## 2 Topics and Results
### Recent Advances in Modeling Diabetic Blood Platelets  
#### 2.6.1 Computational Platelet Modeling in DM2  
DM2 creates the conditions for complex thrombotic pathologies. Extensive experimental, theoretical, and computational studies have been conducted to determine PLT properties, as well as their interaction and thrombus formation [38]. Advanced multi-scale models were developed to better understand the role of various factors in flow-mediated transport, PLT deposition, coagulation kinetics, and their overall effect on thrombus formation. Blood shear rate is an important factor controlling platelet distribution in blood vessels [22; 38; 39; 40; 41].  
[PERSON] et al. (2018) simulated blood with hematocrit at 20% (for controlling different blood cell suspensions) [22; 42]. The results indicated that \"larger platelets\" are more likely to migrate toward the vessel wall. They suggested a roughly 6-10% decrease in platelet migration rate when the wall shear rate decreased from 1000 s\({}^{-1}\) to 600 s\({}^{-1}\).  
Weakened platelet migration at lower wall shear rates is probably due to reduced collision between platelets and RBSs [38].  
Continuum-based partial differential equation (PDE) models [38] have been used to describe the time and spatial dependence of thrombin generation, fibrin formation, and thrombus growth under various flow conditions. However, thrombosis development simulations in diabetes require the discrete representation of the blood flow at a cellular level in computational models. To present and simulate micro-scale interactions between different types of blood cells, numerous mathematical and computational models have been designed [39; 40; 41]. Lattice Boltzmann and lattice kinetic Monte Carlo models have been developed to simulate platelet activation and aggregation by treating PLTs as particles under flow [43]. However, applications for these hybrid models have been mostly limited to two dimensions due to model complexity and significant computational costs.  
In future modeling systems, a multi-scale approach would facilitate patient-specific simulation of thrombosis/thrombogenesis in different hemodynamic conditions with different pharmacological treatments.  
[PERSON] and [PERSON] (2016) [44] performed a systematic study of RBC and PLT transport considering different levels of constriction, controlling hematocrit and flow rates. In their work, normal and diabetic RBC and PLT models were employed to simulate normal and diabetic blood flow in rectangular channels. In the numerical framework, four key sub-processes of blood clotting were combined: hydrodynamics, PLT micromechanics, transport of PLT coagulation factors, and registering coagulation reactions. To consider the coagulation cascade, the authors implemented the mathematical model of [PERSON] et al. (2008) [45].  
[PERSON] and [PERSON] (2016) [46] concluded that higher levels of blood vessel constriction (stenosis) and elevated vessel wall shear rates led to significantly enhanced platelet migration. This model, with modifications, could explain the experimental data of active PLT aggregation in a postvascular stenosis segment of the vessel wall in different pathological states (DM2, atherosclerosis, etc.).  
Computational modeling has emerged as a powerful tool for investigating pathological processes in DM2. However, many unexplored areas and different experimental conditions must be targeted in future research on the topic.  
In the cellular, tissue, and organ-specific modeling of diabetic blood cells and injured microvasculature (complications such as retinopathy, nephropathy, microangiopathy, etc.), micro-aneurisms should be obtained simultaneously with edemas and/or hemorrhages, directly affecting organ functions [20; 41; 46; 47].  
Instead of great advantages in bioinformatics and biomechanics, there is a lack of computational models in the medical scientific literature to connect blood glucose level prediction in diabetic patients with PLT hematological and hemorheological biomarkers [21; 22].