2,064 research outputs found

    Economical and scalable synthesis of 6-amino-2-cyanobenzothiazole

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    2-Cyanobenzothiazoles (CBTs) are useful building blocks for: 1) luciferin derivatives for bioluminescent imaging; and 2) handles for bioorthogonal ligations. A particularly versatile CBT is 6-amino-2-cyanobenzothiazole (ACBT), which has an amine handle for straight-forward derivatisation. Here we present an economical and scalable synthesis of ACBT based on a cyanation catalysed by 1,4-diazabicyclo[2.2.2]octane (DABCO), and discuss its advantages for scale-up over previously reported routes

    Chronic white matter lesion activity predicts clinical progression in primary progressive multiple sclerosis

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    Chronic active and slowly expanding lesions with smouldering inflammation are neuropathological correlates of progressive multiple sclerosis pathology. T1 hypointense volume and signal intensity on T1-weighted MRI reflect brain tissue damage that may develop within newly formed acute focal inflammatory lesions or in chronic pre-existing lesions without signs of acute inflammation. Using a recently developed method to identify slowly expanding/evolving lesions in vivo from longitudinal conventional T2- and T1-weighted brain MRI scans, we measured the relative amount of chronic lesion activity as measured by change in T1 volume and intensity within slowly expanding/evolving lesions and non-slowly expanding/evolving lesion areas of baseline pre-existing T2 lesions, and assessed the effect of ocrelizumab on this outcome in patients with primary progressive multiple sclerosis participating in the phase III, randomized, placebo-controlled, double-blind ORATORIO study (n = 732, NCT01194570). We also assessed the predictive value of T1-weighted measures of chronic lesion activity for clinical multiple sclerosis progression as reflected by a composite disability measure including the Expanded Disability Status Scale, Timed 25-Foot Walk and 9-Hole Peg Test. We observed in this clinical trial population that most of total brain non-enhancing T1 hypointense lesion volume accumulation was derived from chronic lesion activity within pre-existing T2 lesions rather than new T2 lesion formation. There was a larger decrease in mean normalized T1 signal intensity and greater relative accumulation of T1 hypointense volume in slowly expanding/evolving lesions compared with non-slowly expanding/evolving lesions. Chronic white matter lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in slowly expanding/evolving lesions and in non-slowly expanding/evolving lesion areas of pre-existing lesions predicted subsequent composite disability progression with consistent trends on all components of the composite. In contrast, whole brain volume loss and acute lesion activity measured by longitudinal T1 hypointense lesion volume accumulation in new focal T2 lesions did not predict subsequent composite disability progression in this trial at the population level. Ocrelizumab reduced longitudinal measures of chronic lesion activity such as T1 hypointense lesion volume accumulation and mean normalized T1 signal intensity decrease both within regions of pre-existing T2 lesions identified as slowly expanding/evolving and in non-slowly expanding/evolving lesions. Using conventional brain MRI, T1-weighted intensity-based measures of chronic white matter lesion activity predict clinical progression in primary progressive multiple sclerosis and may qualify as a longitudinal in vivo neuroimaging correlate of smouldering demyelination and axonal loss in chronic active lesions due to CNS-resident inflammation and/or secondary neurodegeneration across the multiple sclerosis disease continuum

    Origin of symbol-using systems: speech, but not sign, without the semantic urge

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    Natural language—spoken and signed—is a multichannel phenomenon, involving facial and body expression, and voice and visual intonation that is often used in the service of a social urge to communicate meaning. Given that iconicity seems easier and less abstract than making arbitrary connections between sound and meaning, iconicity and gesture have often been invoked in the origin of language alongside the urge to convey meaning. To get a fresh perspective, we critically distinguish the origin of a system capable of evolution from the subsequent evolution that system becomes capable of. Human language arose on a substrate of a system already capable of Darwinian evolution; the genetically supported uniquely human ability to learn a language reflects a key contact point between Darwinian evolution and language. Though implemented in brains generated by DNA symbols coding for protein meaning, the second higher-level symbol-using system of language now operates in a world mostly decoupled from Darwinian evolutionary constraints. Examination of Darwinian evolution of vocal learning in other animals suggests that the initial fixation of a key prerequisite to language into the human genome may actually have required initially side-stepping not only iconicity, but the urge to mean itself. If sign languages came later, they would not have faced this constraint

    How does cognitive load influence speech perception? : An encoding hypothesis

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    Two experiments investigated the conditions under which cognitive load exerts an effect on speech perception. These experiments extend earlier research by using a different speech perception task (four-interval oddity task) and by implementing cognitive load through a task often thought to be modular, namely, face processing. In the cognitive-load conditions, participants were required to remember two faces presented before the speech stimuli. In Experiment 1, performance in the speech-perception task under cognitive load was not impaired in comparison to a no-load baseline condition. In Experiment 2, we modified the load condition minimally such that it required encoding of the two faces simultaneously with the speech stimuli. As a reference condition, we also used a visual search task that in earlier experiments had led to poorer speech perception. Both concurrent tasks led to decrements in the speech task. The results suggest that speech perception is affected even by loads thought to be processed modularly, and that, critically, encoding in working memory might be the locus of interference

    Pyrene tags for the detection of carbohydrates by label‐assisted laser desorption/ionisation mass spectrometry

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    Matrix‐assisted laser desorption/ionisation mass spectrometry (MALDI‐MS) is widely used for the analysis of biomolecules. Label‐assisted laser desorption/ionisation mass spectrometry (LALDI‐MS) is a matrix‐free variant of MALDI‐MS, in which only analytes covalently attached to a laser desorption/ionisation (LDI) enhancer are detected. LALDI‐MS has shown promise in overcoming the limitations of MALDI‐MS in terms of sample preparation and MS analysis. In this work, we have developed a series of pyrene‐based LDI reagents (LALDI tags) that can be used for labelling and LALDI‐MS analysis of reducing carbohydrates from complex (biological) samples without the need for additional chemical derivatisation or purification. We have systematically explored the suitability of four pyrene‐based LDI enhancers and three aldehyde‐reactive handles, optimised sample preparation, and demonstrated the use of LALDI tags for the detection of lactose. We have also exemplified the potential of LALDI tags for labelling carbohydrates in biological samples by direct detection of lactose in cow's milk. These results demonstrate that LALDI‐MS is a promising technique for the analysis of reducing carbohydrates in biological samples, and pave the way for the development of LALDI‐MS for glycomics and diagnostics

    Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

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    Background: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. Methods: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. Results: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/ signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). Conclusions: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics
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