A Molecular-Assisted Alpha Taxonomic Study of the Genus \u3cem\u3eCentroceras\u3c/em\u3e (Ceramiaceae, Rhodophyta) in Bermuda Reveals Two Novel Species

When the generitype Centroceras clavulatum, a presumed cosmopolitan warm temperate to tropical red alga, was discovered to have a biogeographic distribution limited to the Pacific Ocean using molecular and morphological evidence, the taxonomy in the genus Centroceras was thrown into chaos worldwide. An analysis of what species was, or were, previously identified as C. clavulatum in Bermuda is the focus of the present molecular (COI-5P, rbcL) and morphological study. Two novel species are proposed, C. arcii sp. nov. and C. illaqueans sp. nov., and the distributions of three taxa recently segregated in the \u27C. clavulatum complex\u27 of the western Atlantic, C. gasparrinii, C. hyalacanthum, and C. micracanthum, have been expanded to include Bermuda. C. arcii is shown to be morphologically cryptic with C. micracanthum, and remains best distinguished by its COI-5P barcode sequence

Automated multi-beat tissue Doppler echocardiography analysis using deep neural networks

Tissue Doppler imaging is an essential echocardiographic technique for the non-invasive assessment of myocardial blood velocity. Image acquisition and interpretation are performed by trained operators who visually localise landmarks representing Doppler peak velocities. Current clinical guidelines recommend averaging measurements over several heartbeats. However, this manual process is both time-consuming and disruptive to workflow. An automated system for accurate beat isolation and landmark identification would be highly desirable. A dataset of tissue Doppler images was annotated by three cardiologist experts, providing a gold standard and allowing for observer variability comparisons. Deep neural networks were trained for fully automated predictions on multiple heartbeats and tested on tissue Doppler strips of arbitrary length. Automated measurements of peak Doppler velocities show good Bland–Altman agreement (average standard deviation of 0.40 cm/s) with consensus expert values; less than the inter-observer variability (0.65 cm/s). Performance is akin to individual experts (standard deviation of 0.40 to 0.75 cm/s). Our approach allows for > 26 times as many heartbeats to be analysed, compared to a manual approach. The proposed automated models can accurately and reliably make measurements on tissue Doppler images spanning several heartbeats, with performance indistinguishable from that of human experts, but with significantly shorter processing time

Multibeat echocardiographic phase detection using deep neural networks

Background Accurate identification of end-diastolic and end-systolic frames in echocardiographic cine loops is important, yet challenging, for human experts. Manual frame selection is subject to uncertainty, affecting crucial clinical measurements, such as myocardial strain. Therefore, the ability to automatically detect frames of interest is highly desirable. Methods We have developed deep neural networks, trained and tested on multi-centre patient data, for the accurate identification of end-diastolic and end-systolic frames in apical four-chamber 2D multibeat cine loop recordings of arbitrary length. Seven experienced cardiologist experts independently labelled the frames of interest, thereby providing infallible annotations, allowing for observer variability measurements. Results When compared with the ground-truth, our model shows an average frame difference of −0.09 ± 1.10 and 0.11 ± 1.29 frames for end-diastolic and end-systolic frames, respectively. When applied to patient datasets from a different clinical site, to which the model was blind during its development, average frame differences of −1.34 ± 3.27 and −0.31 ± 3.37 frames were obtained for both frames of interest. All detection errors fall within the range of inter-observer variability: [-0.87, −5.51]±[2.29, 4.26] and [-0.97, −3.46]±[3.67, 4.68] for ED and ES events, respectively. Conclusions The proposed automated model can identify multiple end-systolic and end-diastolic frames in echocardiographic videos of arbitrary length with performance indistinguishable from that of human experts, but with significantly shorter processing time

Neural architecture search of echocardiography view classifiers

Purpose: Echocardiography is the most commonly used modality for assessing the heart in clinical practice. In an echocardiographic exam, an ultrasound probe samples the heart from different orientations and positions, thereby creating different viewpoints for assessing the cardiac function. The determination of the probe viewpoint forms an essential step in automatic echocardiographic image analysis. Approach: In this study, convolutional neural networks are used for the automated identification of 14 different anatomical echocardiographic views (larger than any previous study) in a dataset of 8732 videos acquired from 374 patients. Differentiable architecture search approach was utilized to design small neural network architectures for rapid inference while maintaining high accuracy. The impact of the image quality and resolution, size of the training dataset, and number of echocardiographic view classes on the efficacy of the models were also investigated. Results: In contrast to the deeper classification architectures, the proposed models had significantly lower number of trainable parameters (up to 99.9% reduction), achieved comparable classification performance (accuracy 88.4% to 96%, precision 87.8% to 95.2%, recall 87.1% to 95.1%) and real-time performance with inference time per image of 3.6 to 12.6 ms. Conclusion: Compared with the standard classification neural network architectures, the proposed models are faster and achieve comparable classification performance. They also require less training data. Such models can be used for real-time detection of the standard views

Fat, syn and disordered eating: The dangers and powers of excess

This is an accepted manuscript of an article published by Taylor & Francis in Fat Studies on 8 April 2015 available online: http://wwww.tandfonline.com/10.1080/21604851.2015.1016777This article draws on qualitative research inside one UK secular commercial weight loss group to show how ancient Christian suspicions of appetite and pleasure resurface in this group’s language of “Syn.” Following ancient Christian representations of sin, members assume that Syn depicts disorder and that fat is a visible sign of a body which has fallen out of place. Syn, though, is ambiguous, utilizing ancient theological meanings to discipline fat while containing within it the power to resist the very borders which hold women’s bodies and fat in place. Syn thus signals both the dangers and powers of disordered eating.This article draws on qualitative research inside one UK secular commercial weight loss group to show how ancient Christian suspicions of appetite and pleasure resurface in this group’s language of “Syn.” Following ancient Christian representations of sin, members assume that Syn depicts disorder and that fat is a visible sign of a body which has fallen out of place. Syn, though, is ambiguous, utilizing ancient theological meanings to discipline fat while containing within it the power to resist the very borders which hold women’s bodies and fat in place. Syn thus signals both the dangers and powers of disordered eating

Search for composite and exotic fermions at LEP 2

A search for unstable heavy fermions with the DELPHI detector at LEP is reported. Sequential and non-canonical leptons, as well as excited leptons and quarks, are considered. The data analysed correspond to an integrated luminosity of about 48 pb^{-1} at an e^+e^- centre-of-mass energy of 183 GeV and about 20 pb^{-1} equally shared between the centre-of-mass energies of 172 GeV and 161 GeV. The search for pair-produced new leptons establishes 95% confidence level mass limits in the region between 70 GeV/c^2 and 90 GeV/c^2, depending on the channel. The search for singly produced excited leptons and quarks establishes upper limits on the ratio of the coupling of the excited fermio

Search for lightest neutralino and stau pair production in light gravitino scenarios with stau NLSP

Promptly decaying lightest neutralinos and long-lived staus are searched for in the context of light gravitino scenarios. It is assumed that the stau is the next to lightest supersymmetric particle (NLSP) and that the lightest neutralino is the next to NLSP (NNLSP). Data collected with the Delphi detector at centre-of-mass energies from 161 to 183 \GeV are analysed. No evidence of the production of these particles is found. Hence, lower mass limits for both kinds of particles are set at 95% C.L.. The mass of gaugino-like neutralinos is found to be greater than 71.5 GeV/c^2. In the search for long-lived stau, masses less than 70.0 to 77.5 \GeVcc are excluded for gravitino masses from 10 to 150 \eVcc . Combining this search with the searches for stable heavy leptons and Minimal Supersymmetric Standard Model staus a lower limit of 68.5 \GeVcc may be set for the stau mas

Automated mitral inflow Doppler peak velocity measurement using deep learning

Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce variability, prompting the need for automated solutions. This study introduces an innovative deep learning model for automated detection of peak velocity measurements from mitral inflow Doppler images, independent from Electrocardiogram information. A dataset of Doppler images annotated by multiple expert cardiologists was established, serving as a robust benchmark. The model leverages heatmap regression networks, achieving 96% detection accuracy. The model discrepancy with the expert consensus falls comfortably within the range of inter- and intra-observer variability in measuring Doppler peak velocities. The dataset and models are open-source, fostering further research and clinical application

Imaging of Bubonic Plague Dynamics by In Vivo Tracking of Bioluminescent Yersinia pestis

Yersinia pestis dissemination in a host is usually studied by enumerating bacteria in the tissues of animals sacrificed at different times. This laborious methodology gives only snapshots of the infection, as the infectious process is not synchronized. In this work we used in vivo bioluminescence imaging (BLI) to follow Y. pestis dissemination during bubonic plague. We first demonstrated that Y. pestis CO92 transformed with pGEN-luxCDABE stably emitted bioluminescence in vitro and in vivo, while retaining full virulence. The light produced from live animals allowed to delineate the infected organs and correlated with bacterial loads, thus validating the BLI tool. We then showed that the first step of the infectious process is a bacterial multiplication at the injection site (linea alba), followed by a colonization of the draining inguinal lymph node(s), and subsequently of the ipsilateral axillary lymph node through a direct connection between the two nodes. A mild bacteremia and an effective filtering of the blood stream by the liver and spleen probably accounted for the early bacterial blood clearance and the simultaneous development of bacterial foci within these organs. The saturation of the filtering capacity of the spleen and liver subsequently led to terminal septicemia. Our results also indicate that secondary lymphoid tissues are the main targets of Y. pestis multiplication and that colonization of other organs occurs essentially at the terminal phase of the disease. Finally, our analysis reveals that the high variability in the kinetics of infection is attributable to the time the bacteria remain confined at the injection site. However, once Y. pestis has reached the draining lymph nodes, the disease progresses extremely rapidly, leading to the invasion of the entire body within two days and to death of the animals. This highlights the extraordinary capacity of Y. pestis to annihilate the host innate immune response

Epigenetic Regulation of a Murine Retrotransposon by a Dual Histone Modification Mark

Large fractions of eukaryotic genomes contain repetitive sequences of which the vast majority is derived from transposable elements (TEs). In order to inactivate those potentially harmful elements, host organisms silence TEs via methylation of transposon DNA and packaging into chromatin associated with repressive histone marks. The contribution of individual histone modifications in this process is not completely resolved. Therefore, we aimed to define the role of reversible histone acetylation, a modification commonly associated with transcriptional activity, in transcriptional regulation of murine TEs. We surveyed histone acetylation patterns and expression levels of ten different murine TEs in mouse fibroblasts with altered histone acetylation levels, which was achieved via chemical HDAC inhibition with trichostatin A (TSA), or genetic inactivation of the major deacetylase HDAC1. We found that one LTR retrotransposon family encompassing virus-like 30S elements (VL30) showed significant histone H3 hyperacetylation and strong transcriptional activation in response to TSA treatment. Analysis of VL30 transcripts revealed that increased VL30 transcription is due to enhanced expression of a limited number of genomic elements, with one locus being particularly responsive to HDAC inhibition. Importantly, transcriptional induction of VL30 was entirely dependent on the activation of MAP kinase pathways, resulting in serine 10 phosphorylation at histone H3. Stimulation of MAP kinase cascades together with HDAC inhibition led to simultaneous phosphorylation and acetylation (phosphoacetylation) of histone H3 at the VL30 regulatory region. The presence of the phosphoacetylation mark at VL30 LTRs was linked with full transcriptional activation of the mobile element. Our data indicate that the activity of different TEs is controlled by distinct chromatin modifications. We show that activation of a specific mobile element is linked to a dual epigenetic mark and propose a model whereby phosphoacetylation of histone H3 is crucial for full transcriptional activation of VL30 elements