Distinctive phosphoinositide- and Ca²⁺-binding properties of normal and cognitive performance–linked variant forms of KIBRA C2 domain

Kidney- and brain-expressed protein (KIBRA), a multifunctional scaffold protein with around 20 known binding partners, is involved in memory and cognition, organ size control via the Hippo pathway, cell polarity, and membrane trafficking. KIBRA includes tandem N-terminal WW domains, a C2 domain, and motifs for binding atypical PKC and PDZ domains. A naturally occurring human KIBRA variant involving residue changes at positions 734 (Met-to-Ile) and 735 (Ser-to-Ala) within the C2 domain affects cognitive performance. We have elucidated 3D structures and calcium- and phosphoinositide-binding properties of human KIBRA C2 domain. Both WT and variant C2 adopt a canonical type I topology C2 domain fold. Neither Ca²⁺ nor any other metal ion was bound to WT or variant KIBRA C2 in crystal structures, and Ca²⁺ titration produced no significant reproducible changes in NMR spectra. NMR and X-ray diffraction data indicate that KIBRA C2 binds phosphoinositides via an atypical site involving β-strands 5, 2, 1, and 8. Molecular dynamics simulations indicate that KIBRA C2 interacts with membranes via primary and secondary sites on the same domain face as the experimentally identified phosphoinositide-binding site. Our results indicate that KIBRA C2 domain association with membranes is calcium-independent and involves distinctive C2 domain–membrane relative orientations.

The MINERν\nuA Data Acquisition System and Infrastructure

MINER$\nu$A (Main INjector ExpeRiment $\nu$-A) is a new few-GeV neutrino cross section experiment that began taking data in the FNAL NuMI (Fermi National Accelerator Laboratory Neutrinos at the Main Injector) beam-line in March of 2010. MINER$\nu$A employs a fine-grained scintillator detector capable of complete kinematic characterization of neutrino interactions. This paper describes the MINER$\nu$A data acquisition system (DAQ) including the read-out electronics, software, and computing architecture.Comment: 34 pages, 16 figure

Search for associated Higgs boson production using like charge dilepton events in p(p)over-bar collisions at root s=1.96 TeV

We present a search for associated Higgs boson production in the process p (p) over bar -> W/ZH -> l(+/-)l'(+/-) + X in ee, e mu, and mu mu final states. The search is based on data collected by the D0 experiment at the Fermilab Tevatron Collider at root s = 1.96 TeV corresponding to 5.3 fb(-1) of integrated luminosity. We require two isolated leptons (electrons or muons) with the same electric charge and additional kinematic requirements. No significant excess above background is observed, and we set 95% C. L. observed (expected) upper limits on ratio of the production cross section to the standard model prediction of 6.4 (7.3) for a Higgs boson mass of 165 GeV and 13.5 (19.8) for a mass of 115 GeV

Alexithymia, emotion processing and social anxiety in adults with ADHD

<p>Abstract</p> <p>Objective</p> <p>Given sparse research on the issue, this study sought to shed light upon the interactions of alexithymia, emotion processing, and social anxiety in adults with attention-deficit hyperactivity disorder (ADHD).</p> <p>Subjects and methods</p> <p>73 German adults with ADHD according to DSM-IV diagnostic criteria participated. We used the Toronto Alexithymia Scale (TAS-20) to assess alexithymia, the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) to assess different features of social anxiety, and we applied the German 'Experience of Emotions Scale' (SEE) to measure emotion processing.</p> <p>Results</p> <p>40% of the sample were found to meet the DSM-IV criteria of social anxiety disorder, and about 22% were highly alexithymic according to a TAS-20 total score ≥ 61; however, the mean TAS-20 total score of 50.94 ± 9.3 was not much higher than in community samples. Alexithymic traits emerged to be closely linked to emotion processing problems, particularly 'difficulty accepting own emotions', and to social anxiety features.</p> <p>Discussion/conclusion</p> <p>Our findings suggest interactions of alexithymia, emotion processing dysfunction, and social anxiety in adults with ADHD, which may entail the therapeutic implication to thoroughly instruct these patients to identify, accept, communicate, and regulate their emotions to aid reducing interaction anxiety.</p

MINERvA neutrino detector response measured with test beam data

The MINERvA collaboration operated a scaled-down replica of the solid scintillator tracking and sampling calorimeter regions of the MINERvA detector in a hadron test beam at the Fermilab Test Beam Facility. This article reports measurements with samples of protons, pions, and electrons from 0.35 to 2.0 GeV/c momentum. The calorimetric response to protons, pions, and electrons are obtained from these data. A measurement of the parameter in Birks' law and an estimate of the tracking efficiency are extracted from the proton sample. Overall the data are well described by a Geant4-based Monte Carlo simulation of the detector and particle interactions with agreements better than 4%, though some features of the data are not precisely modeled. These measurements are used to tune the MINERvA detector simulation and evaluate systematic uncertainties in support of the MINERvA neutrino cross section measurement program.Comment: as accepted by NIM

Post-translational modification in the archaea: structural characterization of multi-enzyme complex lipoylation

Lipoylation, the covalent attachment of lipoic acid to 2-oxoacid dehydrogenase multi-enzyme complexes, is essential for metabolism in aerobic bacteria and eukarya. In Escherichia coli, lipoylation is catalysed by lipoate protein ligase (LplA) or by lipoic acid synthetase (LipA) and lipoyl(octanoyl) transferase (LipB) combined. Whereas bacterial and eukaryotic LplAs comprise a single, two-domain protein, archaeal LplA function typically involves two proteins, LplA-N and LplA-C. In the thermophilic archaeon Thermoplasma acidophilum, LplA-N and LplA-C are encoded by overlapping genes in inverted orientation (lpla-c is upstream of lpla-n). The structure of Thermoplasma acidophilum LplA-N is known, but the structure of LplA-C and its role in lipoylation are unknown. We have determined the structures of the substrate-free LplA-N+LplA-C complex and the dihydrolipoyl acyltransferase lipoyl domain (E2lipD) that is lipoylated by LplA-N+LplA-C, and carried out biochemical analyses of this archaeal lipoylation system. Our data reveal the following: LplA-C is disordered but folds upon association with LplA-N; LplA-C induces a conformational change in LplA-N involving substantial shortening of a loop that could repress catalytic activity of isolated LplA-N; the adenylate binding region of LplA-N+LplA-C includes two helices rather than the purely loop structure of varying order observed in other LplA structures; LplA-N+LplA-C and E2lipD do not interact in the absence of substrate; LplA-N+LplA-C undergoes a conformational change (the details of which are currently undetermined) during lipoylation; LplA-N+LplA-C can utilize octanoic acid as well as lipoic acid as substrate. The elucidated functional inter-dependence of LplA-N and LplA-C is consistent with their evolutionary co-retention in archaeal genomes.<br/

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal