852 research outputs found

    An Immobilised Silicon‐Carbon Bond‐Forming Enzyme for Anaerobic Flow Biocatalysis

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    The recent development of tailored cytochrome enzymes has enabled “new-to-nature” reactivities, such as the biocatalytic formation of carbon-silicon bonds using the cytochrome c from Rhodothermus marinus. To maximise the potential of this remarkable biocatalyst by increasing its turnover numbers (TON) and to enable its reusability in continuous processes, we report the use of the SpyTag/SpyCatcher bioconjugation system to immobilise this enzyme. We successfully modified the enzyme with a SpyTag without significant effects on its catalytic activity. Even after immobilization on microparticles the enzyme retained 60 % activity. When the immobilized enzyme was used in sequential batch or continuous flow to produce an organosilicon, we observed up to 6-fold higher turnover numbers over a total period of 10 days compared to the free enzyme reaction, however we observed a drop in stereoselectivity under these conditions. This is the first report on the successful immobilisation of a carbon-silicon bond forming enzyme for the continuous, biocatalytic production of organosilicons

    The influence of a magnetic field on photon beam radiotherapy in a normal human TK6 lymphoblastoid cell line

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    Background: The implementation of magnetic resonance imaging (MRI) guided radiotherapy (RT) continues to increase. Very limited in-vitro data on the interaction of ionizing radiation and magnetic fields (MF) have been published. In these experiments we focused on the radiation response in a MF of the TK6 human lymphoblastoid cells which are known to be highly radiosensitive due to efficient radiation-induced apoptosis. Methods: Clonogenicity was determined 12–14 days after irradiation with 1–4 Gy 6 MV photons with or without a 1.0 Tesla MF. Furthermore, alterations in cell cycle distribution and rates of radiation induced apoptosis (FACS analysis of cells with sub-G1 DNA content) were analyzed. Results: Clonogenic survival showed an exponential dose-dependence, and the radiation sensitivity parameter (α = 1.57/Gy) was in accordance with earlier reports. Upon comparing the clonogenic survival between the two groups, identical results within error bars were obtained. The survival fractions at 2 Gy were 9% (without MF) and 8.5% (with MF), respectively. Conclusion: A 1.0 Tesla MF does not affect the clonogenicity of TK6 cells irradiated with 1–4 Gy 6MV photons. This supports the use of MRI guided RT, however ongoing research on the interaction of MF and radiotherapy is warranted

    Myeloid cell iron uptake pathways and paramagnetic rim formation in multiple sclerosis

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    In multiple sclerosis (MS), sustained inflammatory activity can be visualized by iron-sensitive magnetic resonance imaging (MRI) at the edges of chronic lesions. These paramagnetic rim lesions (PRLs) are associated with clinical worsening, although the cell type-specific and molecular pathways of iron uptake and metabolism are not well known. We studied two postmortem cohorts: an exploratory formalin-fixed paraffin-embedded (FFPE) tissue cohort of 18 controls and 24 MS cases and a confirmatory snap-frozen cohort of 6 controls and 14 MS cases. Besides myelin and non-heme iron imaging, the haptoglobin-hemoglobin scavenger receptor CD163, the iron-metabolizing markers HMOX1 and HAMP as well as immune-related markers P2RY12, CD68, C1QA and IL10 were visualized in myeloid cell (MC) subtypes at RNA and protein levels across different MS lesion areas. In addition, we studied PRLs in vivo in a cohort of 98 people with MS (pwMS) via iron-sensitive 3 T MRI and haptoglobin genotyping by PCR. CSF samples were available from 38 pwMS for soluble CD163 (sCD163) protein level measurements by ELISA. In postmortem tissues, we observed that iron uptake was linked to rim-associated C1QA-expressing MC subtypes, characterized by upregulation of CD163, HMOX1, HAMP and, conversely, downregulation of P2RY12. We found that pwMS with [Formula: see text] 4 PRLs had higher sCD163 levels in the CSF than pwMS with [Formula: see text] 3 PRLs with sCD163 correlating with the number of PRLs. The number of PRLs was associated with clinical worsening but not with age, sex or haptoglobin genotype of pwMS. However, pwMS with Hp2-1/Hp2-2 haplotypes had higher clinical disability scores than pwMS with Hp1-1. In summary, we observed upregulation of the CD163-HMOX1-HAMP axis in MC subtypes at chronic active lesion rims, suggesting haptoglobin-bound hemoglobin but not transferrin-bound iron as a critical source for MC-associated iron uptake in MS. The correlation of CSF-associated sCD163 with PRL counts in MS highlights the relevance of CD163-mediated iron uptake via haptoglobin-bound hemoglobin. Also, while Hp haplotypes had no noticeable influence on PRL counts, pwMS carriers of a Hp2 allele might have a higher risk to experience clinical worsening

    Consumer perceptions of co-branding alliances: Organizational dissimilarity signals and brand fit

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    This study explores how consumers evaluate co-branding alliances between dissimilar partner firms. Customers are well aware that different firms are behind a co-branded product and observe the partner firms’ characteristics. Drawing on signaling theory, we assert that consumers use organizational characteristics as signals in their assessment of brand fit and for their purchasing decisions. Some organizational signals are beyond the control of the co-branding partners or at least they cannot alter them on short notice. We use a quasi-experimental design and test how co-branding partner dissimilarity affects brand fit perception. The results show that co-branding partner dissimilarity in terms of firm size, industry scope, and country-of-origin image negatively affects brand fit perception. Firm age dissimilarity does not exert significant influence. Because brand fit generally fosters a benevolent consumer attitude towards a co-branding alliance, the findings suggest that high partner dissimilarity may reduce overall co-branding alliance performance

    Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

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    Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

    A prognostic neural epigenetic signature in high-grade glioma

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    Neural-tumor interactions drive glioma growth as evidenced in preclinical models, but clinical validation is limited. We present an epigenetically defined neural signature of glioblastoma that independently predicts patients' survival. We use reference signatures of neural cells to deconvolve tumor DNA and classify samples into low- or high-neural tumors. High-neural glioblastomas exhibit hypomethylated CpG sites and upregulation of genes associated with synaptic integration. Single-cell transcriptomic analysis reveals a high abundance of malignant stemcell-like cells in high-neural glioblastoma, primarily of the neural lineage. These cells are further classified as neural-progenitor-cell-like, astrocyte-like and oligodendrocyte-progenitor-like, alongside oligodendrocytes and excitatory neurons. In line with these findings, high-neural glioblastoma cells engender neuron-to-glioma synapse formation in vitro and in vivo and show an unfavorable survival after xenografting. In patients, a high-neural signature is associated with decreased overall and progression-free survival. High-neural tumors also exhibit increased functional connectivity in magnetencephalography and resting-state magnet resonance imaging and can be detected via DNA analytes and brain-derived neurotrophic factor in patients' plasma. The prognostic importance of the neural signature was further validated in patients diagnosed with diffuse midline glioma. Our study presents an epigenetically defined malignant neural signature in high-grade gliomas that is prognostically relevant. High-neural gliomas likely require a maximized surgical resection approach for improved outcomes

    Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease

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    Background: Although convolutional neural networks (CNN) achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) dementia based on magnetic resonance imaging (MRI) scans, they are not yet applied in clinical routine. One important reason for this is a lack of model comprehensibility. Recently developed visualization methods for deriving CNN relevance maps may help to fill this gap. We investigated whether models with higher accuracy also rely more on discriminative brain regions predefined by prior knowledge. Methods: We trained a CNN for the detection of AD in N=663 T1-weighted MRI scans of patients with dementia and amnestic mild cognitive impairment (MCI) and verified the accuracy of the models via cross-validation and in three independent samples including N=1655 cases. We evaluated the association of relevance scores and hippocampus volume to validate the clinical utility of this approach. To improve model comprehensibility, we implemented an interactive visualization of 3D CNN relevance maps. Results: Across three independent datasets, group separation showed high accuracy for AD dementia vs. controls (AUC≄\geq0.92) and moderate accuracy for MCI vs. controls (AUC≈\approx0.75). Relevance maps indicated that hippocampal atrophy was considered as the most informative factor for AD detection, with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (Pearson's r≈\approx-0.86, p<0.001). Conclusion: The relevance maps highlighted atrophy in regions that we had hypothesized a priori. This strengthens the comprehensibility of the CNN models, which were trained in a purely data-driven manner based on the scans and diagnosis labels.Comment: 24 pages, 9 figures/tables, supplementary material, source code available on GitHu

    Magnitude and Durability of the Antibody Response to mRNA-Based Vaccination Among SARS-CoV-2 Seronegative and Seropositive Health Care Personnel

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    Few studies have described changes in SARS-CoV-2 antibody levels in response to infection and vaccination at frequent intervals and over extended follow-up periods. The purpose of this study was to assess changes in SARS-CoV-2–specific antibody responses among a prospective cohort of health care personnel over 18 months with up to 22 samples per person. Antibody levels and live virus neutralization were measured before and after mRNA-based vaccination with results stratified by (1) SARS-CoV-2 infection status prior to initial vaccination and (2) SARS-CoV-2 infection at any point during follow-up. We found that the antibody response to the first dose was almost 2-fold higher in individuals who were seropositive prior to vaccination, although neutralization titers were more variable. The antibody response induced by vaccination appeared to wane over time but generally persisted for 8 to 9 months, and those who were infected at any point during the study had slightly higher antibody levels over time vs those who remained uninfected. These findings underscore the need to account for SARS-CoV-2 natural infection as a modifier of vaccine responses, and they highlight the importance of frequent testing of longitudinal antibody titers over time. Together, our results provide a clearer understanding of the trajectories of antibody response among vaccinated individuals with and without prior SARS-CoV-2 infection
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