18 research outputs found

    Inter-expert and intra-expert reliability in sleep spindle scoring

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    Objectives: To measure the inter-expert and intra-expert agreement in sleep spindle scoring, and to quantify how many experts are needed to build a reliable dataset of sleep spindle scorings. Methods: The EEG dataset was comprised of 400 randomly selected 115 s segments of stage 2 sleep from 110 sleeping subjects in the general population (57 ± 8, range: 42–72 years). To assess expert agreement, a total of 24 Registered Polysomnographic Technologists (RPSGTs) scored spindles in a subset of the EEG dataset at a single electrode location (C3-M2). Intra-expert and inter-expert agreements were calculated as F_1-scores, Cohen’s kappa (κ), and intra-class correlation coefficient (ICC). Results: We found an average intra-expert F_1-score agreement of 72 ± 7% (κ: 0.66 ± 0.07). The average inter-expert agreement was 61 ± 6% (κ: 0.52 ± 0.07). Amplitude and frequency of discrete spindles were calculated with higher reliability than the estimation of spindle duration. Reliability of sleep spindle scoring can be improved by using qualitative confidence scores, rather than a dichotomous yes/no scoring system. Conclusions: We estimate that 2–3 experts are needed to build a spindle scoring dataset with ‘substantial’ reliability (κ: 0.61–0.8), and 4 or more experts are needed to build a dataset with ‘almost perfect’ reliability (κ: 0.81–1). Significance: Spindle scoring is a critical part of sleep staging, and spindles are believed to play an important role in development, aging, and diseases of the nervous system

    CXC receptor-4 mRNA silencing abrogates CXCL12-induced migration of colorectal cancer cells

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    <p>Abstract</p> <p>Background</p> <p>Interactions between CXCR4 and its ligand CXCL12 have been shown to be involved in cancer progression in colorectal cancer (CRC). We performed a comparative CXCL12/CXCR4 expression analysis and assessed the effect of external CXCL12 stimulation on migration of CRC cells without and with CXCR4 inhibition.</p> <p>Methods</p> <p>Expression of CXCL12/CXCR4 was assessed by quantitative real-time PCR, ELISA and immunohistochemistry in resection specimens of 50 CRC patients as well as in the corresponding normal tissues and in three human CRC cell lines with different metastatic potential (Caco-2, SW480 and HT-29). Migration assays were performed after stimulation with CXCL12 and CXCR4 was inhibited by siRNA and neutralizing antibodies.</p> <p>Results</p> <p>In CRC tissues CXCL12 was significantly down-regulated and CXCR4 was significantly up-regulated compared to the corresponding normal tissues. In cell lines CXCR4 was predominantly expressed in SW480 and less pronounced in HT-29 cells. CXCL12 was only detectable in Caco-2 cells. CXCL12 stimulation had no impact on Caco-2 cells but significantly increased migration of CXCR4 bearing SW480 and HT-29 cells. This effect was significantly abrogated by neutralizing anti-CXCR4 antibody as well as by CXCR4 siRNAs (P < 0.05).</p> <p>Conclusions</p> <p>CXCR4 expression was up-regulated in CRC and CXCL12 stimulation increased migration in CXCR4 bearing cell lines. Migration was inhibited by both neutralizing CXCR4 antibodies and CXCR4 siRNAs. Thus, the expression and functionality of CXCR4 might be associated with the metastatic potential of CRC cells and CXCL12/CXCR4 interactions might therefore constitute a promising target for specific treatment interventions.</p

    The D4Z4 Macrosatellite Repeat Acts as a CTCF and A-Type Lamins-Dependent Insulator in Facio-Scapulo-Humeral Dystrophy

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    Both genetic and epigenetic alterations contribute to Facio-Scapulo-Humeral Dystrophy (FSHD), which is linked to the shortening of the array of D4Z4 repeats at the 4q35 locus. The consequence of this rearrangement remains enigmatic, but deletion of this 3.3-kb macrosatellite element might affect the expression of the FSHD-associated gene(s) through position effect mechanisms. We investigated this hypothesis by creating a large collection of constructs carrying 1 to >11 D4Z4 repeats integrated into the human genome, either at random sites or proximal to a telomere, mimicking thereby the organization of the 4q35 locus. We show that D4Z4 acts as an insulator that interferes with enhancer–promoter communication and protects transgenes from position effect. This last property depends on both CTCF and A-type Lamins. We further demonstrate that both anti-silencing activity of D4Z4 and CTCF binding are lost upon multimerization of the repeat in cells from FSHD patients compared to control myoblasts from healthy individuals, suggesting that FSHD corresponds to a gain-of-function of CTCF at the residual D4Z4 repeats. We propose that contraction of the D4Z4 array contributes to FSHD physio-pathology by acting as a CTCF-dependent insulator in patients

    Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods

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    Sleep spindles are discrete, intermittent patterns of brain activity observed in human electroencephalographic data. Increasingly, these oscillations are of biological and clinical interest because of their role in development, learning and neurological disorders. We used an Internet interface to crowdsource spindle identification by human experts and non-experts, and we compared their performance with that of automated detection algorithms in data from middle- to older-aged subjects from the general population. We also refined methods for forming group consensus and evaluating the performance of event detectors in physiological data such as electroencephalographic recordings from polysomnography. Compared to the expert group consensus gold standard, the highest performance was by individual experts and the non-expert group consensus, followed by automated spindle detectors. This analysis showed that crowdsourcing the scoring of sleep data is an efficient method to collect large data sets, even for difficult tasks such as spindle identification. Further refinements to spindle detection algorithms are needed for middle- to older-aged subjects

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

    Multi-messenger Observations of a Binary Neutron Star Merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 {{s}} with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of {40}-8+8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 {M}ȯ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 {{Mpc}}) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.</p

    Estimating plastic pollution levels in rivers through harmonized monitoring strategies

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    Plastic pollution in freshwater environments is an emerging threat to ecosystem health and human livelihood. Plastics that accumulate in rivers and lakes over long time periods have direct local impact, and may eventually also reach the world’s oceans. Monitoring river plastic pollution is therefore key to quantify, understand and reduce plastics in all aquatic ecosystems. Unfortunately, global river plastic monitoring is still in its early stage. The lack of harmonization between ongoing monitoring efforts compromises the direct comparison and combination of available data. Recently, the United Nations Environment Programme (UNEP) launched guidelines on plastic monitoring in rivers and lakes, to provide a starting point for practitioners and scientists towards harmonized data collection, analysis, and reporting. Here, we demonstrate the application of those guidelines through a practical workflow to support to design effective plastic monitoring strategies. The workflow is a five-step iterative approach that aims to match the defined research goal or question to the available resources and river basin characteristics. To test the relevance of the workflow in different settings, we applied the workflow to three rivers across relevant gradients, including geography, hydrology, and plastic pollution levels. In the Rhine basin (Switzerland, France, Germany, the Netherlands) we showed that urban areas and tributaries may act as entry points of plastic pollution. For the Odaw basin (Ghana) we compared floating, terrestrial and riverbank plastics, identifying source and accumulation zones. Finally, in the Mekong river (Cambodia) we quantified the contribution of the city of Phnom Penh to plastic pollution through quantifying the plastic mass balance in the Mekong-Tonle Sap-Bassac region. We show that despite the simplicity of the selected methods and the limited duration of the data collection, a harmonized approach can provide crucial insights in the state of plastic pollution in very different river basins. Although each case study focused on one specific goal, each one is directly transferable to any river globally. Data collection is key in reaching local, regional and global goals on reducing plastic pollution. With our paper we aim to provide a simple workflow to support the design of effective and comparable river plastic monitoring strategies

    Mapping the human genetic architecture of COVID-19

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    The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3–7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease
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