Background Pulmonary hypertension ( PH ) results in increased right ventricular ( RV ) afterload and ventricular remodeling. Sacubitril/valsartan (sac/val) is a dual acting drug, composed of the neprilysin inhibitor sacubitril and the angiotensin receptor blocker valsartan, that has shown promising outcomes in reducing the risk of death and hospitalization for chronic systolic left ventricular heart failure. In this study, we aimed to examine if angiotensin receptor‐neprilysin inhibition using sac/val attenuates RV remodeling in PH . Methods and Results RV pressure overload was induced in Sprague–Dawley rats via banding the main pulmonary artery. Three different cohorts of controls, placebo‐treated PH , and sac/val‐treated PH were studied in a 21‐day treatment window. Terminal invasive hemodynamic measurements, quantitative histological analysis, biaxial mechanical testing, and constitutive modeling were employed to conduct a multiscale analysis on the effects of sac/val on RV remodeling in PH . Sac/val treatment decreased RV maximum pressures (29% improvement, P =0.002), improved RV contractile (30%, P =0.012) and relaxation (29%, P =0.043) functions, reduced RV afterload (35% improvement, P =0.016), and prevented RV ‐ pulmonary artery uncoupling. Furthermore, sac/val attenuated RV hypertrophy (16% improvement, P =0.006) and prevented transmural reorientation of RV collagen and myofibers ( P =0.011). The combined natriuresis and vasodilation resulting from sac/val led to improved RV biomechanical properties and prevented increased myofiber stiffness in PH (61% improvement, P =0.032). Conclusions Sac/val may prevent maladaptive RV remodeling in a pressure overload model via amelioration of RV pressure rise, hypertrophy, collagen, and myofiber reorientation as well as tissue stiffening both at the tissue and myofiber level.

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Pulmonary arterial hypertension (PAH) is a disease resulting in increased right ventricular (RV) afterload and RV remodeling. PAH results in altered RV structure and function at different scales from organ-level hemodynamics to tissue-level biomechanical properties, fiber-level architecture, and cardiomyocyte-level contractility. Biomechanical analysis of RV pathophysiology has drawn significant attention over the past years and recent work has found a close link between RV biomechanics and physiological function. Building upon previously developed techniques, biomechanical studies have employed multi-scale analysis frameworks to investigate the underlying mechanisms of RV remodeling in PAH and effects of potential therapeutic interventions on these mechanisms. In this review, we discuss the current understanding of RV structure and function in PAH, highlighting the findings from recent studies on the biomechanics of RV remodeling at organ, tissue, fiber, and cellular levels. Recent progress in understanding the underlying mechanisms of RV remodeling in PAH, and effects of potential therapeutics, will be highlighted from a biomechanical perspective. The clinical relevance of RV biomechanics in PAH will be discussed, followed by addressing the current knowledge gaps and providing suggested directions for future research.

Much of our understanding of the role of elbow ligaments to overall joint biomechanics has been developed through in vitro cadaver studies using joint motion simulators. The principle of superposition can be used to indirectly compute the force contributions of ligaments during prescribed motions. Previous studies have analyzed the contribution of different soft tissue structures to the stability of human elbow joints, but have limitations in evaluating the loads sustained by those tissues. This manuscript introduces a unique, hybrid experimental-computational technique for measuring and simulating the biomechanical contributions of ligaments to elbow joint kinematics and stability. In vitro testing of cadaveric joints is enhanced by the incorporation of fully parametric virtual ligaments, which are used in place of the native joint stabilizers to characterize the contribution of elbow ligaments during simple flexion-extension motions using the principle of superposition. Our results support previously reported findings that the anterior medial collateral ligament and the radial collateral ligament are the primary soft tissue stabilizers for the elbow joint. Tuned virtual ligaments employed in this study were able to restore the kinematics and laxity of elbows to within 2° of native joint behavior. The hybrid framework presented in this study demonstrates promising capabilities in measuring the biomechanical contribution of ligamentous structures to joint stability.

Right ventricular (RV) remodeling and longitudinal fiber reorientation in the setting of pulmonary hypertension (PH) affects ventricular structure and function, eventually leading to RV failure. Characterizing the kinematics of myocardial fibers helps better understanding the underlying mechanisms of fiber realignment in PH. In the current work, high-frequency ultrasound imaging and structurally-informed finite element (FE) models were employed for an exploratory evaluation of the stretch-induced kinematics of RV fibers. Image-based experimental evaluation of fiber kinematics in porcine myocardium revealed the capability of affine assumptions to effectively approximate myofiber realignment in the RV free wall. The developed imaging framework provides a noninvasive modality to quantify transmural RV myofiber kinematics in large animal models. FE modeling results demonstrated that chronic pressure overload, but not solely an acute rise in pressures, results in kinematic shift of RV fibers towards the longitudinal direction. Additionally, FE simulations suggest a potential protective role for concentric hypertrophy (increased wall thickness) against fiber reorientation, while eccentric hypertrophy (RV dilation) resulted in longitudinal fiber realignment. Our study improves the current understanding of the role of different remodeling events involved in transmural myofiber reorientation in PH. Future experimentations are warranted to test the model-generated hypotheses.