Simulating realistic musculoskeletal dynamics is critical to understanding neural control of muscle activity evoked in sensorimotor feedback responses that have inherent neural transmission delays. Thus, the initial mechanical response of muscles to perturbations in the absence of any change in muscle activity determines which corrective neural responses are required to stabilize body posture. Muscle short-range stiffness, a history-dependent property of muscle that causes a rapid and transient rise in muscle force upon stretch, likely affects musculoskeletal dynamics in the initial mechanical response to perturbations. Here we identified the contributions of short-range stiffness to joint torques and angles in the initial mechanical response to support surface translations using dynamic simulation. We developed a dynamic model of muscle short-range stiffness to augment a Hill-type muscle model. Our simulations show that short-range stiffness can provide stability against external perturbations during the neuromechanical response delay. Assuming constant muscle activation during the initial mechanical response, including muscle short-range stiffness was necessary to account for the rapid rise in experimental sagittal plane knee and hip joint torques that occurs simultaneously with very small changes in joint angles and reduced root mean square errors between simulated and experimental torques by 56% and 47%, respectively. Moreover, forward simulations lacking short-range stiffness produced unreasonably large joint angle changes during the initial response. Using muscle models accounting for short-range stiffness along with other aspects of history-dependent muscle dynamics may be important to advance our ability to simulate inherently unstable human movements based on principles of neural control and biomechanics.
Neuromusculoskeletal models solve the basic problem of determining how the body moves under the influence of external and internal forces. Existing biomechanical modeling programs often emphasize dynamics with the goal of finding a feed-forward neural program to replicate experimental data or of estimating force contributions or individual muscles. The computation of rigid-body dynamics, muscle forces, and activation of the muscles are often performed separately. We have developed an intrinsically forward computational platform (Neuromechanic, www.neuromechanic.com) that explicitly represents the interdependencies among rigid body dynamics, frictional contact, muscle mechanics, and neural control modules. This formulation has significant advantages for optimization and forward simulation, particularly with application to neural controllers with feedback or regulatory features. Explicit inclusion of all state dependencies allows calculation of system derivatives with respect to kinematic states and muscle and neural control states, thus affording a wealth of analytical tools, including linearization, stability analyses and calculation of initial conditions for forward simulations. In this review, we describe our algorithm for generating state equations and explain how they may be used in integration, linearization, and stability analysis tools to provide structural insights into the neural control of movement.
Objective. High morphological variability magnitude (MVM) and microvolt T wave alternans (TWA) within an electrocardiogram (ECG) signifies increased electrical instability and risk of sudden cardiac death. However, the influence of breathing rate (BR), heart rate (HR), and signal-to-noise ratio (SNR) is unknown and may inflate measured values. Approach. We synthesize ECGs with morphologies derived from the Physikalisch-Technische Bundesanstalt Database. We calculate MVM and TWA at varying BRs, HRs and SNRs. We compare the MVM and TWA of signal with versus without breathing at varying HRs and SNRs. We then quantify the percentage of MVM and TWA estimates affected by BR and HR in a healthy population and assess the effect of removing these affected estimates on a method for classifying individuals with and without post-traumatic stress disorder (PTSD). Main results. For signals with high SNR (>15 dB), MVM is significantly increased when BRs are > 9 respirations/minute (rpm) and HRs are < 100 beats/minute (bpm). Increased TWAs are detected for HR/BR pairs of 60/15, 60/30 and 120/30 bpm/rpm. For 18 healthy participants, 8.33% of TWA windows and 66.76% of MVM windows are affected by BR and HR. On average, the number of windows with TWA elevations > 47 μV decreases by 23% after excluding regions with significant BR and HR effect. Adding HR and BR to a morphological variability feature increases the classification performance by 6% for individuals with and without PTSD. Significance. Physiological BR and HR significantly increase MVM and TWA, indicating that BR and HR should be considered separately as confounders. The code for this work has been released as part of an open-source toolbox.
Formins promote actin assembly and are involved in force-dependent cytoskeletal remodeling. However, how force alters the formin functions still needs to be investigated. Here, using atomic force microscopy and biomembrane force probe, we investigated how mechanical force affects formin-mediated actin interactions at the level of single molecular complexes. The biophysical parameters of G-actin/G-actin (GG) or G-actin/F-actin (GF) interactions were measured under force loading in the absence or presence of two C-terminal fragments of the mouse formin mDia1: mDia1Ct that contains formin homology 2 domain (FH2) and diaphanous autoregulatory domain (DAD) and mDia1Ct-ΔDAD that contains only FH2. Under force-free conditions, neither association nor dissociation kinetics of GG and GF interactions were significantly affected by mDia1Ct or mDia1Ct-ΔDAD. Under tensile forces (0–7 pN), the average lifetimes of these bonds were prolonged and molecular complexes were stiffened in the presence of mDia1Ct, indicating mDia1Ct association kinetically stabilizes and mechanically strengthens bonds of the dimer and at the end of the F-actin under force. Interestingly, mDia1Ct-ΔDAD prolonged the lifetime of GF but not GG bond under force, suggesting the DAD domain is critical for mDia1Ct to strengthen GG interaction. These data unravel the mechanochemical coupling in formin-induced actin assembly and provide evidence to understand the initiation of formin-mediated actin elongation and nucleation.
Purpose: Pediatric and adult patients with sickle cell anemia (SCA) are at increased risk of stroke and cerebrovascular accident. In the general adult population, there is a relationship between arterial hemodynamics and pathology; however, this relationship in SCA patients remains to be elucidated. The aim of this work was to characterize circle of Willis hemodynamics in patients with SCA and quantify the impact of viscosity choice on pathophysiologically-relevant hemodynamics measures. Methods: Based on measured vascular geometries, time-varying flow rates, and blood parameters, detailed patient-specific simulations of the circle of Willis were conducted for SCA patients (n = 6). Simulations quantified the impact of patient-specific and standard blood viscosities on wall shear stress (WSS). Results: These results demonstrated that use of a standard blood viscosity introduces large errors into the estimation of pathophysiologically-relevant hemodynamic parameters. Standard viscosity models overpredicted peak WSS by 55% and 49% for steady and pulsatile flow, respectively. Moreover, these results demonstrated non-uniform, spatial patterns of positive and negative WSS errors related to viscosity, and standard viscosity simulations overpredicted the time-averaged WSS by 32% (standard deviation = 7.1%). Finally, differences in shear rate demonstrated that the viscosity choice alters the simulated near-wall flow field, impacting hemodynamics measures. Conclusions: This work presents simulations of circle of Willis arterial flow in SCA patients and demonstrates the importance and feasibility of using a patient-specific viscosity in these simulations. Accurately characterizing cerebrovascular hemodynamics in SCA populations has potential for elucidating the pathophysiology of large-vessel occlusion, aneurysms, and tissue damage in these patients.
A number of clinical, in vitro and computational studies have shown the potential for thromboembolic complications in bileaflet mechanical heart valves (BMHV), primarily due to the complex and unsteady flows in the valve hinges. These studies have focused on quantitative and qualitative parameters such as velocity magnitude, turbulent shear stresses, vortex formation, and platelet activation to identify potential for blood damage. However, experimental characterization of the whole flow fields within the valve hinges has not yet been conducted. This information can be utilized to investigate instantaneous damage to blood elements and also to validate numerical studies focusing on the hinge's complex fluid dynamics. The objective of this study was therefore to develop a high-resolution imaging system to characterize the flow fields and global velocity maps in a BMHV hinge. In this study, the steady leakage hinge flow fields representing the diastolic phase during the cardiac cycle in a 23 mm St. Jude Medical regent BMHV in the aortic position were characterized using a two-dimensional micro particle image velocimetry system. Diastolic flow was simulated by imposing a static pressure head on the aortic side. Under these conditions, a reverse flow jet from the aortic to the ventricular side was observed with velocities in the range of 1.47-3.24 m/s, whereas low flow regions were observed on the ventricular side of the hinge with viscous shear stress magnitude up to 60 N/m2. High velocities and viscous shearing may be associated with platelet activation and hemolysis, while low flow zones can cause thrombosis due to increased residence time in the hinge. Overall, this study provides a high spatial resolution experimental technique to map the fluid velocity in the BMHV hinge, which can be extended to investigate micron-scale flow domains in various prosthetic devices under different hemodynamic conditions.
This study presents a new algorithm to adaptively detect change points of functional connectivity networks in the brain. It uses scans from resting-state functional magnetic resonance imaging (rsfMRI) which is one of the major tools to investigate intrinsic brain functionality. Different regions of the resting brain form networks that change states within a few seconds to minutes. The change points of these networks are different in normal and disordered brain functions and their understanding can help in identification of brain disorders. These changes arise from many unknown factors and extraction of these change points is one of the the major challenges in the absence of any ground truth. Our algorithm detects these change points adaptively by computing sum of absolute sign differences of adjacent images in rsfMRI scans using measures from image and video processing. We demonstrate the effectiveness of the proposed algorithm and show that these change points can be detected reliably in both task-based and resting-state networks. The outcomes also point to new directions for future work.
Memory B cells originate in response to antigenic stimulation in B-cell follicles of secondary lymphoid organs where naive B cells undergo maturation within a subanatomical microenvironment, the germinal centers. The understanding of memory B-cell immunology and its regulation is based primarily on sophisticated experiments that involve mouse models. To date, limited evidence exists on whether memory B cells can be successfully engineered ex vivo, specifically using biomaterials-based platforms that support the growth and differentiation of B cells. Here, we report the characterization of a recently reported maleimide-functionalized poly(ethylene glycol) (PEG) hydrogels as immune organoids towards the development of early memory B-cell phenotype and germinal center-like B cells. We demonstrate that the use of interleukin 9 (IL9), IL21, and bacterial antigen presentation as outer membrane-bound fragments drives the conversion of naive, primary murine B cells to early memory phenotype in ex vivo immune organoids. These findings describe the induction of early memory B-cell-like phenotype in immune organoids and highlight the potential of synthetic organoids as a platform for the future development of antigen-specific bona fide memory B cells for the study of the immune system and generation of therapeutic antibodies.
Cardiovascular simulations have great potential as a clinical tool for planning and evaluating patient-specific treatment strategies for those suffering from congenital heart diseases, specifically Fontan patients. However, several bottlenecks have delayed wider deployment of the simulations for clinical use; the main obstacle is simulation cost. Currently, time-averaged clinical flow measurements are utilized as numerical boundary conditions (BCs) in order to reduce the computational power and time needed to offer surgical planning within a clinical time frame. Nevertheless, pulsatile blood flow is observed in vivo, and its significant impact on numerical simulations has been demonstrated. Therefore, it is imperative to carry out a comprehensive study analyzing the sensitivity of using time-averaged BCs. In this study, sensitivity is evaluated based on the discrepancies between hemodynamic metrics calculated using time-averaged and pulsatile BCs; smaller discrepancies indicate less sensitivity. The current study incorporates a comparison between 3D patient-specific CFD simulations using both the time-averaged and pulsatile BCs for 101 Fontan patients. The sensitivity analysis involves two clinically important hemodynamic metrics: hepatic flow distribution (HFD) and indexed power loss (iPL). Paired demographic group comparisons revealed that HFD sensitivity is significantly different between single and bilateral superior vena cava cohorts but no other demographic discrepancies were observed for HFD or iPL. Multivariate regression analyses show that the best predictors for sensitivity involve flow pulsatilities, time-averaged flow rates, and geometric characteristics of the Fontan connection. These predictors provide patient-specific guidelines to determine the effectiveness of analyzing patient-specific surgical options with time-averaged BCs within a clinical time frame.
We present a calculation of the amide I′ infrared (IR) spectra of the folded, unfolded, and intermediate states of the WW domain Fip35, a model system for β-sheet folding. Using an all-atom molecular dynamics simulation in which multiple folding and unfolding events take place we identify six conformational states and then apply perturbed matrix method quantum-mechanical calculations to determine their amide I′ IR spectra. Our analysis focuses on two states previously identified as Fip35 folding intermediates and suggests that a three-stranded core similar to the folded state core is the main source of the spectroscopic differences between the two intermediates. In particular, we propose a hypothesis for why folding via one of these intermediates was not experimentally observed by IR T-jump.