In the literature: November 2023 highlights

Click here to read some interesting recently published papers from our community. If you have published an article in the field of in silico medicine, send it to us: we will include it in this section of the newsletter!

PLOS Computational Biology: External mechanical loading overrules cell-cell mechanical communication in sprouting angiogenesis during early bone regeneration

Chiara Dazzi et al

Abstract

Sprouting angiogenesis plays a key role during bone regeneration. For example, insufficient early revascularization of the injured site can lead to delayed or non-healing. During sprouting, endothelial cells are known to be mechano-sensitive and respond to local mechanical stimuli. Endothelial cells interact and communicate mechanically with their surroundings, such as outer-vascular stromal cells, through cell-induced traction forces. In addition, external physiological loads act at the healing site, resulting in tissue deformations and impacting cellular arrangements. How these two distinct mechanical cues (cell-induced and external) impact angiogenesis and sprout patterning in early bone healing remains however largely unknown. Therefore, the aim of this study was to investigate the relative role of externally applied and cell-induced mechanical signals in driving sprout patterning at the onset of bone healing. To investigate cellular self-organisation in early bone healing, an in silico model accounting for the mechano-regulation of sprouting angiogenesis and stromal cell organization was developed. Computer model predictions were compared to in vivo experiments of a mouse osteotomy model stabilized with a rigid or a semirigid fixation system. We found that the magnitude and orientation of principal strains within the healing region can explain experimentally observed sprout patterning, under both fixation conditions. Furthermore, upon simulating the selective inhibition of either cell-induced or externally applied mechanical cues, external mechanical signals appear to overrule the mechanical communication acting on a cell-cell interaction level. Such findings illustrate the relevance of external mechanical signals over the local cell-mediated mechanical cues and could be used in the design of fracture treatment strategies for bone regeneration.

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Journal of Bone and Mineral Research: Reduced Bone Regeneration in Rats With Type 2 Diabetes Mellitus as a Result of Impaired Stromal Cell and Osteoblast Function—A Computer Modeling Study

Mahdi Jaber et al

Abstract

Bone has the fascinating ability to self-regenerate. However, under certain conditions, such as type 2 diabetes mellitus (T2DM), this ability is impaired. T2DM is a chronic metabolic disease known by the presence of elevated blood glucose levels that is associated with reduced bone regeneration capability, high fracture risk, and eventual non-union risk after a fracture. Several mechanical and biological factors relevant to bone regeneration have been shown to be affected in a diabetic environment. However, whether impaired bone regeneration in T2DM can be explained due to mechanical or biological alterations remains unknown. To elucidate the relevance of either one, the aim of this study was to investigate the relative contribution of T2DM-related alterations on either cellular activity or mechanical stimuli driving bone regeneration. A previously validated in silico computer modeling approach that was capable of explaining bone regeneration in uneventful conditions of healing was further developed to investigate bone regeneration in T2DM. Aspects analyzed included the presence of mesenchymal stromal cells (MSCs), cellular migration, proliferation, differentiation, apoptosis, and cellular mechanosensitivity. To further verify the computer model findings against in vivo data, an experimental setup was replicated, in which regeneration was compared in healthy and diabetic after a rat femur bone osteotomy stabilized with plate fixation. We found that mechanical alterations had little effect on the reduced bone regeneration in T2DM and that alterations in MSC proliferation, MSC migration, and osteoblast differentiation had the highest effect. In silico predictions of regenerated bone in T2DM matched qualitatively and quantitatively those from ex vivo μCT at 12 weeks post-surgery when reduced cellular activities reported in previous in vitro and in vivo studies were included in the model. The presented findings here could have clinical implications in the treatment of bone fractures in patients with T2DM. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

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International Journal for Numerical Methods in Engineering: Generation of synthetic aortic valve stenosis geometries for in silico trials.

Sabine Verstraeten et al

Abstract

In silico trials are a promising way to increase the efficiency of the development, and the time to market of cardiovascular implantable devices. The development of transcatheter aortic valve implantation (TAVI) devices, could benefit from in silico trials to overcome frequently occurring complications such as paravalvular leakage and conduction problems. To be able to perform in silico TAVI trials virtual cohorts of TAVI patients are required. In a virtual cohort, individual patients are represented by computer models that usually require patient-specific aortic valve geometries. This study aimed to develop a virtual cohort generator that generates anatomically plausible, synthetic aortic valve stenosis geometries for in silico TAVI trials and allows for the selection of specific anatomical features that influence the occurrence of complications. To build the generator, a combination of non-parametrical statistical shape modeling and sampling from a copula distribution was used. The developed virtual cohort generator successfully generated synthetic aortic valve stenosis geometries that are comparable with a real cohort, and therefore, are considered as being anatomically plausible. Furthermore, we were able to select specific anatomical features with a sensitivity of around 90%. The virtual cohort generator has the potential to be used by TAVI manufacturers to test their devices. Future work will involve including calcifications to the synthetic geometries, and applying high-fidelity fluid–structure-interaction models to perform in silico trials.

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Date: 28/11/2023 | Tag: | News: 1522 of 1554
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