Triple-marker cardiac MRI detects sequential tissue changes of healing myocardium after a hydrogel-based therapy

Regenerative therapies based on injectable biomaterials, hold an unparalleled potential for treating myocardial ischemia. Yet, noninvasive evaluation of their efficacy has been lagging behind. Here, we report the development and longitudinal application of multiparametric cardiac magnetic resonance imaging (MRI) to evaluate a hydrogel-based cardiac regenerative therapy. A pH-switchable hydrogel was loaded with slow releasing insulin growth factor 1 and vascular endothelial growth factor, followed by intramyocardial injection in a mouse model of ischemia reperfusion injury. Longitudinal cardiac MRI assessed three hallmarks of cardiac regeneration: angiogenesis, resolution of fibrosis and (re)muscularization after infarction. The multiparametric approach contained dynamic contrast enhanced MRI that measured improved vessel features by assessing fractional blood volume and permeability*surface area product, T1-mapping that displayed reduced fibrosis, and tagging MRI that showed improved regional myocardial strain in hydrogel treated infarcts. Finally, standard volumetric MRI demonstrated improved left ventricular functioning in hydrogel treated mice followed over time. Histology confirmed MR-based vessel features and fibrotic measurements. Our novel triple-marker strategy enabled detection of ameliorated regeneration in hydrogel treated hearts highlighting the translational potential of these longitudinal MRI approaches

Generation of human motor units with functional neuromuscular junctions in microfluidic devices

Neuromuscular junctions (NMJs) are specialized synapses between the axon of the lower motor neuron and the muscle facilitating the engagement of muscle contraction. In motor neuron disorders, such as amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA), NMJs degenerate, resulting in muscle atrophy and progressive paralysis. The underlying mechanism of NMJ degeneration is unknown, largely due to the lack of translatable research models. This study aimed to create a versatile and reproducible in vitro model of a human motor unit with functional NMJs. Therefore, human induced pluripotent stem cell (hiPSC)-derived motor neurons and human primary mesoangioblast (MAB)-derived myotubes were co-cultured in commercially available microfluidic devices. The use of fluidically isolated micro-compartments allows for the maintenance of cell-specific microenvironments while permitting cell-to-cell contact through microgrooves. By applying a chemotactic and volumetric gradient, the growth of motor neuron-neurites through the microgrooves promoting myotube interaction and the formation of NMJs were stimulated. These NMJs were identified immunocytochemically through co-localization of motor neuron presynaptic marker synaptophysin (SYP) and postsynaptic acetylcholine receptor (AChR) marker α-bungarotoxin (Btx) on myotubes and characterized morphologically using scanning electron microscopy (SEM). The functionality of the NMJs was confirmed by measuring calcium responses in myotubes upon depolarization of the motor neurons. The motor unit generated using standard microfluidic devices and stem cell technology can aid future research focusing on NMJs in health and disease

Online Training of an Opto-Electronic Reservoir Computer

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals. Its analog implementations equal and sometimes outperform other digital algorithms on a series of benchmark tasks. Their performance can be increased by switching from offline to online training method. Here we present the first online trained opto-electronic reservoir computer. The system is tested on a channel equalisation task and the algorithm is executed by an FPGA chip. We report performances close to previous implementations and demonstrate the benefits of online training on a non-stationary task that could not be easily solved using offline methods.info:eu-repo/semantics/publishe

Brain energy rescue:an emerging therapeutic concept for neurodegenerative disorders of ageing

The brain requires a continuous supply of energy in the form of ATP, most of which is produced from glucose by oxidative phosphorylation in mitochondria, complemented by aerobic glycolysis in the cytoplasm. When glucose levels are limited, ketone bodies generated in the liver and lactate derived from exercising skeletal muscle can also become important energy substrates for the brain. In neurodegenerative disorders of ageing, brain glucose metabolism deteriorates in a progressive, region-specific and disease-specific manner — a problem that is best characterized in Alzheimer disease, where it begins presymptomatically. This Review discusses the status and prospects of therapeutic strategies for countering neurodegenerative disorders of ageing by improving, preserving or rescuing brain energetics. The approaches described include restoring oxidative phosphorylation and glycolysis, increasing insulin sensitivity, correcting mitochondrial dysfunction, ketone-based interventions, acting via hormones that modulate cerebral energetics, RNA therapeutics and complementary multimodal lifestyle changes

Three-dimensional monitoring of soil water content in a maize field using Electrical Resistivity Tomography

A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that Electrical Resistivity Tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). This study was conducted (i) to check and validate how ERT is able to monitor SWC distribution in a maize field during the late growing season; and (ii) to investigate how maize plants and rainfall affect the dynamics of SWC distribution. Time Domain Reflectometry (TDR) measurements were used to validate ERT-inverted SWC values. Evolution of water mass balance was also calculated to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. It is observed that ERT was able to give the same average SWC as TDR (R2 = 0.98). In addition, ERT gives better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows for the discrimination of SWC heterogeneities. The SWC distribution showed that alternation of maize rows and inter-rows was the main influencing factor of the SWC distribution. The drying patterns were linked to the root profiles, with drier zones under the maize rows. During short periods, with negligible rainfall, the SWC decrease took place mainly in the two upper soil horizons and in the inter-row area. In contrast, rainfall increased the SWC mostly under the maize rows and in the upper soil layer. Nevertheless, the total amount of rainfall during the growing season was not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, there was hardly any SWC redistribution from maize rows to inter-rows. Yet, lateral redistribution from inter-rows to maize rows induced by potential gradient generates SWC decrease in the inter-row area and in the deeper soil horizons

AirTAP Briefings (Winter 2019, vol. 19, no. 1)

Articles include: Is more ice the new normal?; TPT, MnDOT create drone safety video; An airport story’s: Granite Falls Municipal Airport; Mankato lighting renovations make taxiways brighter, easier to repair; Annual conference heading to Willmar; More aviation event

Eléments de bilan du programme quinquennal 1998-2003 et réflexions

Bilan établi sur base d'un travail préparatoire de la direction générale de la santé et des quatre services communautaires de promotion de la santé (ULG-APES, ULB-PROMES, UCL-RESO, Question santé asbl

Reservoir Computing: Quo Vadis?

Reservoir Computing (RC) is an umbrella term for adaptive computational paradigms that rely on an excitable dynamical system, also called the reservoir. The paradigms have been shown to be particularly promising for temporal signal processing. RC was also explored as a potential candidate for emerging nanoscale architectures. In this article we reflect on the current state of RC and muse about its future. In particular, we propose a set of open problems that we think need to be addressed in order to make RC more mainstream