251 research outputs found

    TNPO2 variants associate with human developmental delays, neurologic deficits, and dysmorphic features and alter TNPO2 activity in Drosophila

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    Transportin-2 (TNPO2) mediates multiple pathways including non-classical nucleocytoplasmic shuttling of >60 cargoes, such as developmental and neuronal proteins. We identified 15 individuals carrying de novo coding variants in TNPO2 who presented with global developmental delay (GDD), dysmorphic features, ophthalmologic abnormalities, and neurological features. To assess the nature of these variants, functional studies were performed in Drosophila. We found that fly dTnpo (orthologous to TNPO2) is expressed in a subset of neurons. dTnpo is critical for neuronal maintenance and function as downregulating dTnpo in mature neurons using RNAi disrupts neuronal activity and survival. Altering the activity and expression of dTnpo using mutant alleles or RNAi causes developmental defects, including eye and wing deformities and lethality. These effects are dosage dependent as more severe phenotypes are associated with stronger dTnpo loss. Interestingly, similar phenotypes are observed with dTnpo upregulation and ectopic expression of TNPO2, showing that loss and gain of Transportin activity causes developmental defects. Further, proband-associated variants can cause more or less severe developmental abnormalities compared to wild-type TNPO2 when ectopically expressed. The impact of the variants tested seems to correlate with their position within the protein. Specifically, those that fall within the RAN binding domain cause more severe toxicity and those in the acidic loop are less toxic. Variants within the cargo binding domain show tissue-dependent effects. In summary, dTnpo is an essential gene in flies during development and in neurons. Further, proband-associated de novo variants within TNPO2 disrupt the function of the encoded protein. Hence, TNPO2 variants are causative for neurodevelopmental abnormalities

    Genomic Expression Analysis Reveals Strategies of Burkholderia cenocepacia to Adapt to Cystic Fibrosis Patients' Airways and Antimicrobial Therapy

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    Pulmonary colonization of cystic fibrosis (CF) patients with Burkholderia cenocepacia or other bacteria of the Burkholderia cepacia complex (Bcc) is associated with worse prognosis and increased risk of death. During colonization, the bacteria may evolve under the stressing selection pressures exerted in the CF lung, in particular, those resulting from challenges of the host immune defenses, antimicrobial therapy, nutrient availability and oxygen limitation. Understanding the adaptive mechanisms that promote successful colonization and long-term survival of B. cenocepacia in the CF lung is essential for an improved therapeutic outcome of chronic infections. To get mechanistic insights into these adaptive strategies a transcriptomic analysis, based on DNA microarrays, was explored in this study. The genomic expression levels in two clonal variants isolated during long-term colonization of a CF patient who died from the cepacia syndrome were compared. One of the isolates examined, IST439, is the first B. cenocepacia isolate retrieved from the patient and the other isolate, IST4113, was obtained three years later and is more resistant to different classes of antimicrobials. Approximately 1000 genes were found to be differently expressed in the two clonal variants reflecting a marked reprogramming of genomic expression. The up-regulated genes in IST4113 include those involved in translation, iron uptake (in particular, in ornibactin biosynthesis), efflux of drugs and in adhesion to epithelial lung tissue and to mucin. Alterations related with adaptation to the nutritional environment of the CF lung and to an oxygen-limited environment are also suggested to be a key feature of transcriptional reprogramming occurring during long-term colonization, antibiotic therapy and the progression of the disease

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

    The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

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    We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

    Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

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    Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

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    Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

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