Concert recording 2016-02-28

[Track 01]. Bagatellen. Elegie ; [Track 02]. Scherzo ; [Track 03]. Aria ; [Track 04]. Gigue / Erwin Dressel -- [Track 05]. Sonata. Allegro, ma non troppo ; [Track 06]. Sarabande ; Allegro / Wolfgang Jacobi -- [Track 07]. Flirtations. Sweet nothings ; [Track 08]. These soft shoes ; [Track 09]. Showtune / Michael Markowski -- [Track 10]. Sonata. Allegro ; [Track 11]. Andantino cantabile ; [Track 12]. Allegro vivace / Lawson Lunde

Emotional arousal in agenesis of the corpus callosum

While the processing of verbal and psychophysiological indices of emotional arousal have been investigated extensively in relation to the left and right cerebral hemispheres, it remains poorly understood how both hemispheres normally function together to generate emotional responses to stimuli. Drawing on a unique sample of nine high-functioning subjects with complete agenesis of the corpus callosum (AgCC), we investigated this issue using standardized emotional visual stimuli. Compared to healthy controls, subjects with AgCC showed a larger variance in their cognitive ratings of valence and arousal, and an insensitivity to the emotion category of the stimuli, especially for negatively-valenced stimuli, and especially for their arousal. Despite their impaired cognitive ratings of arousal, some subjects with AgCC showed large skin-conductance responses, and in general skin-conductance responses discriminated emotion categories and correlated with stimulus arousal ratings. We suggest that largely intact right hemisphere mechanisms can support psychophysiological emotional responses, but that the lack of interhemispheric communication between the hemispheres, perhaps together with dysfunction of the anterior cingulate cortex, interferes with normal verbal ratings of arousal, a mechanism in line with some models of alexithymia

Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas.

Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone and develop along previously healthy brain networks. Here, we evaluated these hypotheses by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers and large-scale connectivity networks. By applying independent component analysis to lesion data from 242 adult patients with high- and low-grade glioma, we identified three lesion covariance networks, which reflect clusters of frequent glioma localization. Replicability of the lesion covariance networks was assessed in an independent sample of 168 glioma patients. We related the lesion covariance networks to important clinical variables, including tumour grade and patient survival, as well as genomic information such as molecular genetic subtype and bulk transcriptomic profiles. Finally, we systematically cross-correlated the lesion covariance networks with structural and functional connectivity networks derived from neuroimaging data of over 4000 healthy UK BioBank participants to uncover intrinsic brain networks that may that underlie tumour development. The three lesion covariance networks overlapped with the anterior, posterior and inferior horns of the lateral ventricles respectively, extending into the frontal, parietal and temporal cortices. These locations were independently replicated. The first lesion covariance network, which overlapped with the anterior horn, was associated with low-grade, isocitrate dehydrogenase -mutated/1p19q-codeleted tumours, as well as a neural transcriptomic signature and improved overall survival. Each lesion covariance network significantly coincided with multiple structural and functional connectivity networks, with the first bearing an especially strong relationship with brain connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each lesion covariance network. In conclusion, we demonstrated replicable patterns of glioma localization with clinical relevance and spatial correspondence with large-scale functional and structural connectivity networks. These results are consistent with prior reports of glioma growth along white matter pathways, as well as evidence for the coordination of glioma stem cell proliferation by neuronal activity. Our findings describe how the locations of gliomas relate to their proposed subventricular origins, suggesting a model wherein periventricular brain connectivity guides tumour development

Lesion covariance networks reveal proposed origins and pathways of diffuse gliomas.

Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone and develop along previously healthy brain networks. Here, we evaluated these hypotheses by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers and large-scale connectivity networks. By applying independent component analysis to lesion data from 242 adult patients with high- and low-grade glioma, we identified three lesion covariance networks, which reflect clusters of frequent glioma localization. Replicability of the lesion covariance networks was assessed in an independent sample of 168 glioma patients. We related the lesion covariance networks to important clinical variables, including tumour grade and patient survival, as well as genomic information such as molecular genetic subtype and bulk transcriptomic profiles. Finally, we systematically cross-correlated the lesion covariance networks with structural and functional connectivity networks derived from neuroimaging data of over 4000 healthy UK BioBank participants to uncover intrinsic brain networks that may that underlie tumour development. The three lesion covariance networks overlapped with the anterior, posterior and inferior horns of the lateral ventricles respectively, extending into the frontal, parietal and temporal cortices. These locations were independently replicated. The first lesion covariance network, which overlapped with the anterior horn, was associated with low-grade, isocitrate dehydrogenase -mutated/1p19q-codeleted tumours, as well as a neural transcriptomic signature and improved overall survival. Each lesion covariance network significantly coincided with multiple structural and functional connectivity networks, with the first bearing an especially strong relationship with brain connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each lesion covariance network. In conclusion, we demonstrated replicable patterns of glioma localization with clinical relevance and spatial correspondence with large-scale functional and structural connectivity networks. These results are consistent with prior reports of glioma growth along white matter pathways, as well as evidence for the coordination of glioma stem cell proliferation by neuronal activity. Our findings describe how the locations of gliomas relate to their proposed subventricular origins, suggesting a model wherein periventricular brain connectivity guides tumour development

Relative commutants of strongly self-absorbing C*-algebras

The relative commutant $A'\cap A^{\mathcal{U}}$ of a strongly self-absorbing algebra $A$ is indistinguishable from its ultrapower $A^{\mathcal{U}}$. This applies both to the case when $A$ is the hyperfinite II$_1$ factor and to the case when it is a strongly self-absorbing C*-algebra. In the latter case we prove analogous results for $\ell_\infty(A)/c_0(A)$ and reduced powers corresponding to other filters on $\bf N$. Examples of algebras with approximately inner flip and approximately inner half-flip are provided, showing the optimality of our results. We also prove that strongly self-absorbing algebras are smoothly classifiable, unlike the algebras with approximately inner half-flip.Comment: Some minor correction

Testing the potential of Twitter mining methods for data acquisition: Evaluating novel opportunities for ecological research in multiple taxa

Social media provides unique opportunities for data collection. Retrospective analysis of social media posts has been used in seismology, political science and public risk perception studies but has not been used extensively in ecological research. There is currently no assessment of whether such data are valid and robust in ecological contexts. We used “Twitter mining” methods to search Twitter (a microblogging site) for terms relevant to three nationwide UK ecological phenomena: winged ant emergence; autumnal house spider sightings; and starling murmurations. To determine the extent to which Twitter‐mined data were reliable and suitable for answering specific ecological questions the data so gathered were analysed and the results directly compared to the findings of three published studies based on primary data collected by citizen scientists during the same time period. Twitter‐mined data proved robust for quantifying temporal ecological patterns. There was striking similarity in the temporal patterns of winged ant emergence between previously published work and our analysis of Twitter‐mined data at national scales; this was also the case for house spider sightings. Spatial data were less available but analysis of Twitter‐mined data was able to replicate most spatial findings from all three studies. Baseline ecological findings, such as the sex ratio of house spider sightings, could also be replicated. Where Twitter mining was less successful was answering specific questions and testing hypotheses. Thus, we were unable to determine the influence of microhabitat on winged ants or test predation and weather hypotheses for initiation of murmuration behaviour. Twitter mining clearly has great potential to generate spatiotemporal ecological data and to answer specific ecological questions. However, we found that the types and usefulness of data differed substantially between the three phenomena. Consequently, we suggest that understanding users' behaviour when posting on ecological topics would be useful if using social media is to generate ecological data

Decreased function of survival motor neuron protein impairs endocytic pathways

This document is the Accepted Manuscript version. The final, definitive version is available online at https://doi.org/10.1073/pnas.1600015113.Spinal muscular atrophy (SMA) is caused by depletion of the ubiquitously expressed survival motor neuron (SMN) protein, with 1 in 40 Caucasians being heterozygous for a disease allele. SMN is critical for the assembly of numerous ribonucleoprotein complexes, yet it is still unclear how reduced SMN levels affect motor neuron function. Here, we examined the impact of SMN depletion in Caenorhabditis elegans and found that decreased function of the SMN ortholog SMN-1 perturbed endocytic pathways at motor neuron synapses and in other tissues. Diminished SMN-1 levels caused defects in C. elegans neuromuscular function, and smn-1 genetic interactions were consistent with an endocytic defect. Changes were observed in synaptic endocytic proteins when SMN-1 levels decreased. At the ultrastructural level, defects were observed in endosomal compartments, including significantly fewer docked synaptic vesicles. Finally, endocytosis-dependent infection by JC polyomavirus (JCPyV) was reduced in human cells with decreased SMN levels. Collectively, these results demonstrate for the first time, to our knowledge, that SMN depletion causes defects in endosomal trafficking that impair synaptic function, even in the absence of motor neuron cell death.Peer reviewedFinal Accepted Versio

Combinatorial CRISPR-Cas9 screens for de novo mapping of genetic interactions.

We developed a systematic approach to map human genetic networks by combinatorial CRISPR-Cas9 perturbations coupled to robust analysis of growth kinetics. We targeted all pairs of 73 cancer genes with dual guide RNAs in three cell lines, comprising 141,912 tests of interaction. Numerous therapeutically relevant interactions were identified, and these patterns replicated with combinatorial drugs at 75% precision. From these results, we anticipate that cellular context will be critical to synthetic-lethal therapies

A time study of physicians' work in a German university eye hospital to estimate unit costs.

BACKGROUND: Technical efficiency of hospital services is debated since performance has been heterogeneous. Staff time represents the main resource in patient care and its inappropriate allocation has been identified as a key factor of inefficiency. The aim of this study was to analyse the utilisation of physicians' work time stratified by staff groups, tasks and places of work. A further aim was to use these data to estimate resource use per unit of output. METHODS: A self-reporting work-sampling study was carried during 14-days at a University Eye Hospital. Staff costs of physicians per unit of output were calculated at the wards, the operating rooms and the outpatient unit. RESULTS: Forty per cent of total work time was spent in contact with the patient. Thirty per cent was spent with documentation tasks. Time spent with documentation tasks declined monotonically with increasing seniority of staff. Unit costs were 56 € per patient day at the wards, 77 € and 20 € per intervention at the operating rooms for inpatients and outpatients, respectively, and 33 € per contact at the outpatient unit. Substantial differences in resources directly dedicated to the patient were found between these locations. CONCLUSION: The presented data provide unprecedented units costs in inpatient Ophthalmology. Future research should focus on analysing factors that influence differences in time allocation, such as types of patients, organisation of care processes and composition of staff

Deglacierization of a marginal basin and implications for outburst floods

This article was submitted to Cryospheric Sciences, a section of the journal Frontiers in Earth ScienceSuicide Basin is a partly glacierized marginal basin of Mendenhall Glacier, Alaska, that has released glacier lake outburst floods (GLOFs) annually since 2011. The floods cause inundation and erosion in the Mendenhall Valley, impacting homes and other infrastructure. Here, we utilize in-situ and remote sensing data to assess the recent evolution and current state of Suicide Basin. We focus on the 2018 and 2019 melt seasons, during which we collected most of our data, partly using unmanned aerial vehicles (UAVs). To provide longer-term context, we analyze DEMs collected since 2006 and model glacier surface mass balance over the 2006–2019 period. During the 2018 and 2019 outburst flood events, Suicide Basin released ∼ 30 Å~ 106 m3 of water within approximately 4–5 days. Since lake drainage was partial in both years, these ∼ 30 Å~ 106 m3 represent only a fraction (∼ 60%) of the basin’s total storage capacity. In contrast to previous years, subglacial drainage was preceded by supraglacial outflow over the ice dam, which lasted ∼ 1 day in 2018 and 6 days in 2019. Two large calving events occurred in 2018 and 2019, with submerged ice breaking off the main glacier during lake filling, thereby increasing the basin’s storage capacity. In 2018, the floating ice in the basin was 36 m thick on average. In 2019, ice thickness was 29 m, suggesting rapid decay of the ice tongue despite increasing ice inflow from Mendenhall Glacier. The ice dam at the basin entrance thinned by more than 5 m a–1 from 2018 to 2019, which is approximately double the rate of the reference period 2006–2018. While ice-dam thinning reduces water storage capacity in the basin, that capacity is increased by declining ice volume in the basin and longitudinal lake expansion, with the latter process challenging to predict. The potential for premature drainage onset (i.e., drainage before the lake’s storage capacity is reached), intermittent drainage decelerations, and early drainage termination further complicates prediction of future GLOF events.This work was funded by the Alaska Climate Adaptation Science Center (AK CASC). UAVs and other surveying equipment were partly funded through the U.S. National Science Foundation (NSF) award EAR-1921598. EH and SH were partially supported by the NSF award OIA-1753748 and the State of Alaska. Streamflow monitoring of the Mendenhall River and real-time imagery of Suicide Basin were funded by the U.S. Geological Survey Groundwater and Streamflow Information Program. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Ye