321 research outputs found

    Investigating chromosomal instability in long-term survivors with glioblastoma and grade 4 astrocytoma

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    Background Only a small group of patients with glioblastoma multiforme (GBM) survives more than 36 months, so-called long-term survivors. Recent studies have shown that chromosomal instability (CIN) plays a prognostic and predictive role among different cancer types. Here, we compared histological (chromosome missegregation) and bioinformatic metrics (CIN signatures) of CIN in tumors of GBM typical survivors (<= 36 months overall survival), GBM long-term survivors and isocitrate dehydrogenase (IDH)-mutant grade 4 astrocytomas.Methods Tumor sections of all gliomas were examined for anaphases and chromosome missegregation. Further CIN signature activity analysis in the The Cancer Genome Atlas (TCGA)-GBM cohort was performed.Results Our data show that chromosome missegregation is pervasive in high grade gliomas and is not different between the 3 groups. We find only limited evidence of altered CIN levels in tumors of GBM long-term survivors relative to the other groups, since a significant depletion in CIN signature 11 relative to GBM typical survivors was the only alteration detected. In contrast, within IDH-mutant grade 4 astrocytomas we detected a significant enrichment of CIN signature 5 and 10 activities and a depletion of CIN signature 1 activity relative to tumors of GBM typical survivors.Conclusions Our data suggest that CIN is pervasive in high grade gliomas, however this is unlikely to be a major contributor to the phenomenon of long-term survivorship in GBM. Nevertheless, further evaluation of specific types of CIN (signatures) could have prognostic value in patients suffering from grade 4 gliomas

    Review of the mathematical foundations of data fusion techniques in surface metrology

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    The recent proliferation of engineered surfaces, including freeform and structured surfaces, is challenging current metrology techniques. Measurement using multiple sensors has been proposed to achieve enhanced benefits, mainly in terms of spatial frequency bandwidth, which a single sensor cannot provide. When using data from different sensors, a process of data fusion is required and there is much active research in this area. In this paper, current data fusion methods and applications are reviewed, with a focus on the mathematical foundations of the subject. Common research questions in the fusion of surface metrology data are raised and potential fusion algorithms are discussed

    Characterisation of the topography of metal additive surface features with different measurement technologies

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    The challenges of measuring the surface topography of metallic surfaces produced by additive manufacturing are investigated. The differences between measurements made using various optical and non-optical technologies, including confocal and focus-variation microscopy, coherence scanning interferometry and x-ray computed tomography, are examined. As opposed to concentrating on differences which may arise through computing surface texture parameters from measured topography datasets, a comparative analysis is performed focussing on investigation of the quality of the topographic reconstruction of a series of surface features. The investigation is carried out by considering the typical surface features of a metal powder-bed fusion process: weld tracks, weld ripples, attached particles and surface recesses. Results show that no single measurement technology provides a completely reliable rendition of the topographic features that characterise the metal powder-bed fusion process. However, through analysis of measurement discrepancies, light can be shed on where instruments are more susceptible to error, and why differences between measurements occur. The results presented in this work increase the understanding of the behaviour and performance of areal topography measurement, and thus promote the development of improved surface characterisation pipelines

    An intranasal ASO therapeutic targeting SARS-CoV-2

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    The COVID-19 pandemic is exacting an increasing toll worldwide, with new SARS-CoV-2 variants emerging that exhibit higher infectivity rates and that may partially evade vaccine and antibody immunity. Rapid deployment of non-invasive therapeutic avenues capable of preventing infection by all SARS-CoV-2 variants could complement current vaccination efforts and help turn the tide on the COVID-19 pandemic. Here, we describe a novel therapeutic strategy targeting the SARS-CoV-2 RNA using locked nucleic acid antisense oligonucleotides (LNA ASOs). We identify an LNA ASO binding to the 5′ leader sequence of SARS-CoV-2 that disrupts a highly conserved stem-loop structure with nanomolar efficacy in preventing viral replication in human cells. Daily intranasal administration of this LNA ASO in the COVID-19 mouse model potently suppresses viral replication (>80-fold) in the lungs of infected mice. We find that the LNA ASO is efficacious in countering all SARS-CoV-2 “variants of concern” tested both in vitro and in vivo. Hence, inhaled LNA ASOs targeting SARS-CoV-2 represents a promising therapeutic approach to reduce or prevent transmission and decrease severity of COVID-19 in infected individuals. LNA ASOs are chemically stable and can be flexibly modified to target different viral RNA sequences and could be stockpiled for future coronavirus pandemics

    Combined Point-of-Care Nucleic Acid and Antibody Testing for SARS-CoV-2 following Emergence of D614G Spike Variant

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    Rapid COVID-19 diagnosis in the hospital is essential, although this is complicated by 30%-50% of nose/throat swabs being negative by SARS-CoV-2 nucleic acid amplification testing (NAAT). Furthermore, the D614G spike mutant dominates the pandemic and it is unclear how serological tests designed to detect anti-spike antibodies perform against this variant. We assess the diagnostic accuracy of combined rapid antibody point of care (POC) and nucleic acid assays for suspected COVID-19 disease due to either wild-type or the D614G spike mutant SARS-CoV-2. The overall detection rate for COVID-19 is 79.2% (95% CI 57.8-92.9) by rapid NAAT alone. The combined point of care antibody test and rapid NAAT is not affected by D614G and results in very high sensitivity for COVID-19 diagnosis with very high specificity
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