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Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).
Purpose: Impaired paravascular drainage of β-Amyloid (Aβ) has been proposed as a contributing cause for sporadic Alzheimer’s disease (AD), as decreased cerebral blood vessel pulsatility and subsequently reduced propulsion in this pathway could lead to the accumulation and deposition of Aβ in the brain. Therefore, we hypothesized that there is an increased impairment in pulsatility across AD spectrum.
Patients and Methods: Using transcranial color-coded duplex sonography (TCCS) the resistance and pulsatility index (RI; PI) of the middle cerebral artery (MCA) in healthy controls (HC, n=14) and patients with AD dementia (ADD, n=12) were measured. In a second step, we extended the sample by adding patients with mild cognitive impairment (MCI) stratified by the presence (MCI-AD, n=8) or absence of biomarkers (MCI-nonAD, n=8) indicative for underlying AD pathology, and compared RI and PI across the groups. To control for atherosclerosis as a confounder, we measured the arteriolar-venular-ratio of retinal vessels.
Results: Left and right RI (p=0.020; p=0.027) and left PI (p=0.034) differed between HC and ADD controlled for atherosclerosis with AUCs of 0.776, 0.763, and 0.718, respectively. The RI and PI of MCI-AD tended towards ADD, of MCI-nonAD towards HC, respectively. RIs and PIs were associated with disease severity (p=0.010, p=0.023).
Conclusion: Our results strengthen the hypothesis that impaired pulsatility could cause impaired amyloid clearance from the brain and thereby might contribute to the development of AD. However, further studies considering other factors possibly influencing amyloid clearance as well as larger sample sizes are needed.
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
A new in vitro tool to investigate cardiac contractility under physiological mechanical conditions
(2019)
Production and Characterization of Porous Fibroin Scaffolds for Regenerative Medical Application
(2019)
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.