agonist-stimulated whole blood was incubated in the presence of P-selectin, PSGL1, PAR1, P2Y
12
, GP IIb/IIIa, and COX-1 inhibitors and assessed for platelet and monocyte activity via flow cytometry. RNA-Seq of monocytes incubated with platelets was used to identify platelet-induced monocyte transcripts and was validated by RT-qPCR in monocyte-PR co-incubation ± APT.
Results
Consistent with a proinflammatory platelet effector role, MPAs were increased in patients with COVID-19. RNA-Seq revealed a thromboinflammatory monocyte transcriptome upon incubation with platelets. Monocytes aggregated to platelets expressed higher CD40 and tissue factor than monocytes without platelets (
p
< 0.05 for each). Inhibition with P-selectin (85% reduction) and PSGL1 (87% reduction) led to a robust decrease in MPA. P2Y
12
and PAR1 inhibition lowered MPA formation (30 and 21% reduction,
p
< 0.05, respectively) and decreased monocyte CD40 and TF expression, while GP IIb/IIIa and COX1 inhibition had no effect. Pretreatment of platelets with P2Y
12
inhibitors reduced the expression of platelet-mediated monocyte transcription of proinflammatory
SOCS3
and
OSM.
Conclusions
Platelets skew monocytes toward a proinflammatory phenotype. Among traditional APTs, P2Y
12
inhibition attenuates platelet-induced monocyte activation.
Identifying patients with the optimal risk:benefit for ticagrelor is challenging. The aim was to identify ticagrelor-responsive platelet transcripts as biomarkers of platelet function and ...cardiovascular risk.
Healthy volunteers (n=58, discovery; n=49, validation) were exposed to 4 weeks of ticagrelor with platelet RNA data, platelet function, and self-reported bleeding measured pre-/post-ticagrelor. RNA sequencing was used to discover platelet genes affected by ticagrelor, and a subset of the most informative was summarized into a composite score and tested for validation. This score was further analyzed (1) in CD34+ megakaryocytes exposed to an P2Y12 inhibitor in vitro, (2) with baseline platelet function in healthy controls, (3) in peripheral artery disease patients (n=139) versus patient controls (n=30) without atherosclerosis, and (4) in patients with peripheral artery disease for correlation with atherosclerosis severity and risk of incident major adverse cardiovascular and limb events.
Ticagrelor exposure differentially expressed 3409 platelet transcripts. Of these, 111 were prioritized to calculate a Ticagrelor Exposure Signature score, which ticagrelor reproducibly increased in discovery and validation cohorts. Ticagrelor's effects on platelets transcripts positively correlated with effects of P2Y12 inhibition in primary megakaryocytes. In healthy controls, higher baseline scores correlated with lower baseline platelet function and with minor bleeding while receiving ticagrelor. In patients, lower scores independently associated with both the presence and extent of atherosclerosis and incident ischemic events.
Ticagrelor-responsive platelet transcripts are a biomarker for platelet function and cardiovascular risk and may have clinical utility for selecting patients with optimal risk:benefit for ticagrelor use.
Abstract
Background
CLEC-2 is a platelet receptor with an important role in thromboinflammation but a minor role in hemostasis. Two endogenous ligands of CLEC-2 have been identified, the ...transmembrane protein podoplanin and iron-containing porphyrin hemin, which is formed following hemolysis from red blood cells. Other exogenous ligands such as rhodocytin have contributed to our understanding of the role of CLEC-2.
Objectives
To identify novel CLEC-2 small-molecule ligands to aid therapeutic targeting of CLEC-2.
Methods
ALPHA screen technology has been used for the development of a high-throughput screening (HTS) assay recapitulating the podoplanin–CLEC-2 interaction. Light transmission aggregometry was used to evaluate platelet aggregation. Immunoprecipitation and western blot were used to evaluate direct phosphorylation of CLEC-2 and downstream protein phosphorylation. Autodock vina software was used to predict the molecular binding site of katacine and mass spectrometry to determine the polymeric nature of the ligand.
Results and Conclusion
We developed a CLEC-2–podoplanin interaction assay in a HTS format and screened 5,016 compounds from a European Union-open screen library. We identified katacine, a mixture of polymers of proanthocyanidins, as a novel ligand for CLEC-2 and showed that it induces platelet aggregation and CLEC-2 phosphorylation via Syk and Src kinases. Platelet aggregation induced by katacine is inhibited by the anti-CLEC-2 monoclonal antibody fragment AYP1 F(ab)′2. Katacine is a novel nonprotein ligand of CLEC-2 that could contribute to a better understanding of CLEC-2 activation in human platelets.
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Mining of metabolite-protein interaction networks facilitates the identification of design principles underlying the regulation of different cellular processes. However, ...identification and characterization of the regulatory role that metabolites play in interactions with proteins on a genome-scale level remains a pressing task. Based on availability of high-quality metabolite-protein interaction networks and genome-scale metabolic networks, here we propose a supervised machine learning approach, called CIRI that determines whether or not a metabolite is involved in a competitive inhibitory regulatory interaction with an enzyme. First, we show that CIRI outperforms the naive approach based on a structural similarity threshold for a putative competitive inhibitor and the substrates of a metabolic reaction. We also validate the performance of CIRI on several unseen data sets and databases of metabolite-protein interactions not used in the training, and demonstrate that the classifier can be effectively used to predict competitive inhibitory interactions. Finally, we show that CIRI can be employed to refine predictions about metabolite-protein interactions from a recently proposed PROMIS approach that employs metabolomics and proteomics profiles from size exclusion chromatography in E. coli to predict metabolite-protein interactions. Altogether, CIRI fills a gap in cataloguing metabolite-protein interactions and can be used in directing future machine learning efforts to categorize the regulatory type of these interactions.
Background
Accurate protein quantification is a vital prerequisite for generating meaningful predictions when using systems biology approaches, a method that is increasingly being used to unravel the ...complexities of subcellular interactions and as part of the drug discovery process. Quantitative proteomics, flow cytometry, and western blotting have been extensively used to define human platelet protein copy numbers, yet for mouse platelets, a model widely used for platelet research, evidence is largely limited to a single proteomic dataset in which the total amount of proteins was generally comparatively higher than those found in human platelets.
Objectives
To investigate the functional implications of discrepancies between levels of mouse and human proteins in the glycoprotein VI (GPVI) signalling pathway using a systems pharmacology model of GPVI.
Methods
The protein copy number of mouse platelet receptors was determined using flow cytometry. The Virtual Platelet, a mathematical model of GPVI signalling, was used to determine the consequences of protein copy number differences observed between human and mouse platelets.
Results and conclusion
Despite the small size of mouse platelets compared to human platelets they possessed a greater density of surface receptors alongside a higher concentration of intracellular signalling proteins. Surprisingly the predicted temporal profile of Syk activity was similar in both species with predictions supported experimentally. Super resolution microscopy demonstrates that the spatial distribution of Syk is similar between species, suggesting that the spatial distribution of receptors and signalling molecules in activated platelets, rather than their copy number, is important for signalling pathway regulation.
Abstract only Megakaryocytes (MKs) and platelets are recognized as mediators of inflammation and immunity. Antiplatelet therapies are widely used to prevent cardiovascular events; however, their role ...in attenuating platelet-mediated inflammation is uncertain. We investigated whether antiplatelet drugs, aspirin (ASA) and P2Y 12 inhibitors, alter the MK and platelet transcriptomes. We hypothesized that antiplatelet therapy reduces MK- and platelet-mediated inflammation. RNA-seq was performed in CD34 + derived MKs treated with ASA (100 μM), P2Y 12 inhibitor (AZD1283, 5 μM) or PBS for 24 hours. We validated our MK model using RNA-seq data from platelets of healthy volunteers randomized in a crossover design to low-dose ASA (n = 70, 64% female, 43.6 ± 9 years) or P2Y 12 inhibitor (ticagrelor, n = 57, 61% female, 43.9 ± 10 years) for 4 weeks each. The clinical relevance of our findings was assessed using RNA-seq data from platelets of SLE patients (n = 54, 100% female, 40.6 ± 12 years) and matched controls (n = 18, 100% female, 42.1 ± 15 years). Finally, we validated our findings in vitro using RT-qPCR and western blot. We identified 74 ASA- and 2,499 P2Y 12 inhibitor MK-responsive genes. In contrast to ASA, P2Y 12 inhibitor-mediated gene changes between MK and platelet transcriptomes were positively correlated (R=0.37, p<0.001). P2Y 12 inhibition downregulated IFNα response pathway in both MKs (NES = -2.3, p = 0.002) and platelets (NES = -2.24, p = 3.22 х 10 -8 ). SLE is characterized by activation of the IFN system. Consistently, the IFNα pathway was upregulated in platelets from SLE patients versus controls (NES = 3.38, p = 1.25 х 10 -9 ). Among 72 upregulated IFNα genes in SLE patients, 33 were inhibited with P2Y 12 inhibition in MKs or platelets, including IRF7 and IFITM3. Finally, we validated the P2Y 12 inhibitory effect on IFN-associated responses. While IFNα (1000 U/mL) significantly upregulated both IRF7 and IFITM3, pre-treatment with P2Y 12 receptor inhibition attenuated this response on both, the transcriptomic and proteomic levels. Our data indicate that targeting the P2Y 12 receptor attenuates MK- and platelet-mediated IFN signaling pathways. P2Y 12 -mediated suppression of platelet-induced IFNα signaling may be beneficial in inflammatory and autoimmune diseases including SLE.
Due to the potential decrease of the computation time for problems with fractional order derivatives, and due to the extension of the range of applicable solvers for a given problem, the ...approximation of fractional derivatives (e.g., using Oustaloup’s method) is an important and frequently discussed topic. A significant problem that can occur (although one that is not discussed very often) when approximations are applied concerns the potential numerical issues that can arise when applying these approximations in a transient analysis, e.g., as shown in the paper, in a time-stepping solver. This paper examines five different methods for approximating the fractional derivative (Oustaloup’s method, a refined Oustaloup method, a modified continued fraction expansion method, Matsuda’s method and Charef’s method). An important preliminary step in the analysis was the establishment of the general form of FDAE (fractional differential-algebraic equations), the general form of the applied approximations and the general form of the DAE (differential-algebraic equations) resulting from the approximation. This allowed for a precise description of the equations according to which the transformation from the FDAE to the approximating DAE takes place. Three problems derived from studies in electrical engineering have been introduced into the analysis (a linear circuit problem, a circuit problem with nonlinear fractional elements, and a problem featuring nonlinearities and pregenerated noise). For these problems, the conditions in which numerical issues appear have been studied in detail. They are the main motivation of this study as these issues are so significant that they often result in zero-solutions or solutions tending to infinity (giving an impression as if the system is unstable). Modifications and alternatives of the transformation into the DAE, that aim at the mitigation of these numerical errors, are mentioned later. The final result is very satisfactory, where the algorithm for the transformation of the FDAE to the approximating DAE practically eliminates the most important barriers (which was the impossibility of using approximations above a certain order due to the mentioned numerical issues). The study presented in this paper is motivated by problems in electrical engineering but due to its generality it is also applicable in other fields where fractional calculus is used.
•Five fractional derivative approximation methods are examined.•General FDAE and DAE forms are recalled (for the problem and its approximation).•Numerical issues appearing after applying approximations are demonstrated.•Various methodologies on the mitigation of these numerical issues have been proposed.•The final transformation methodology allows for very high approximation orders.
The application of a numerical method for the approximation of the fractional derivative (in Riemann–Liouville and Caputo definitions) in initial value problems is discussed. The method (previously ...known as the subinterval-based method) is now referred to by its acronym, SubIval, for simpler future references.
It is dependent on subinterval partitions (performed according to a proposed algorithm), interpolations using selected time axis nodes (i.e. nodes where solutions have been computed) and analytical monomial integrodifferentiation formulae.
Two exemplary circuit problems have been introduced as a test for the method. These problems have analytical solutions available in literature. The evaluations of these solutions have been compared with results obtained through an adaptive step size predictor-corrector scheme, where the core computations relied on the proposed numerical method.
SubIval has been implemented into an ActiveX Dynamic-Link Library (DLL). The paper contains instructions on how the predictor-corrector algorithm can be implemented into a Computer Algebra System, where the SubIval library is applied for the fractional derivative approximation. Examples of this are given in the form of scripts in MATLAB and Mathematica. These scripts generally allow to solve systems of fractional order state equations, to which the introduced circuit examples can be brought to.
The modeling of coils with ferromagnetic cores is considered. An attempt is made at the application of fractional derivatives because of the success in the modeling of real phenomena in various other ...fields. Three coils with ferromagnetic cores have been selected for the analysis. In order to obtain a basis for the study, measurements have been taken on a specially designed setup including an arbitrary function generator and a data acquisition device. The measurement process has been controlled by an original algorithm written in C#. The studied model has been considered in several varieties (various numbers of fractional coil and capacitor branches) in a ladder-like structure. The estimation process has been performed in an original program written in C#, applying the COBYLA method for constrained optimization. The modeling and simulation results have been compared through their frequency characteristics. A more critical approach has also been applied, where the measurements and simulations are compared for both a non-sinusoidal waveform and a step function on the source output.
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