A multiscale model for multiple platelet aggregation in shear flow

Platelet Biorheology and Mechanobiology in Thrombosis and Hemostasis: Perspectives from Multiscale Computation

Thrombosis is the pathological clot formation under abnormal hemodynamic conditions, which can result in vascular obstruction, causing ischemic strokes and myocardial infarction. Thrombus growth under moderate to low shear (<1000 s-1) relies on platelet activation and coagulation. Thrombosis at elevated high shear rates (>10,000 s-1) is predominantly driven by unactivated platelet binding and aggregating mediated by von Willebrand factor (VWF), while platelet activation and coagulation are secondary in supporting and reinforcing the thrombus. Given the molecular and cellular level information it can access, multiscale computational modeling informed by biology can provide new pathophysiological mechanisms that are otherwise not accessible experimentally, holding promise for novel first-principle-based therapeutics. In this review, we summarize the key aspects of platelet biorheology and mechanobiology, focusing on the molecular and cellular scale events and how they build up to thrombosis through platelet adhesion and aggregation in the presence or absence of platelet activation. In particular, we highlight recent advancements in multiscale modeling of platelet biorheology and mechanobiology and how they can lead to the better prediction and quantification of thrombus formation, exemplifying the exciting paradigm of digital medicine.

[Progress in the analysis of hemolysis and coagulation models for interventional micro-axial flow blood pumps]

Interventional micro-axial flow blood pump is widely used as an effective treatment for patients with cardiogenic shock. Hemolysis and coagulation are vital concerns in the clinical application of interventional micro-axial flow pumps. This paper reviewed hemolysis and coagulation models for micro-axial flow blood pumps. Firstly, the structural characteristics of commercial interventional micro-axial flow blood pumps and issues related to clinical applications were introduced. Then the basic mechanisms of hemolysis and coagulation were used to study the factors affecting erythrocyte damage and platelet activation in interventional micro-axial flow blood pumps, focusing on the current models of hemolysis and coagulation on different scales (macroscopic, mesoscopic, and microscopic). Since models at different scales have different perspectives on the study of hemolysis and coagulation, a comprehensive analysis combined with multi-scale models is required to fully consider the influence of complex factors of interventional pumps on hemolysis and coagulation.

Modelling of the in-stent thrombus formation by dissipative particle dynamics

BACKGROUND

Stent implantation is a highly efficacious intervention for the treatment of coronary atherosclerosis. Nevertheless, stent thrombosis and other post-operative complications persist, and the underlying mechanism of adverse event remains elusive.

METHODS

In the present study, a dissipative particle dynamics model was formulated to simulate the motion, adhesion, activation, and aggregation of platelets, with the aim of elucidating the mechanisms of in-stent thrombosis.

FINDINGS

The findings suggest that stent thrombosis arises from a complex interplay of multiple factors, including endothelial injury resulting from stent implantation and alterations in the hemodynamic milieu. Furthermore, the results suggest a noteworthy association between in-stent thrombosis and both the length of the endothelial injured site and the degree of stent malposition. Specifically, the incidence of stent thrombosis appears to rise in tandem with the extent of the injured site, while moderate stent malposition is more likely to result in in-stent thrombosis compared to severe or minor malposition.

INTERPRETATION

This study offers novel research avenues for investigating the plasticity mechanism of stent thrombosis, while also facilitating the clinical prediction of stent thrombosis formation and the development of more precise treatment strategies.

Decoding thrombosis through code: a review of computational models

From the molecular level up to a blood vessel, thrombosis and hemostasis involves many interconnected biochemical and biophysical processes over a wide range of length and time scales. Computational modeling has gained eminence in offering insights into these processes beyond what can be obtained from in vitro or in vivo experiments, or clinical measurements. The multiscale and multiphysics nature of thrombosis has inspired a wide range of modeling approaches that aim to address how a thrombus forms and dismantles. Here, we review recent advances in computational modeling with a focus on platelet-based thrombosis. We attempt to summarize the diverse range of modeling efforts straddling the wide-spectrum of physical phenomena, length scales, and time scales; highlighting key advancements and insights from existing studies. Potential information gleaned from models is discussed, ranging from identification of thrombus-prone regions in patient-specific vasculature to modeling thrombus deformation and embolization in response to fluid forces. Furthermore, we highlight several limitations of current models, future directions in the field, and opportunities for clinical translation, to illustrate the state-of-the-art. There are a plethora of opportunity areas for which models can be expanded, ranging from topics of thromboinflammation to platelet production and clearance. Through successes demonstrated in existing studies described here, as well as continued advancements in computational methodologies and computer processing speeds and memory, in silico investigations in thrombosis are poised to bring about significant knowledge growth in the years to come.

Local Clays from China as Alternative Hemostatic Agents

In recent years, the coagulation properties of inorganic minerals such as kaolin and zeolite have been demonstrated. This study aimed to assess the hemostatic properties of three local clays from China: natural kaolin from Hainan, natural halloysite from Yunnan, and zeolite synthesized by our group. The physical and chemical properties, blood coagulation performance, and cell biocompatibility of the three materials were tested. The studied materials were characterized by using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), X-ray fluorescence spectroscopy (XRF), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). All three clays showed different morphologies and particle size, and exhibited negative potentials between pH 6 and 8. The TGA and DSC curves for kaolin and halloysite were highly similar. Kaolin showed the highest water absorption capacity (approximately 93.8% ± 0.8%). All three clays were noncytotoxic toward L929 mouse fibroblasts. Kaolin and halloysite showed blood coagulation effects similar to that exhibited by zeolite, indicating that kaolin and halloysite are promising alternative hemostatic materials.

A Multiscale Model for Shear-Mediated Platelet Adhesion Dynamics: Correlating In Silico with In Vitro Results

Platelet adhesion to blood vessel walls is a key initial event in thrombus formation in both vascular disease processes and prosthetic cardiovascular devices. We extended a deformable multiscale model (MSM) of flowing platelets, incorporating Dissipative Particle Dynamics (DPD) and Coarse-Grained Molecular Dynamics (CGMD) describing molecular-scale intraplatelet constituents and their interaction with surrounding flow, to predict platelet adhesion dynamics under physiological flow shear stresses. Binding of platelet glycoprotein receptor Ibα (GPIbα) to von Willebrand factor (vWF) on the blood vessel wall was modeled by a molecular-level hybrid force field and validated with in vitro microchannel experiments of flowing platelets at 30 dyne/cm2. High frame rate videos of flipping platelets were analyzed with a Semi-Unsupervised Learning System (SULS) machine learning-guided imaging approach to segment platelet geometries and quantify adhesion dynamics parameters. In silico flipping dynamics followed in vitro measurements at 15 and 45 dyne/cm2 with high fidelity, predicting GPIbα-vWF bonding and debonding processes, distribution of bonds strength, and providing a biomechanical insight into initiation of the complex platelet adhesion process. The adhesion model and simulation framework can be further integrated with our established MSMs of platelet activation and aggregation to simulate initial mural thrombus formation on blood vessel walls.

In Vitro Measurements of Shear-Mediated Platelet Adhesion Kinematics as Analyzed through Machine Learning

Platelet adhesion to blood vessel walls in shear flow is essential to initiating the blood coagulation cascade and prompting clot formation in vascular disease processes and prosthetic cardiovascular devices. Validation of predictive adhesion kinematics models at the single platelet level is difficult due to gaps in high resolution, dynamic morphological data or a mismatch between simulation and experimental parameters. Gel-filtered platelets were perfused at 30 dyne/cm² in von Willebrand Factor (vWF)-coated microchannels, with flipping platelets imaged at high spatial and temporal resolution. A semi-unsupervised learning system (SULS), consisting of a series of convolutional neural networks, was used to segment platelet geometry, which was compared with expert-analyzed images. Resulting time-dependent rotational angles were smoothed with wavelet-denoising and shifting techniques to characterize the rotational period and quantify flipping kinematics. We observed that flipping platelets do not follow the previously-modeled modified Jefferey orbit, but are characterized by a longer lift-off and shorter reattachment period. At the juncture of the two periods, rotational velocity approached 257.48 ± 13.31 rad/s. Our SULS approach accurately segmented large numbers of moving platelet images to identify distinct adhesive kinematic characteristics which may further validate the physical accuracy of individual platelet motion in multiscale models of shear-mediated thrombosis.