A posterior epidural mass causing paraparesis in a 20-year-old healthy individual

We present a case of a posterior epidural abscess at the thoracic vertebral level causing paraparesia in a young, healthy individual with no otherwise predisposing factors, with normal laboratory findings, as diagnosed using fat-suppressed MR imaging. Spinal epidural abscess is a rare condition, encountered mostly in the midthoracic or lower lumbar vertebral levels of elderly patients, that has a high mortality and morbidity (18-31%) when diagnosis and treatment is delayed. It is rarely spontaneous and is usually accompanied by spinal osteomyelitis. Diagnosis is rather easy in cases of vertebral osteomyelitis or when classical clinical, laboratory and imaging findings are present. However, cases of spontaneous development, with no predisposing factors, and lack of abscess suggesting clinical and laboratory findings may be a diagnostic challenge. In such cases, other posterior epidural masses such as schwannoma, neurofibroma, meningioma and hematoma should be considered in the differential diagnosis. Both the clinician and the radiology physician should have a high suspicion of epidural abscesses, because their early diagnosis and treatment is important. In addition to routine MR images, fat-suppressed MR images prove helpful in the diagnosis of spontaneous epidural abscesses by showing the inflammatory changes in the paraspinal area

Neural Decision Boundaries for Maximal Information Transmission

We consider here how to separate multidimensional signals into two categories, such that the binary decision transmits the maximum possible information transmitted about those signals. Our motivation comes from the nervous system, where neurons process multidimensional signals into a binary sequence of responses (spikes). In a small noise limit, we derive a general equation for the decision boundary that locally relates its curvature to the probability distribution of inputs. We show that for Gaussian inputs the optimal boundaries are planar, but for non-Gaussian inputs the curvature is nonzero. As an example, we consider exponentially distributed inputs, which are known to approximate a variety of signals from natural environment.Comment: 5 pages, 3 figure

Hematological Changes as Prognostic Indicators of Survival: Similarities Between Gottingen Minipigs, Humans, and Other Large Animal Models

The animal efficacy rule addressing development of drugs for selected disease categories has pointed out the need to develop alternative large animal models. Based on this rule, the pathophysiology of the disease in the animal model must be well characterized and must reflect that in humans. So far, manifestations of the acute radiation syndrome (ARS) have been extensively studied only in two large animal models, the non-human primate (NHP) and the canine. We are evaluating the suitability of the minipig as an additional large animal model for development of radiation countermeasures. We have previously shown that the Gottingen minipig manifests hematopoietic ARS phases and symptoms similar to those observed in canines, NHPs, and humans.We establish here the LD50/30 dose (radiation dose at which 50% of the animals succumb within 30 days), and show that at this dose the time of nadir and the duration of cytopenia resemble those observed for NHP and canines, and mimic closely the kinetics of blood cell depletion and recovery in human patients with reversible hematopoietic damage (H3 category, METREPOL approach). No signs of GI damage in terms of diarrhea or shortening of villi were observed at doses up to 1.9 Gy. Platelet counts at days 10 and 14, number of days to reach critical platelet values, duration of thrombocytopenia, neutrophil stress response at 3 hours and count at 14 days, and CRP-to-platelet ratio were correlated with survival. The ratios between neutrophils, lymphocytes and platelets were significantly correlated with exposure to irradiation at different time intervals.As a non-rodent animal model, the minipig offers a useful alternative to NHP and canines, with attractive features including ARS resembling human ARS, cost, and regulatory acceptability. Use of the minipig may allow accelerated development of radiation countermeasures

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Reading comprehension in autism spectrum disorders: The role of oral language and social functioning

Reading comprehension is an area of difficulty for many individuals with autism spectrum disorders (ASD). According to the Simple View of Reading, word recognition and oral language are both important determinants of reading comprehension ability. We provide a novel test of this model in 100 adolescents with ASD of varying intellectual ability. Further, we explore whether reading comprehension is additionally influenced by individual differences in social behaviour and social cognition in ASD. Adolescents with ASD aged 14-16 years completed assessments indexing word recognition, oral language, reading comprehension, social behaviour and social cognition. Regression analyses show that both word recognition and oral language explain unique variance in reading comprehension. Further, measures of social behaviour and social cognition predict reading comprehension after controlling for the variance explained by word recognition and oral language. This indicates that word recognition, oral language and social impairments may constrain reading comprehension in ASD

The association between delusional-like experiences, and tobacco, alcohol or cannabis use: a nationwide population-based survey

<p>Abstract</p> <p>Background</p> <p>Previous population-based studies have found that delusional-like experiences (DLE) are prevalent in the community, and are associated with a wide range of mental health disorders including substance use. The aim of the study was to explore the association between DLE and three commonly used substances - tobacco, alcohol and cannabis.</p> <p>Methods</p> <p>Subjects were drawn from the Australian National Survey of Mental Health and Wellbeing 2007. The Composite International Diagnostic Interview was used to identify DLE, common psychiatric disorders, and substance use. We examined the relationship between the variables of interest using logistic regression, adjusting for potential confounding factors.</p> <p>Results</p> <p>Of 8 773 participants, 8.4% (n = 776) subjects endorsed one or more DLE. With respect to tobacco use, compared to nonusers, DLE were more common in those who (a) had daily use, (b) commenced usage aged 15 years or less, and (c) those who smoked heavily (23 or more cigarettes per day). Participants with cannabis use disorders were more likely to endorse DLE; this association was most prominent in those with an onset of 16 years or younger. In contrast, the pattern of association between DLE versus alcohol use or dependence was less consistent, however those with early onset alcohol use disorders were more likely to endorse DLE probe items.</p> <p>Conclusions</p> <p>While cannabis use disorders have been previously linked with DLE, our findings linking alcohol and tobacco use and DLE suggest that the influence of these substances on psychosis-related outcomes warrants closer scrutiny in longitudinal prospective studies.</p

Second Order Dimensionality Reduction Using Minimum and Maximum Mutual Information Models

Conventional methods used to characterize multidimensional neural feature selectivity, such as spike-triggered covariance (STC) or maximally informative dimensions (MID), are limited to Gaussian stimuli or are only able to identify a small number of features due to the curse of dimensionality. To overcome these issues, we propose two new dimensionality reduction methods that use minimum and maximum information models. These methods are information theoretic extensions of STC that can be used with non-Gaussian stimulus distributions to find relevant linear subspaces of arbitrary dimensionality. We compare these new methods to the conventional methods in two ways: with biologically-inspired simulated neurons responding to natural images and with recordings from macaque retinal and thalamic cells responding to naturalistic time-varying stimuli. With non-Gaussian stimuli, the minimum and maximum information methods significantly outperform STC in all cases, whereas MID performs best in the regime of low dimensional feature spaces

Machines vs. Ensembles: Effective MAPK Signaling through Heterogeneous Sets of Protein Complexes

A grant from the One-University Open Access Fund at the University of Kansas was used to defray the author’s publication fees in this Open Access journal. The Open Access Fund, administered by librarians from the KU, KU Law, and KUMC libraries, is made possible by contributions from the offices of KU Provost, KU Vice Chancellor for Research & Graduate Studies, and KUMC Vice Chancellor for Research. For more information about the Open Access Fund, please see http://library.kumc.edu/authors-fund.xml.Despite the importance of intracellular signaling networks, there is currently no consensus regarding the fundamental nature of the protein complexes such networks employ. One prominent view involves stable signaling machines with well-defined quaternary structures. The combinatorial complexity of signaling networks has led to an opposing perspective, namely that signaling proceeds via heterogeneous pleiomorphic ensembles of transient complexes. Since many hypotheses regarding network function rely on how we conceptualize signaling complexes, resolving this issue is a central problem in systems biology. Unfortunately, direct experimental characterization of these complexes has proven technologically difficult, while combinatorial complexity has prevented traditional modeling methods from approaching this question. Here we employ rule-based modeling, a technique that overcomes these limitations, to construct a model of the yeast pheromone signaling network. We found that this model exhibits significant ensemble character while generating reliable responses that match experimental observations. To contrast the ensemble behavior, we constructed a model that employs hierarchical assembly pathways to produce scaffold-based signaling machines. We found that this machine model could not replicate the experimentally observed combinatorial inhibition that arises when the scaffold is overexpressed. This finding provides evidence against the hierarchical assembly of machines in the pheromone signaling network and suggests that machines and ensembles may serve distinct purposes in vivo. In some cases, e.g. core enzymatic activities like protein synthesis and degradation, machines assembled via hierarchical energy landscapes may provide functional stability for the cell. In other cases, such as signaling, ensembles may represent a form of weak linkage, facilitating variation and plasticity in network evolution. The capacity of ensembles to signal effectively will ultimately shape how we conceptualize the function, evolution and engineering of signaling networks