bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of coronary artery calcium scoring from surface electrocardiogram in atherosclerotic cardiovascular disease: a pilot study
Authors: Farjo Peter D , Yanamala Naveena , Kagiyama Nobuyuki , Patel Heenaben B , Casaclang-Verzosa Grace , Nezarat Negin , Budoff Matthew J , Sengupta Partho P 
Published: November 2020

Abstract

Aims
Coronary artery calcium (CAC) scoring is an established tool for cardiovascular risk stratification. However, the lack of widespread availability and concerns about radiation exposure have limited the universal clinical utilization of CAC. In this study, we sought to explore whether machine learning (ML) approaches can aid cardiovascular risk stratification by predicting guideline recommended CAC score categories from clinical features and surface electrocardiograms.

Methods and results
In this substudy of a prospective, multicentre trial, a total of 534 subjects referred for CAC scores and electrocardiographic data were split into 80% training and 20% testing sets. Two binary outcome ML logistic regression models were developed for prediction of CAC scores equal to 0 and ≥400. Both CAC = 0 and CAC ≥400 models yielded values for the area under the curve, sensitivity, specificity, and accuracy of 84%, 92%, 70%, and 75%, and 87%, 91%, 75%, and 81%, respectively. We further tested the CAC ≥400 model to risk stratify a cohort of 87 subjects referred for invasive coronary angiography. Using an intermediate or higher pretest probability (≥15%) to predict CAC ≥400, the model predicted the presence of significant coronary artery stenosis (P = 0.025), the need for revascularization (P &lt; 0.001), notably bypass surgery (P = 0.021), and major adverse cardiovascular events (P = 0.023) during a median follow-up period of 2 years.

Conclusion
ML techniques can extract information from electrocardiographic data and clinical variables to predict CAC score categories and similarly risk-stratify patients with suspected coronary artery disease.
Increased myocardial stiffness more than impaired relaxation function limits cardiac performance during exercise in heart failure with preserved ejection fraction: a virtual patient study
Authors: van Loon Tim , Knackstedt Christian , Cornelussen Richard , Reesink Koen D , Brunner La Rocca Hans-Peter , Delhaas Tammo , van Empel Vanessa , Lumens Joost 
Published: November 2020

Abstract

Aims
The relative impact of left ventricular (LV) diastolic dysfunction (LVDD) and impaired left atrial (LA) function on cardiovascular haemodynamics in heart failure with preserved ejection fraction (HFpEF) is largely unknown. We performed virtual patient simulations to elucidate the relative effects of these factors on haemodynamics at rest and during exercise.

Methods and results
The CircAdapt cardiovascular system model was used to simulate cardiac haemodynamics in wide ranges of impaired LV relaxation function, increased LV passive stiffness, and impaired LA function. Simulations showed that LV ejection fraction (LVEF) was preserved (&gt;50%), despite these changes in LV and LA function. Impairment of LV relaxation function decreased E/A ratio and mildly increased LV filling pressure at rest. Increased LV passive stiffness resulted in increased E/A ratio, LA dilation and markedly elevated LV filling pressure. Impairment of LA function increased E/A ratio and LV filling pressure, explaining inconsistent grading of LVDD using echocardiographic indices. Exercise simulations showed that increased LV passive stiffness exerts a stronger exercise-limiting effect than impaired LV relaxation function does, especially with impaired LA function.

Conclusion
The CircAdapt model enabled realistic simulation of virtual HFpEF patients, covering a wide spectrum of LVDD and related limitations of cardiac exercise performance, all with preserved resting LVEF. Simulations suggest that increased LV passive stiffness, more than impaired relaxation function, reduces exercise tolerance, especially when LA function is impaired. In future studies, the CircAdapt model can serve as a valuable platform for patient-specific simulations to identify the disease substrate(s) underlying the individual HFpEF patient’s cardiovascular phenotype.
Immersive 3D virtual reality imaging in planning minimally invasive and complex adult cardiac surgery
Authors: Sadeghi Amir H , Bakhuis Wouter , Van Schaagen Frank , Oei Frans B S , Bekkers Jos A , Maat Alexander P W M , Mahtab Edris A F , Bogers Ad J J C , Taverne Yannick J H J 
Published: November 2020

Abstract

Aims
Increased complexity in cardiac surgery over the last decades necessitates more precise preoperative planning to minimize operating time, to limit the risk of complications during surgery and to aim for the best possible patient outcome. Novel, more realistic, and more immersive techniques, such as three-dimensional (3D) virtual reality (VR) could potentially contribute to the preoperative planning phase. This study shows our initial experience on the implementation of immersive VR technology as a complementary research-based imaging tool for preoperative planning in cardiothoracic surgery. In addition, essentials to set up and implement a VR platform are described.

Methods
Six patients who underwent cardiac surgery at the Erasmus Medical Center, Rotterdam, The Netherlands, between March 2020 and August 2020, were included, based on request by the surgeon and availability of computed tomography images. After 3D VR rendering and 3D segmentation of specific structures, the reconstruction was analysed via a head mount display. All participating surgeons (n = 5) filled out a questionnaire to evaluate the use of VR as preoperative planning tool for surgery.

Conclusion
Our study demonstrates that immersive 3D VR visualization of anatomy might be beneficial as a supplementary preoperative planning tool for cardiothoracic surgery, and further research on this topic may be considered to implement this innovative tool in daily clinical practice.

Lay summary
Over the past decades, surgery on the heart and vessels is becoming more and more complex, necessitating more precise and accurate preoperative planning. Nowadays, operative planning is feasible on flat, two-dimensional computer screens, however, requiring a lot of spatial and three-dimensional (3D) thinking of the surgeon. Since immersive 3D virtual reality (VR) is an upcoming imaging technique with promising results in other fields of surgery, we aimed in this study to explore the additional value of this technique in heart surgery. Our surgeons planned six different heart operations by visualizing computed tomography scans with a dedicated VR headset, enabling them to visualize the patient’s anatomy in an immersive and 3D environment. The outcomes of this preliminary study are positive, with a much more reality-like simulation for the surgeon. In such, VR could potentially be beneficial as a preoperative planning tool for complex heart surgery.
Automated lumen segmentation using multi-frame convolutional neural networks in intravascular ultrasound datasets
Authors: Ziemer Paulo G P , Bulant Carlos A , Orlando José I , Maso Talou Gonzalo D , Álvarez Luis A Mansilla , Guedes Bezerra Cristiano , Lemos Pedro A , García-García Héctor M , Blanco Pablo J 
Published: November 2020

Abstract

Aims
Assessment of minimum lumen areas in intravascular ultrasound (IVUS) pullbacks is time-consuming and demands adequately trained personnel. In this work, we introduce a novel and fully automated pipeline to segment the lumen boundary in IVUS datasets.

Methods and results
First, an automated gating is applied to select end-diastolic frames and bypass saw-tooth artefacts. Second, within a machine learning (ML) environment, we automatically segment the lumen boundary using a multi-frame (MF) convolutional neural network (MFCNN). Finally, we use the theory of Gaussian processes (GPs) to regress the final lumen boundary. The dataset consisted of 85 IVUS pullbacks (52 patients). The dataset was partitioned at the pullback-level using 73 pullbacks for training (20 586 frames), 6 pullbacks for validation (1692 frames), and 6 for testing (1692 frames). The degree of overlapping, between the ground truth and ML contours, median (interquartile range, IQR) systematically increased from 0.896 (0.874–0.933) for MF1 to 0.925 (0.911–0.948) for MF11. The median (IQR) of the distance error was also reduced from 3.83 (2.94–4.98)% for MF1 to 3.02 (2.25–3.95)% for MF11-GP. The corresponding median (IQR) in the lumen area error remained between 5.49 (2.50–10.50)% for MF1 and 5.12 (2.15–9.00)% for MF11-GP. The dispersion in the relative distance and area errors consistently decreased as we increased the number of frames, and also when the GP regressor was coupled to the MFCNN output.

Conclusion
These results demonstrate that the proposed ML approach is suitable to effectively segment the lumen boundary in IVUS scans, reducing the burden of costly and time-consuming manual delineation.
Many roads to bacterial generalism
Authors: Bell Terrence H , Bell Thomas 
Published: November 2020

ABSTRACTThe fundamental niches of bacteria can be defined along many environmental axes, including temperature tolerance and resources consumed, while interactions with other organisms can constrain (e.g. competition) or enlarge (e.g. cross-feeding) realized niches. Organisms are often categorized as generalists or specialists, corresponding to broad or narrow niche requirements, which can then be linked to their functional role in an ecosystem. We show how these terms are applied to bacteria, make predictions about how the type and extent of generalism displayed by an organism relates to its functional potential and discuss the value of collecting different types of generalist bacteria. We believe that new approaches that take advantage of both high-throughput sequencing and environmental manipulation can allow us to understand the many types of generalism found within both cultivated and yet-to-be-cultivated bacteria.
Residential cluster design and potential improvement for maximum energy performance and outdoor thermal comfort on a hot summer in Thailand
Authors: Jareemit Daranee , Canyookt Parintorn 
Published: November 2020

Abstract
Thailand committed to achieving the Sustainable Development Goals to increase urban livability and reduce energy use in the building sector. However, the design information to achieve those challenge goals has been undefined. This study aimed to investigate and examine potential improvements for outdoor thermal comfort and energy efficiency in 136 designs of the two-type residential cluster in Pathum Thani, Thailand, via designs of building orientation, geometry and window-to-wall ratio (WWR). The daily cooling energy consumption in residential clusters was performed using eQuest under the modified weather data from the prior microclimate analysis. The energy-saving scenarios were calculated and compared to the acceptable outdoor thermal comfort hours. It is found that the row house cluster had the potential to be more sustainable than a single house. The row house clusters on orthogonal street orientation offered the highest percentage of hours in outdoor thermal comfort of 46% and energy efficiency below the new standard of Thailand. The cooling energy savings through increasing H/W with lowering WWR was up to 32%. This study’s results could provide urban planners and architects with the new design guidelines and improvement potentials to make cities more energy efficient and environmentally friendly for outdoor living in Thailand.
COVID-19: leadership on the frontline is what matters when we support healthcare workers
Authors: Obrien Niki , Flott Kelsey , Durkin Mike 
Published: November 2020

Abstract
The implications of severe acute respiratory syndrome coronavirus (SARS-CoV-2, henceforth described as COVID-19) on healthcare systems globally are proving to be immense, with unforeseen impacts that are still to fully emerge. Local and national healthcare systems, hospitals and healthcare workers have been overwhelmed by the needs of patients and limited by weaknesses in resources, staff capacity and distribution networks. These circumstances impact the ergonomic conditions within which healthcare staff work and subsequently their behavioural responses.In this commentary, we argue that urgent research is needed globally to bridge the evidence gap that exists on how best to support healthcare workers with the repercussions of working on the frontline of a pandemic. Leadership on the frontline is what matters. It is not only what policies, guidelines and checklists are in place to support nurses, doctors and healthcare workers, it is the actions and behaviours of their frontline and local leaders in implementing initiatives that really make the difference.Recognizing that the leadership style, organizational culture and model of successful implementation are inextricable is the first step to ensure sustainable interventions to support healthcare workers’ well-being will follow.
Transcriptional integration of plant responses to iron availability
Authors: Gao Fei , Dubos Christian 
Published: November 2020

AbstractIron is one of the most important micronutrients for plant growth and development. It functions as the enzyme cofactor or component of electron transport chains in various vital metabolic processes, including photosynthesis, respiration, and amino acid biosynthesis. To maintain iron homeostasis, and therefore prevent any deficiency or excess that could be detrimental, plants have evolved complex transcriptional regulatory networks to tightly control iron uptake, translocation, assimilation, and storage. These regulatory networks are composed of various transcription factors; among them, members of the basic helix-loop-helix (bHLH) family play an essential role. Here, we first review recent advances in understanding the roles of bHLH transcription factors involved in the regulatory cascade controlling iron homeostasis in the model plant Arabidopsis, and extend this understanding to rice and other plant species. The importance of other classes of transcription factors will also be discussed. Second, we elaborate on the post-translational mechanisms involved in the regulation of these regulatory networks. Finally, we provide some perspectives on future research that should be conducted in order to precisely understand how plants control the homeostasis of this micronutrient.
Growth and structure of multiphase gas in the cloud-crushing problem with cooling
Authors: Kanjilal Vijit , Dutta Alankar , Sharma Prateek 
Published: November 2020

ABSTRACT
We revisit the problem of the growth of dense/cold gas in the cloud-crushing set-up with radiative cooling. The relative motion between the dense cloud and the diffuse medium produces a turbulent boundary layer of mixed gas with a short cooling time. This mixed gas may explain the ubiquity of the range of absorption/emission lines observed in various sources such as the circumgalactic medium and galactic/stellar/active galactic nucleus outflows. Recently, Gronke & Oh showed that the efficient radiative cooling of the mixed gas can lead to continuous growth of the dense cloud. They presented a threshold cloud size for the growth of dense gas that was contradicted by the more recent works of Li et al. & Sparre et al. These thresholds are qualitatively different as the former is based on the cooling time of the mixed gas whereas the latter is based on the cooling time of the hot gas. Our simulations agree with the threshold based on the cooling time of the mixed gas. We argue that the radiative cloud-crushing simulations should be run long enough to allow for the late-time growth of the dense gas due to cooling of the mixed gas but not so long that the background gas cools catastrophically. Moreover, the simulation domain should be large enough that the mixed gas is not lost through the boundaries. While the mixing layer is roughly isobaric, the emissivity of the gas at different temperatures is fundamentally different from an isobaric single-phase steady cooling flow.
A study of radial self-similar non-relativistic MHD outflow models: parameter space exploration and application to the water fountain W43A
Authors: Ceccobello C , Heemskerk M H M , Cavecchi Y , Vlemmings W H T , Tafoya D 
Published: November 2020

ABSTRACT
Outflows, spanning a wide range of dynamical properties and spatial extensions, have now been associated with a variety of accreting astrophysical objects, from supermassive black holes at the core of active galaxies to young stellar objects. The role of such outflows is key to the evolution of the system that generates them, for they extract a fraction of the orbiting material and angular momentum from the region close to the central object and release them in the surroundings. The details of the launching mechanism and their impact on the environment are fundamental to understand the evolution of individual sources and the similarities between different types of outflow-launching systems. We solve semi-analytically the non-relativistic, ideal, magnetohydrodynamics equations describing outflows launched from a rotating disc threaded with magnetic fields using our new numerical scheme. We present here a parameter study of a large sample of new solutions. We study the different combinations of forces that lead to a successfully launched jet and discuss their global properties. We show how these solutions can be applied to the outflow of the water fountain W43A for which we have observational constraints on magnetic field, density and velocity of the flow at the location of two symmetrical water maser emitting regions.
A quantitative in-depth analysis of the prototype sdB+BD system SDSS J08205+0008 revisited in the Gaia era
Authors: Schaffenroth V , Casewell S L , Schneider D , Kilkenny D , Geier S , Heber U , Irrgang A , Przybilla N , Marsh T R , Littlefair S P , Dhillon V S 
Published: November 2020

ABSTRACT
Subdwarf B stars are core-helium-burning stars located on the extreme horizontal branch (EHB). Extensive mass loss on the red giant branch is necessary to form them. It has been proposed that substellar companions could lead to the required mass loss when they are engulfed in the envelope of the red giant star. J08205+0008 was the first example of a hot subdwarf star with a close, substellar companion candidate to be found. Here, we perform an in-depth re-analysis of this important system with much higher quality data allowing additional analysis methods. From the higher resolution spectra obtained with ESO-VLT/XSHOOTER, we derive the chemical abundances of the hot subdwarf as well as its rotational velocity. Using the Gaia parallax and a fit to the spectral energy distribution in the secondary eclipse, tight constraints to the radius of the hot subdwarf are derived. From a long-term photometric campaign, we detected a significant period decrease of $-3.2(8)\times 10^{-12} \, \rm dd^{-1}$. This can be explained by the non-synchronized hot subdwarf star being spun up by tidal interactions forcing it to become synchronized. From the rate of period decrease we could derive the synchronization time-scale to be 4 Myr, much smaller than the lifetime on EHB. By combining all different methods, we could constrain the hot subdwarf to a mass of $0.39\!-\!0.50\, \rm M_\odot$ and a radius of $R_{\rm sdB}=0.194\pm 0.008\, \rm R_\odot$, and the companion to $0.061\!-\!0.071\rm \, M_\odot$ with a radius of $R_{\rm comp}=0.092 \pm 0.005\, \rm R_\odot$, below the hydrogen-burning limit. We therefore confirm that the companion is most likely a massive brown dwarf.
A new transient ultraluminous X-ray source in NGC 7090
Authors: Walton D J , Heida M , Bachetti M , Fürst F , Brightman M , Earnshaw H , Evans P A , Fabian A C , Grefenstette B W , Harrison F A , Israel G L , Lansbury G B , Middleton M J , Pike S , Rana V , Roberts T P , Rodriguez Castillo G A , Salvaterra R , Song X , Stern D 
Published: November 2020

ABSTRACT
We report on the discovery of a new, transient ultraluminous X-ray source (ULX) in the galaxy NGC 7090. This new ULX, which we refer to as NGC 7090 ULX3, was discovered via monitoring with Swift during 2019–2020, and to date has exhibited a peak luminosity of LX ∼ 6 × 1039 erg s−1. Archival searches show that, prior to its recent transition into the ULX regime, ULX3 appeared to exhibit a fairly stable luminosity of LX ∼ 1038 erg s−1. Such strong long-time-scale variability may be reminiscent of the small population of known ULX pulsars, although deep follow-up observations with XMM–Newton and NuSTAR do not reveal any robust X-ray pulsation signals. Pulsations similar to those seen from known ULX pulsars cannot be completely excluded, however, as the limit on the pulsed fraction of any signal that remains undetected in these data is ≲20 per cent. The broad-band spectrum from these observations is well modelled with a simple thin disc model, consistent with sub-Eddington accretion, which may instead imply a moderately large black hole accretor (MBH ∼ 40 M⊙). Similarly, though, more complex models consistent with the super-Eddington spectra seen in other ULXs (and the known ULX pulsars) cannot be excluded given the limited signal-to-noise ratio of the available broad-band data. The nature of the accretor powering this new ULX therefore remains uncertain.
AstroVaDEr: astronomical variational deep embedder for unsupervised morphological classification of galaxies and synthetic image generation
Authors: Spindler Ashley , Geach James E , Smith Michael J 
Published: November 2020

ABSTRACTWe present AstroVaDEr (Astronomical Variational Deep Embedder), a variational autoencoder designed to perform unsupervised clustering and synthetic image generation using astronomical imaging catalogues. The model is a convolutional neural network that learns to embed images into a low-dimensional latent space, and simultaneously optimizes a Gaussian Mixture Model (GMM) on the embedded vectors to cluster the training data. By utilizing variational inference, we are able to use the learned GMM as a statistical prior on the latent space to facilitate random sampling and generation of synthetic images. We demonstrate AstroVaDEr’s capabilities by training it on grey-scaled gri images from the Sloan Digital Sky Survey, using a sample of galaxies that are classified by Galaxy Zoo 2. An unsupervised clustering model is found that separates galaxies based on learned morphological features such as axial ratio, surface brightness profile, orientation, and the presence of companions. We use the learned mixture model to generate synthetic images of galaxies based on the morphological profiles of the Gaussian components. AstroVaDEr succeeds in producing a morphological classification scheme from unlabelled data, but unexpectedly places high importance on the presence of companion objects – demonstrating the importance of human interpretation. The network is scalable and flexible, allowing for larger data sets to be classified, or different kinds of imaging data. We also demonstrate the generative properties of the model, which allow for realistic synthetic images of galaxies to be sampled from the learned classification scheme. These can be used to create synthetic image catalogues or to perform image processing tasks such as deblending.