Discontinuous Galerkin for the heterodimer model of prion dynamics in Parkinson's disease

Neurodegenerative diseases have a significant global impact affecting millions of individuals worldwide. Some of them, known as proteinopathies, are characterized by the accumulation and propagation of toxic proteins, known as prions. Alzheimer's and Parkinson's diseases are relevant of protheinopathies. Mathematical models of prion dynamics play a crucial role in understanding disease progression and could be of help to potential interventions. This article focuses on the heterodimer model: a system of two partial differential equations that describe the evolution of healthy and misfolded proteins. In particular, we propose a space discretization based on a Discontinuous Galerkin method on polygonal/polyhedral grids, which provides flexibility in handling meshes of complex brain geometries. Concerning the semi-discrete formulation we prove stability and a-priori error estimates. Next, we adopt a $\vartheta$-method scheme for time discretization. Some convergence tests are performed to confirm the theoretical bounds and the ability of the method to approximate travelling wave solutions. The proposed scheme is also tested to simulate the spread of $\alpha$-synuclein in a realistic test case of Parkinson's disease in a two-dimensional sagittal brain section geometry reconstructed from medical images

Numerical Modelling of the Brain Poromechanics by High-Order Discontinuous Galerkin Methods

We introduce and analyze a discontinuous Galerkin method for the numerical modelling of the equations of Multiple-Network Poroelastic Theory (MPET) in the dynamic formulation. The MPET model can comprehensively describe functional changes in the brain considering multiple scales of fluids. Concerning the spatial discretization, we employ a high-order discontinuous Galerkin method on polygonal and polyhedral grids and we derive stability and a priori error estimates. The temporal discretization is based on a coupling between a Newmark $\beta$-method for the momentum equation and a $\theta$-method for the pressure equations. After the presentation of some verification numerical tests, we perform a convergence analysis using an agglomerated mesh of a geometry of a brain slice. Finally we present a simulation in a three dimensional patient-specific brain reconstructed from magnetic resonance images. The model presented in this paper can be regarded as a preliminary attempt to model the perfusion in the brain

Discontinuous Galerkin Methods for Fisher-Kolmogorov Equation with Application to α\alpha-Synuclein Spreading in Parkinson's Disease

The spreading of prion proteins is at the basis of brain neurodegeneration. The paper deals with the numerical modelling of the misfolding process of $\alpha$-synuclein in Parkinson's disease. We introduce and analyze a discontinuous Galerkin method for the semi-discrete approximation of the Fisher-Kolmogorov (FK) equation that can be employed to model the process. We employ a discontinuous Galerkin method on polygonal and polyhedral grids (PolyDG) for space discretization, which allows us to accurately simulate the wavefronts typically observed in the prionic spreading. We prove stability and a priori error estimates for the semi-discrete formulation. Next, we use a Crank-Nicolson scheme to advance in time. For the numerical verification of our numerical model, we first consider a manufactured solution, and then we consider a case with wavefront propagation in two-dimensional polygonal grids. Next, we carry out a simulation of $\alpha$-synuclein spreading in a two-dimensional brain slice in the sagittal plane with a polygonal agglomerated grid that takes full advantage of the flexibility of PolyDG approximation. Finally, we present a simulation in a three-dimensional patient-specific brain geometry reconstructed from magnetic resonance images.Comment: arXiv admin note: text overlap with arXiv:2210.0227

Combining deep learning and machine learning for the automatic identification of hip prosthesis failure: Development, validation and explainability analysis

Aim: Revision hip arthroplasty has a less favorable outcome than primary total hip arthroplasty and an understanding of the timing of total hip arthroplasty failure may be helpful. The aim of this study is to develop a combined deep learning (DL) and machine learning (ML) approach to automatically detect hip prosthetic failure from conventional plain radiographs. Methods: Two cohorts of patients (of 280 and 352 patients) were included in the study, for model development and validation, respectively. The analysis was based on one antero-posterior and one lateral radiographic view obtained from each patient during routine post-surgery follow-up. After pre-processing, three images were obtained: the original image, the acetabulum image and the stem image. These images were analyzed through convolutional neural networks aiming to predict prosthesis failure. Deep features of the three images were extracted for each model and two feature-based pipelines were developed: one utilizing only the features of the original image (original image pipeline) and the other concatenating the features of the three images (3-image pipeline). The obtained features were either used directly or reduced through principal component analysis. Both support vector machine (SVM) and random forest (RF) classifiers were considered for each pipeline. Results: The SVM applied to the 3-image pipeline provided the best performance, with an accuracy of 0.958 +/- 0.006 in the internal validation and an F1-score of 0.874 in the external validation set. The explainability analysis, besides identifying the features of the complete original images as the major contributor, highlighted the role of the acetabulum and stem images on the prediction. Conclusions: This study demonstrated the potentialities of the developed DL-ML procedure based on plain radiographs in the detection of the failure of the hip prosthesis

MICROWAVE-ASSISTED BRUCITE AND TALC REACTIONS WITH CO2 AS A PROXY FOR CARBON CAPTURE AND STORAGE BY SERPENTINE

In the last decades many studies have been focusing on Carbon Capture and Storage (CCS) to find a possible remedy to reduce the large increase of anthropogenic carbon dioxide (CO ). Mineral Carbonation (MC) is a potential solution for almost irreversible chemical long-term CCS. It concerns the combination of CaO and MgO with CO forming spontaneously and exothermically dolomite and magnesite. However, kinetic barriers pose sever limitations for the practical exploitation of this reaction. High fractions of MgO are available in silicates such as olivine, orthopyroxene, clinopyroxene and serpentine. To date, data reported that serpentine polymorphs, above all antigorite, is an excellent candidate for fixing the CO as the reaction efficiency is approximately 92% compared to lizardite (40%) and olivine (66%). This is due to the surface reactivity of approximately 18.7 m /g for the dehydrated antigorite compared to10.8 m /g for dehydrated lizardite and 4.6 m /g for olivine. The microwave assisted process for CCS is an innovative technology that can be employed to catalyze the reaction through thermal and non-thermal mechanisms. Some pioneering tests of direct carbonation by microwave hydrothermal equipment have been performed on olivine, lizardite and chrysotile powders [1] but not on antigorite. The structure of serpentine is characterized by corrugated stacked layers of silica and brucite. For this reason, MC involves dissolution of SiO layers, dissolution/dehydration of Mg(OH) layers, and precipitation of magnesium carbonate. To address the chemical response of the single phases, experiments have been performed by both a local microwave-source acting locally on a specific crystal surface and a volume source interacting with an ensemble of grains on synthetic powders and single crystals of pure brucite and talc. In a second step, treatments have been extended to chrysotile, lizardite and antigorite. A characterization of the mechanism and kinetics were performed by scanning probe microscopy on the surface of single crystals phases, supported by Raman spectroscopy and by Scanning and Transmission Electron Microscopy study performed on micro- and nano-sized grains. [1] White, et al. Reaction mechanisms of magnesium silicates with carbon dioxide in microwave fields. Final Report to the U.S. Department ofEnergy, National Energy Technology Laboratory (2004

Intractable coronary fibromuscular dysplasia leading to end‐stage heart failure and fatal heart transplantation

Coronary fibromuscular dysplasia is uncommon, and even rarer its unstable and recurrent course. We present the unique case of a 52-year-old woman who underwent in total 12 coronary angiographies and three percutaneous coronary intervention within 24 months because of repetitive acute coronary syndromes due to refractory spasm, dissection, restenosis all leading to end-stage heart failure, and heart transplantation. The patient died 12 days after the heart transplantation complicated by intraoperative acute thrombotic occlusion of left anterior descending artery of the graft despite normal pretransplant coronary angiography. Autopsy of the recipient heart confirmed coronary fibromuscular dysplasia with massive intimal hyperplasia and restenosis

Prophylactic and postexposure efficacy of a potent human monoclonal antibody against MERS coronavirus

Middle East Respiratory Syndrome coronavirus (MERS-CoV) causes severe respiratory disease with a high mortality rate. There is no licensed vaccine or antiviral for MERS. Here we isolated for the first time, to our knowledge, a potent MERS-CoV–neutralizing antibody from memory B cells of an infected individual. This antibody binds to a novel site on the viral Spike protein, neutralizes by interfering with the binding to the cellular receptor CD26, and is highly effective both in prophylaxis and in therapy in a relevant mouse model. This antibody can be developed for prophylaxis, for postexposure prophylaxis, or for the treatment of severe MERS-CoV infections

Causes of unrest at silicic calderas in the East African Rift: new constraints from InSAR and soil-gas chemistry at Aluto volcano, Ethiopia

This work is a contribution to the Natural Environment Research Council (NERC) funded RiftVolc project (NE/L013932/1, Rift volcanism: past, present, and future). W.H., J.B., T.A.M., and D.M.P. are supported by and contribute to the NERC Centre for the Observation and Modelling of Earthquakes, Volcanoes, and Tectonics (COMET). Envisat data were provided by ESA. ALOS data were provided through ESA third party mission. W.H. funded by NERC studentship, NE/J5000045/1. Additional funding for fieldwork was provided by University College (University of Oxford), the Geological Remote Sensing Group, the Edinburgh Geological Society, and the Leverhulme Trust. Analytical work at the University of New Mexico was supported by the Volcanic and Geothermal Volatiles Lab at the Center for Stable Isotopes and an NSF grant EAR-1113066 to T.P.F.Restless silicic calderas present major geological hazards, and yet many also host significant untapped geothermal resources. In East Africa this poses a major challenge, although the calderas are largely unmonitored their geothermal resources could provide substantial economic benefits to the region. Understanding what causes unrest at these volcanoes is vital for weighing up the opportunities against the potential risks. Here we bring together new field and remote sensing observations to evaluate causes of ground deformation at Aluto, a restless silicic volcano located in the Main Ethiopian Rift (MER). Interferometric Synthetic Aperture Radar (InSAR) data reveal the temporal and spatial characteristics of a ground deformation episode that took place between 2008 and 2010. Deformation time-series reveal pulses of accelerating uplift that transition to gradual long-term subsidence, and analytical models support inflation source depths of ∼5 km. Gases escaping along the major fault zone of Aluto show high CO2 flux, and a clear magmatic carbon signature (CO2–δ13C of −4.2 to −4.5 ‰). This provides compelling evidence that the magmatic and hydrothermal reservoirs of the complex are physically connected. We suggest that a coupled magmatic-hydrothermal system can explain the uplift-subsidence signals. We hypothesize that magmatic fluid injection and/or intrusion in the cap of the magmatic reservoir drives edifice wide inflation while subsequent deflation is related to magmatic degassing and depressurization of the hydrothermal system. These new constraints on the plumbing of Aluto yield important insights into the behaviour of rift volcanic systems and will be crucial for interpreting future patterns of unrest.Publisher PDFPeer reviewe