Efficient design of piezoresistive sensors based on carbon black conductive composites

Flexible and stretchable sensors are widely investigated taking into account their potential for wearable electronics, such as electronic skin, healthcare monitoring, human-machine interfaces, and soft robotics. In this contribution, highly sensitive conductive polymer composites (CPCs) for piezoresistive sensing are summarized, considering a straightforward manufacturing process based on extrusion of thermoplastic polyurethane (TPU) and/or olefin block copolymer (OBC), carbon black (CB), and additionally polyethylene-octene elastomer (POE) grafted with maleic anhydride (POE-g-MA). The design of the formulation variables is successfully performed to enable both low and high strain sensing, as highlighted by both static and dynamic testing

Segmentation d'images échocardiographiques par contours actifs implicites : exploitation de descripteurs statistiques de régions

Le problème traité concerne la segmentation d'images échocardiographiques par contour actifs implicites utilisant des descripteurs statistiques de région basés sur les K-distributions. La quasi totalité des auteurs traitant ce sujet exploite la statistique de Rayleigh, qui est un modèle limité pour la caractérisation de certain milieux tissulaires, tel que le myocarde. Ainsi, l'originalité de la méthode proposée réside en l'exploitation du formalisme récemment développé par Jehan-Besson et al. afin d'utiliser un paramètre statistique issu du modèle des K-distributions qui reflète plus fidèlement les propriétés des images ultrasonores du myocarde

Automatic characterization of neointimal tissue by intravascular optical coherence tomography

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Automatic Extraction of Hiatal Dimensions in 3-D Transperineal Pelvic Ultrasound Recordings

The aims of this work were to create a robust automatic software tool for measurement of the levator hiatal area on transperineal ultrasound (TPUS) volumes and to measure the potential reduction in variability and time taken for analysis in a clinical setting. The proposed tool automatically detects the C-plane (i.e., the plane of minimal hiatal dimensions) from a 3-D TPUS volume and subsequently uses the extracted plane to automatically segment the levator hiatus, using a convolutional neural network. The automatic pipeline was tested using 73 representative TPUS volumes. Reference hiatal outlines were obtained manually by two experts and compared with the pipeline's automated outlines. The Hausdorff distance, area, a clinical quality score, C-plane angle and C-plane Euclidean distance were used to evaluate C-plane detection and quantify levator hiatus segmentation accuracy. A visual Turing test was created to compare the performance of the software with that of the expert, based on the visual assessment of C-plane and hiatal segmentation quality. The overall time taken to extract the hiatal area with both measurement methods (i.e., manual and automatic) was measured. Each metric was calculated both for computer–observer differences and for inter-and intra-observer differences. The automatic method gave results similar to those of the expert when determining the hiatal outline from a TPUS volume. Indeed, the hiatal area measured by the algorithm and by an expert were within the intra-observer variability. Similarly, the method identified the C-plane with an accuracy of 5.76 ± 5.06° and 6.46 ± 5.18 mm in comparison to the inter-observer variability of 9.39 ± 6.21° and 8.48 ± 6.62 mm. The visual Turing test suggested that the automatic method identified the C-plane position within the TPUS volume visually as well as the expert. The average time taken to identify the C-plane and segment the hiatal area manually was 2 min and 35 ± 17 s, compared with 35 ± 4 s for the automatic result. This study presents a method for automatically measuring the levator hiatal area using artificial intelligence-based methodologies whereby the C-plane within a TPUS volume is detected and subsequently traced for the levator hiatal outline. The proposed solution was determined to be accurate, relatively quick, robust and reliable and, importantly, to reduce time and expertise required for pelvic floor disorder assessment

Long-term miR-669a therapy alleviates chronic dilated cardiomyopathy in dystrophic mice.

BACKGROUND: Dilated cardiomyopathy (DCM) is a leading cause of chronic morbidity and mortality in muscular dystrophy (MD) patients. Current pharmacological treatments are not yet able to counteract chronic myocardial wastage, thus novel therapies are being intensely explored. MicroRNAs have been implicated as fine regulators of cardiomyopathic progression. Previously, miR-669a downregulation has been linked to the severe DCM progression displayed by Sgcb-null dystrophic mice. However, the impact of long-term overexpression of miR-669a on muscle structure and functionality of the dystrophic heart is yet unknown. METHODS AND RESULTS: Here, we demonstrate that intraventricular delivery of adeno-associated viral (AAV) vectors induces long-term (18 months) miR-669a overexpression and improves survival of Sgcb-null mice. Treated hearts display significant decrease in hypertrophic remodeling, fibrosis, and cardiomyocyte apoptosis. Moreover, miR-669a treatment increases sarcomere organization, reduces ventricular atrial natriuretic peptide (ANP) levels, and ameliorates gene/miRNA profile of DCM markers. Furthermore, long-term miR-669a overexpression significantly reduces adverse remodeling and enhances systolic fractional shortening of the left ventricle in treated dystrophic mice, without significant detrimental consequences on skeletal muscle wastage. CONCLUSIONS: Our findings provide the first evidence of long-term beneficial impact of AAV-mediated miRNA therapy in a transgenic model of severe, chronic MD-associated DCM

Technical note: automatic segmentation method of pelvic floor levator hiatus in ultrasound using a self-normalising neural network

Segmentation of the levator hiatus in ultrasound allows to extract biometrics which are of importance for pelvic floor disorder assessment. In this work, we present a fully automatic method using a convolutional neural network (CNN) to outline the levator hiatus in a 2D image extracted from a 3D ultrasound volume. In particular, our method uses a recently developed scaled exponential linear unit (SELU) as a nonlinear self-normalising activation function. SELU has important advantages such as being parameter-free and mini-batch independent. A dataset with 91 images from 35 patients all labelled by three operators, is used for training and evaluation in a leave-one-patient-out cross-validation. Results show a median Dice similarity coefficient of 0.90 with an interquartile range of 0.08, with equivalent performance to the three operators (with a Williams’ index of 1.03), and outperforming a U-Net architecture without the need for batch normalisation. We conclude that the proposed fully automatic method achieved equivalent accuracy in segmenting the pelvic floor levator hiatus compared to a previous semi-automatic approach

Absence of thrombospondin-2 causes age-related dilated cardiomyopathy

BACKGROUND: The progressive shift from a young to an aged heart is characterized by alterations in the cardiac matrix. The present study investigated whether the matricellular protein thrombospondin-2 (TSP-2) may affect cardiac dimensions and function with physiological aging of the heart. METHODS AND RESULTS: TSP-2 knockout (KO) and wild-type mice were followed up to an age of 60 weeks. Survival rate, cardiac function, and morphology did not differ at a young age in TSP-2 KO compared with wild-type mice. However, >55% of the TSP-2 KO mice died between 24 and 60 weeks of age, whereas <10% of the wild-type mice died. In the absence of TSP-2, older mice displayed a severe dilated cardiomyopathy with impaired systolic function, increased cardiac dilatation, and fibrosis. Ultrastructural analysis revealed progressive myocyte stress and death, accompanied by an inflammatory response and replacement fibrosis, in aging TSP-2 KO animals, whereas capillary or coronary morphology or density was not affected. Importantly, adeno-associated virus-9 gene-mediated transfer of TSP-2 in 7-week-old TSP-2 KO mice normalized their survival and prevented dilated cardiomyopathy. In TSP-2 KO animals, age-related cardiomyopathy was accompanied by increased matrix metalloproteinase-2 and decreased tissue transglutaminase-2 activity, together with impaired collagen cross-linking. At the cardiomyocyte level, TSP-2 deficiency in vivo and its knockdown in vitro decreased the activation of the Akt survival pathway in cardiomyocytes. CONCLUSIONS: TSP-2 expression in the heart protects against age-dependent dilated cardiomyopath

DMRN+18: Digital Music Research Network One-day Workshop 2023

DMRN+18: Digital Music Research Network One-day Workshop 2023 Queen Mary University of London Tuesday 19th December 2023 • Keynote speaker: Stefan Bilbao The Digital Music Research Network (DMRN) aims to promote research in the area of digital music, by bringing together researchers from UK and overseas universities, as well as industry, for its annual workshop. The workshop will include invited and contributed talks and posters. The workshop will be an ideal opportunity for networking with other people working in the area. Keynote speakers: Stefan Bilbao Tittle: Physics-based Audio: Sound Synthesis and Virtual Acoustics. Abstract: Any acoustically-produced sound produced must be the result of physical laws that describe the dynamics of a given system---always at least partly mechanical, and sometimes with an electronic element as well. One approach to the synthesis of natural acoustic timbres, thus, is through simulation, often referred to in this context as physical modelling, or physics-based audio. In this talk, the principles of physics-based audio, and the various different approaches to simulation are described, followed by a set of examples covering: various musical instrument types; the important related problem of the emulation of room acoustics or “virtual acoustics”; the embedding of instruments in a 3D virtual space; electromechanical effects; and also new modular instrument designs based on physical laws, but without a counterpart in the real world. Some more technical details follow, including the strengths, weaknesses and limitations of such methods, and pointers to some links to data-centred black-box approaches to sound generation and effects processing. The talk concludes with some musical examples and recent work on moving such algorithms to a real-time setting.. Bio: Stefan is a Professor (full) at Reid School of Music, University of Edinburgh, he is the Personal Chair of Acoustics and Audio Signal Processing, Music. He currently works on computational acoustics, for applications in sound synthesis and virtual acoustics. Special topics of interest include: Finite difference time domain methods, distributed nonlinear systems such as strings and plates, architectural acoustics, spatial audio in simulation, multichannel sound synthesis, and hardware and software realizations. More information on: https://www.acoustics.ed.ac.uk/group-members/dr-stefan-bilbao/ DMRN+18 is sponsored by The UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM); a leading PhD research programme aimed at the Music/Audio Technology and Creative Industries, based at Queen Mary University of London

Reducing the number of accepted species in Aspergillus series Nigri

The Aspergillus series Nigri contains biotechnologically and medically important species. They can produce hazardous mycotoxins, which is relevant due to the frequent occurrence of these species on foodstuffs and in the indoor environment. The taxonomy of the series has undergone numerous rearrangements, and currently, there are 14 species accepted in the series, most of which are considered cryptic. Species-level identifications are, however, problematic or impossible for many isolates even when using DNA sequencing or MALDI-TOF mass spectrometry, indicating a possible problem in the definition of species limits or the presence of undescribed species diversity. To re-examine the species boundaries, we collected DNA sequences from three phylogenetic markers (benA, CaM and RPB2) for 276 strains from series Nigri and generated 18 new whole-genome sequences. With the three-gene dataset, we employed phylogenetic methods based on the multispecies coalescence model, including four single-locus methods (GMYC, bGMYC, PTP and bPTP) and one multilocus method (STACEY). From a total of 15 methods and their various settings, 11 supported the recognition of only three species corresponding to the three main phylogenetic lineages: A. niger, A. tubingensis and A. brasiliensis. Similarly, recognition of these three species was supported by the GCPSR approach (Genealogical Concordance Phylogenetic Species Recognition) and analysis in DELINEATE software. We also showed that the phylogeny based on benA, CaM and RPB2 is suboptimal and displays significant differences from a phylogeny constructed using 5 752 single-copy orthologous proteins; therefore, the results of the delimitation methods may be subject to a higher than usual level of uncertainty. To overcome this, we randomly selected 200 genes from these genomes and performed ten independent STACEY analyses, each with 20 genes. All analyses supported the recognition of only one species in the A. niger and A. brasiliensis lineages, while one to four species were inconsistently delimited in the A. tubingensis lineage. After considering all of these results and their practical implications, we propose that the revised series Nigri includes six species: A. brasiliensis, A. eucalypticola, A. luchuensis (syn. A. piperis), A. niger (syn. A. vinaceus and A. welwitschiae), A. tubingensis (syn. A. chiangmaiensis, A. costaricensis, A. neoniger and A. pseudopiperis) and A. vadensis. We also showed that the intraspecific genetic variability in the redefined A. niger and A. tubingensis does not deviate from that commonly found in other aspergilli. We supplemented the study with a list of accepted species, synonyms and unresolved names, some of which may threaten the stability of the current taxonomy.The Czech Ministry of Health, the Charles University Research Centre program, the Czech Academy of Sciences Long-term Research Development Project, the project of Charles University Grant Agency, JST SPRING, the Foundational Biodiversity Information Programme (FBIP) of the National Research Foundation of South Africa, the Japan Society for the Promotion of Science - Postdoctoral Fellowships for Research in Japan and Grant-in-aid for a JSPS research fellow.https://www.journals.elsevier.com/studies-in-mycologyam2023BiochemistryGeneticsMicrobiology and Plant Patholog