Search Results (8)

The anatomical arrangement of the atrioventricular node has been likened to a riddle wrapped up in an enigma. There are several reasons for this alleged mystery, not least the marked variability in structure between different species. Lack of detailed knowledge of the location of the node relative to the atrial and ventricular septal structures has also contributed to previous misunderstandings. Recent studies comparing the findings of gross dissection with virtual dissection of living datasets, combined with access to a large number of serially sectioned human and animal hearts, have served to provide the evidence to solve the riddle. We summarise these findings in this review. We explain how the node is located within the atrial walls of the inferior pyramidal space. It becomes the non-branching component of the atrioventricular conduction axis as the axis extends through the plane of atrioventricular insulation to enter the infero-septal recess of the left ventricular outflow tract. The node itself is formed by contributions from the tricuspid and mitral vestibules, with extensive additional inputs from the base of the atrial septum. We show how knowledge of development enhances the appreciation of the arrangements and offers an explanation as to why, on occasion, there can be persisting nodoventricular connections. We discuss the findings relative to the circuits producing atrioventricular re-entry tachycardia. We conclude by emphasising the significance of the variation of the anatomical arrangements within different mammalian species. Full article

The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations. Full article

Seizures are common in preterm newborns and are associated with poor neurodevelopmental outcomes. Current anticonvulsants have poor efficacy, and many have been associated with upregulation of apoptosis in the developing brain. Apigenin, a natural bioactive flavonoid, is a potent inhibitor of hyaluronidase and reduces seizures in adult animal models. However, its impact on perinatal seizures is unclear. In the present study, we examined the effect of apigenin and S3, a synthetic, selective hyaluronidase inhibitor, on seizures after cerebral ischemia in preterm fetal sheep at 0.7 gestation (98–99 days, term ~147 days). Fetuses received sham ischemia (n = 9) or ischemia induced by bilateral carotid occlusion for 25 min. Immediately after ischemia, fetuses received either a continuous infusion of vehicle (0.036% dimethyl sulfoxide, n = 8) or apigenin (50 µM, n = 6). In a pilot study, we also tested infusion of S3 (2 µM, n = 3). Fetuses were monitored continuously for 72 h after ischemia. Infusion of apigenin or S3 were both associated with reduced numbers of animals with seizures, total seizure time, and mean seizure burden. S3 was also associated with a reduction in the total number of seizures over the 72 h recovery period. In animals that developed seizures, apigenin was associated with earlier cessation of seizures. However, apigenin or S3 treatment did not alter recovery of electroencephalographic power or spectral edge frequency. These data support that targeting brain hyaluronidase activity with apigenin or S3 may be an effective strategy to reduce perinatal seizures following ischemia. Further studies are required to determine their effects on neurohistological outcomes. Full article

The objective of this study was to examine if diets differing in crude protein (CP) to metabolizable energy (ME) ratio (CP:ME) pre-weaning altered peripheral quantitative computed tomography (pQCT) measures of bone mass and strength in lambs. The left hind leg of lambs were available at the completion of a trial designed to examine the effect that altering the CP:ME ratio in milk replacer had on growth and body composition of pre-weaned lambs reared artificially. Treatments consisted of either normal commercial milk replacer (CMR, n = 10) containing 240 g/kg CP and 21.89 MJ/kg ME, high protein milk replacer (HPM, n = 9) containing CMR with additional milk protein concentrate to reach 478.7 g/kg CP and 19.15 MJ/kg ME or a mix of normal milk replacer and milk protein concentrate adjusted twice-weekly to match optimal CP:ME requirements (MB, n = 8) based on maintenance plus 300 g/d liveweight gain. At 22 kg live weight, lambs were euthanized and the tibia including the surrounding muscle was collected and scanned using pQCT at the mid-diaphysis. Lambs on the HPM and MB diets had a greater average daily gain (p < 0.01). There were limited differences in bone morphology and muscle mass, though notably the higher protein diets (MB and HPM) were associated with greater cortical thickness (p < 0.05) and, therefore, potentially greater peak bone mass at maturity This finding demonstrates that pre-weaning diets, and the protein content in particular, may influence the developmental potential of long bones and attainment of peak bone mass at maturity. Full article

We show that magnetic skyrmions can be stabilised at room temperature in continuous [Ir/Co/Pt]₅ multilayers on SiO₂/Si substrates without the prior application of electric current or magnetic field. While decreasing the Co thickness, a transition of the magnetic domain patterns from worm-like state to separated stripes is observed. The skyrmions are clearly imaged in both states using magnetic force microscopy. The density of skyrmions can be significantly enhanced after applying the “in-plane field procedure”. Our results provide means to manipulate magnetic skyrmion density, further allowing for the optimised engineering of skyrmion-based devices. Full article

Feature engineering is an essential step in the pipelines used for many machine learning tasks, including time-series forecasting. Although existing AutoML approaches partly automate feature engineering, they do not support specialised approaches for applications on time-series data such as multi-step forecasting. Multi-step forecasting is the task of predicting a sequence of values in a time-series. Two kinds of approaches are commonly used for multi-step forecasting. A typical approach is to apply one model to predict the value for the next time step. Then the model uses this predicted value as an input to forecast the value for the next time step. Another approach is to use multi-output models to make the predictions for multiple time steps of each time-series directly. In this work, we demonstrate how automated machine learning can be enhanced with feature engineering techniques for multi-step time-series forecasting. Specifically, we combine a state-of-the-art automated machine learning system, auto-sklearn, with tsfresh, a library for feature extraction from time-series. In addition to optimising machine learning pipelines, we propose to optimise the size of the window over which time-series data are used for predicting future time-steps. This is an essential hyperparameter in time-series forecasting. We propose and compare (i) auto-sklearn with automated window size selection, (ii) auto-sklearn with tsfresh features, and (iii) auto-sklearn with automated window size selection and tsfresh features. We evaluate these approaches with statistical techniques, machine learning techniques and state-of-the-art automated machine learning techniques, on a diverse set of benchmarks for multi-step time-series forecasting, covering 20 synthetic and real-world problems. Our empirical results indicate a significant potential for improving the accuracy of multi-step time-series forecasting by using automated machine learning in combination with automatically optimised feature extraction techniques. Full article

(1) Background: Some COVID-19 vaccine recipients show breakthrough infection. It remains unknown, which factors contribute to risks and severe outcomes. Our aim was to identify risk factors for SCoV2 breakthrough infections in fully vaccinated individuals. (2) Methods: We conducted a retrospective case-control study from 28 December 2020 to 25 October 2021. Data of all patients with breakthrough infection was compared to data of all vaccine recipients in the Canton of Basel-City, Switzerland. Further, breakthrough infections by Alpha- and Delta-variants were compared. (3) Results: Only 0.39% (488/126,586) of all vaccine recipients suffered from a breakthrough infection during the observational period, whereof most cases were asymptomatic or mild (97.2%). Breakthrough infections after full vaccination occurred in the median after 78 days (IQR 47-123.5). Factors with lower odds for breakthrough infection were age (OR 0.987) and previous COVID-19 infection prior to vaccination (OR 0.296). Factors with higher odds for breakthrough infection included vaccination with Pfizer/BioNTech instead of Moderna (OR 1.459), chronic disease (OR 2.109), and healthcare workers (OR 1.404). (4) Conclusions: Breakthrough infections are rare and mild but can occur early after vaccination. This implies that booster vaccination might be initiated earlier, especially for risk groups. Due to new variants emerging repeatedly, continuous monitoring of breakthrough infections is crucial. Full article

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents. Full article