Distinguishing Healthy Ageing from Dementia: A Biomechanical Simulation of Brain Atrophy Using Deep Networks

Biomechanical modeling of tissue deformation can be used to simulate different scenarios of longitudinal brain evolution. In this work, we present a deep learning framework for hyper-elastic strain modelling of brain atrophy, during healthy ageing and in Alzheimer’s Disease. The framework directly models the effects of age, disease status, and scan interval to regress regional patterns of atrophy, from which a strain-based model estimates deformations. This model is trained and validated using 3D structural magnetic resonance imaging data from the ADNI cohort. Results show that the framework can estimate realistic deformations, following the known course of Alzheimer’s disease, that clearly differentiate between healthy and demented patterns of ageing. This suggests the framework has potential to be incorporated into explainable models of disease, for the exploration of interventions and counterfactual examples

Seropositivity for Coxiella burnetii in Wild Boar (Sus scrofa) and Red Deer (Cervus elaphus) in Portugal

Q fever is caused by the pathogen Coxiella burnetii and is a zoonosis that naturally infects goats, sheep, and cats, but can also infect humans, birds, reptiles, or arthropods. A survey was conducted for the detection of antibodies against C. burnetii in a sample of 617 free-ranging wild ruminants, 358 wild boar (Sus scrofa) and 259 red deer (Cervus elaphus), in east-central Portugal during the 2016-2022 hunting seasons. Only adult animals were sampled in this study. Antibodies specific to C. burnetii were detected using a commercial enzyme-linked immunosorbent assay (ELISA; IDVet(R), Montpellier, France) according to the manufacturer's instructions. The seroprevalence of C. burnetii infection was 1.5% (n = 9; 95% confidence interval [CI]: 0.7-2.8%). Antibodies against C. burnetii were detected in 4/358 wild boar (1.1%; 95% CI: CI: 0.3-2.8%) and 5/259 red deer (1.9%; 0.6-4.5%). Results of the present study indicate that antibodies against C. burnetii were present in wild boar and red deer in Portugal. These findings can help local health authorities to focus on the problem of C. burnetii in wildlife and facilitate the application of a One Health approach to its prevention and control

An isoform of Dicer protects mammalian stem cells against multiple RNA viruses

In mammals, early resistance to viruses relies on interferons, which protect differentiated cells but not stem cells from viral replication. Many other organisms rely instead on RNA interference (RNAi) mediated by a specialized Dicer protein that cleaves viral double-stranded RNA. Whether RNAi also contributes to mammalian antiviral immunity remains controversial. We identified an isoform of Dicer, named antiviral Dicer (aviD), that protects tissue stem cells from RNA viruses—including Zika virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—by dicing viral double-stranded RNA to orchestrate antiviral RNAi. Our work sheds light on the molecular regulation of antiviral RNAi in mammalian innate immunity, in which different cell-intrinsic antiviral pathways can be tailored to the differentiation status of cells

Fully automated grey and white matter segmentation of the cervical cord in vivo

We propose and validate a new fully automated spinal cord (SC) segmentation technique that incorporates two different multi-atlas segmentation propagation and fusion techniques: Optimized PatchMatch Label fusion (OPAL) and Similarity and Truth Estimation for Propagated Segmentations (STEPS). We collaboratively join the advantages of each method to obtain the most accurate SC segmentation. The new method reaches the inter-rater variability, providing automatic segmentations equivalents to inter-rater segmentations in terms of DSC 0.97 for whole cord for any subject

Fully automated grey and white matter spinal cord segmentation

Axonal loss in the spinal cord is one of the main contributing factors to irreversible clinical disability in multiple sclerosis (MS). In vivo axonal loss can be assessed indirectly by estimating a reduction in the cervical cross-sectional area (CSA) of the spinal cord over time, which is indicative of spinal cord atrophy, and such a measure may be obtained by means of image segmentation using magnetic resonance imaging (MRI). In this work, we propose a new fully automated spinal cord segmentation technique that incorporates two different multi-atlas segmentation propagation and fusion techniques: The Optimized PatchMatch Label fusion (OPAL) algorithm for localising and approximately segmenting the spinal cord, and the Similarity and Truth Estimation for Propagated Segmentations (STEPS) algorithm for segmenting white and grey matter simultaneously. In a retrospective analysis of MRI data, the proposed method facilitated CSA measurements with accuracy equivalent to the inter-rater variability, with a Dice score (DSC) of 0.967 at C2/C3 level. The segmentation performance for grey matter at C2/C3 level was close to inter-rater variability, reaching an accuracy (DSC) of 0.826 for healthy subjects and 0.835 people with clinically isolated syndrome MS

Small Hairy Black Holes in Global AdS Spacetime

We study small charged black holes in global AdS spacetime in the presence of a charged massless minimally coupled scalar field. In a certain parameter range these black holes suffer from well known superradiant instabilities. We demonstrate that the end point of the resultant tachyon condensation process is a hairy black hole which we construct analytically in a perturbative expansion in the black hole radius. At leading order our solution is a small undeformed RNAdS black hole immersed into a charged scalar condensate that fills the AdS `box'. These hairy black hole solutions appear in a two parameter family labelled by their mass and charge. Their mass is bounded from below by a function of their charge; at the lower bound a hairy black hole reduces to a regular horizon free soliton which can also be thought of as a nonlinear Bose condensate. We compute the microcanonical phase diagram of our system at small mass, and demonstrate that it exhibits a second order `phase transition' between the RNAdS black hole and the hairy black hole phases.Comment: 68+1 pages, 18 figures, JHEP format. v2 : small typos corrected and a reference adde

Coarse-grained reconfigurable array architectures

Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. By executing non-loop code on other cores, however, CGRAs can focus on such loops to execute them more efficiently. This chapter discusses the basic principles of CGRAs, and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code

A generative-oriented model-driven design environment for customizable video surveillance systems

To tackle the growing complexity and huge demand for tailored domestic video surveillance systems along with a high demanding time-to-market expectation, engineers at IVV Automação, LDAa are exploiting video surveillance domain as families of systems that can be developed following a pay-as-you-go fashion rather than developing an ex-nihilo new product. Several and different new functionalities are required for each new product’s hardware platforms (e.g., ranging from mobile phone, PDA to desktop PC) and operating systems (e.g., flavors of Linux, Windows and MAC OS X). Some of these functionalities have special economical constraints of development time and memory footprint. To better accommodate all the above listing requirements, a model-driven generative software development paradigm supported by mainstream tools is proposed to offer a significant leverage in hiding commonalities and configuring variabilities across families of video surveillance products while maintaining the new product quality.This work was funded through the Competitive Factors Operational Program COMPETE and through national funds though the Science and Technology Foundation - FCT, within the project: FCOMP-01-0124-FEDER-022674. This work was developed in cooperation with IVV Automation; all support and means provided by the company is acknowledged