A Central Role for Monocyte-Platelet Interactions in Heart Failure

Heart failure (HF) is an increasingly prevalent and costly multifactorial syndrome with high morbidity and mortality rates. The exact pathophysiological mechanisms leading to the development of HF are not completely understood. Several emerging paradigms implicate cardiometabolic risk factors, inflammation, endothelial dysfunction, myocardial fibrosis, and myocyte dysfunction as key factors in the gradual progression from a healthy state to HF. Inflammation is now a recognized factor in disease progression in HF and a therapeutic target. Furthermore, the monocyte-platelet interaction has been highlighted as an important pathophysiological link between inflammation, thrombosis, endothelial activation, and myocardial malfunction. The contribution of monocytes and platelets to acute cardiovascular injury and acute HF is well established. However, their role and interaction in the pathogenesis of chronic HF are not well understood. In particular, the cross talk between monocytes and platelets in the peripheral circulation and in the vicinity of the vascular wall in the form of monocyte-platelet complexes (MPCs) may be a crucial element, which influences the pathophysiology and progression of chronic heart disease and HF. In this review, we discuss the role of monocytes and platelets as key mediators of cardiovascular inflammation in HF, the mechanisms of cell activation, and the importance of monocyte-platelet interaction and complexes in HF pathogenesis. Finally, we summarize recent information on pharmacological inhibition of inflammation and studies of antithrombotic strategies in the setting of HF that can inform opportunities for future work. We discuss recent data on monocyte-platelet interactions and the potential benefits of therapy directed at MPCs, particularly in the setting of HF with preserved ejection fraction.

Improved Real-time State-of-Charge Estimation of LiFePO4 Battery Based on a Novel Thermoelectric Model

Li-ion batteries have been widely used in electric vehicles, and battery internal state estimation plays an important role in the battery management system. However, it is technically challenging, in particular, for the estimation of the battery internal temperature and state-ofcharge (SOC), which are two key state variables affecting the battery performance. In this paper, a novel method is proposed for realtime simultaneous estimation of these two internal states, thus leading to a significantly improved battery model for realtime SOC estimation. To achieve this, a simplified battery thermoelectric model is firstly built, which couples a thermal submodel and an electrical submodel. The interactions between the battery thermal and electrical behaviours are captured, thus offering a comprehensive description of the battery thermal and electrical behaviour. To achieve more accurate internal state estimations, the model is trained by the simulation error minimization method, and model parameters are optimized by a hybrid optimization method combining a meta-heuristic algorithm and the least square approach. Further, timevarying model parameters under different heat dissipation conditions are considered, and a joint extended Kalman filter is used to simultaneously estimate both the battery internal states and time-varying model parameters in realtime. Experimental results based on the testing data of LiFePO4 batteries confirm the efficacy of the proposed method.