6,026 research outputs found
Intense physical activity is associated with cognitive performance in the elderly
Numerous studies have reported positive impacts of physical activity on cognitive function. However, the majority of these studies have utilised physical activity questionnaires or surveys, thus results may have been influenced by reporting biases. Through the objective measurement of routine levels of physical activity via actigraphy, we report a significant association between intensity, but not volume, of physical activity and cognitive functioning. A cohort of 217 participants (aged 60–89 years) wore an actigraphy unit for 7 consecutive days and underwent comprehensive neuropsychological assessment. The cohort was stratified into tertiles based on physical activity intensity. Compared with individuals in the lowest tertile of physical activity intensity, those in the highest tertile scored 9%, 9%, 6% and 21% higher on the digit span, digit symbol, Rey Complex Figure Test (RCFT) copy and Rey Figure Test 30-min recall test, respectively. Statistically, participants in the highest tertile of physical activity intensity performed significantly better on the following cognitive tasks: digit symbol, RCFT copy and verbal fluency test (all P<0.05). The results indicate that intensity rather than quantity of physical activity may be more important in the association between physical activity and cognitive function
Reliability and correlation analysis of computed methods to convert conventional 2D radiological hindfoot measurements to a 3D setting using weightbearing CT
Enhanced insulin sensitivity associated with provision of mono and polyunsaturated fatty acids in skeletal muscle cells involves counter modulation of PP2A
International audienceAims/Hypothesis: Reduced skeletal muscle insulin sensitivity is a feature associated with sustained exposure to excess saturated fatty acids (SFA), whereas mono and polyunsaturated fatty acids (MUFA and PUFA) not only improve insulin sensitivity but blunt SFA-induced insulin resistance. The mechanisms by which MUFAs and PUFAs institute these favourable changes remain unclear, but may involve stimulating insulin signalling by counter-modulation/repression of protein phosphatase 2A (PP2A). This study investigated the effects of oleic acid (OA; a MUFA), linoleic acid (LOA; a PUFA) and palmitate (PA; a SFA) in cultured myotubes and determined whether changes in insulin signalling can be attributed to PP2A regulation. Principal Findings: We treated cultured skeletal myotubes with unsaturated and saturated fatty acids and evaluated insulin signalling, phosphorylation and methylation status of the catalytic subunit of PP2A. Unlike PA, sustained incubation of rat or human myotubes with OA or LOA significantly enhanced Akt-and ERK1/2-directed insulin signalling. This was not due to heightened upstream IRS1 or PI3K signalling nor to changes in expression of proteins involved in proximal insulin signalling, but was associated with reduced dephosphorylation/inactivation of Akt and ERK1/2. Consistent with this, PA reduced PP2Ac demethylation and tyrosine 307 phosphorylation-events associated with PP2A activation. In contrast, OA and LOA strongly opposed these PA-induced changes in PP2Ac thus exerting a repressive effect on PP2A.Conclusions/Interpretation: Beneficial gains in insulin sensitivity and the ability of unsaturated fatty acids to oppose palmitate-induced insulin resistance in muscle cells may partly be accounted for by counter-modulation of PP2A
Observation and Characterization of a Cosmic Muon Neutrino Flux from the Northern Hemisphere using six years of IceCube data
The IceCube Collaboration has previously discovered a high-energy
astrophysical neutrino flux using neutrino events with interaction vertices
contained within the instrumented volume of the IceCube detector. We present a
complementary measurement using charged current muon neutrino events where the
interaction vertex can be outside this volume. As a consequence of the large
muon range the effective area is significantly larger but the field of view is
restricted to the Northern Hemisphere. IceCube data from 2009 through 2015 have
been analyzed using a likelihood approach based on the reconstructed muon
energy and zenith angle. At the highest neutrino energies between 191 TeV and
8.3 PeV a significant astrophysical contribution is observed, excluding a
purely atmospheric origin of these events at significance. The
data are well described by an isotropic, unbroken power law flux with a
normalization at 100 TeV neutrino energy of
and a hard spectral index of . The observed spectrum is
harder in comparison to previous IceCube analyses with lower energy thresholds
which may indicate a break in the astrophysical neutrino spectrum of unknown
origin. The highest energy event observed has a reconstructed muon energy of
which implies a probability of less than 0.005% for
this event to be of atmospheric origin. Analyzing the arrival directions of all
events with reconstructed muon energies above 200 TeV no correlation with known
-ray sources was found. Using the high statistics of atmospheric
neutrinos we report the currently best constraints on a prompt atmospheric muon
neutrino flux originating from charmed meson decays which is below in
units of the flux normalization of the model in Enberg et al. (2008).Comment: 20 pages, 21 figure
All-sky search for time-integrated neutrino emission from astrophysical sources with 7 years of IceCube data
Since the recent detection of an astrophysical flux of high energy neutrinos,
the question of its origin has not yet fully been answered. Much of what is
known about this flux comes from a small event sample of high neutrino purity,
good energy resolution, but large angular uncertainties. In searches for
point-like sources, on the other hand, the best performance is given by using
large statistics and good angular reconstructions. Track-like muon events
produced in neutrino interactions satisfy these requirements. We present here
the results of searches for point-like sources with neutrinos using data
acquired by the IceCube detector over seven years from 2008--2015. The
discovery potential of the analysis in the northern sky is now significantly
below , on average
lower than the sensitivity of the previously published analysis of four
years exposure. No significant clustering of neutrinos above background
expectation was observed, and implications for prominent neutrino source
candidates are discussed.Comment: 19 pages, 17 figures, 3 tables; ; submitted to The Astrophysical
Journa
The IceCube Neutrino Observatory: Instrumentation and Online Systems
The IceCube Neutrino Observatory is a cubic-kilometer-scale high-energy
neutrino detector built into the ice at the South Pole. Construction of
IceCube, the largest neutrino detector built to date, was completed in 2011 and
enabled the discovery of high-energy astrophysical neutrinos. We describe here
the design, production, and calibration of the IceCube digital optical module
(DOM), the cable systems, computing hardware, and our methodology for drilling
and deployment. We also describe the online triggering and data filtering
systems that select candidate neutrino and cosmic ray events for analysis. Due
to a rigorous pre-deployment protocol, 98.4% of the DOMs in the deep ice are
operating and collecting data. IceCube routinely achieves a detector uptime of
99% by emphasizing software stability and monitoring. Detector operations have
been stable since construction was completed, and the detector is expected to
operate at least until the end of the next decade.Comment: 83 pages, 50 figures; updated with minor changes from journal review
and proofin
Exponential Random Graph Modeling for Complex Brain Networks
Exponential random graph models (ERGMs), also known as p* models, have been
utilized extensively in the social science literature to study complex networks
and how their global structure depends on underlying structural components.
However, the literature on their use in biological networks (especially brain
networks) has remained sparse. Descriptive models based on a specific feature
of the graph (clustering coefficient, degree distribution, etc.) have dominated
connectivity research in neuroscience. Corresponding generative models have
been developed to reproduce one of these features. However, the complexity
inherent in whole-brain network data necessitates the development and use of
tools that allow the systematic exploration of several features simultaneously
and how they interact to form the global network architecture. ERGMs provide a
statistically principled approach to the assessment of how a set of interacting
local brain network features gives rise to the global structure. We illustrate
the utility of ERGMs for modeling, analyzing, and simulating complex
whole-brain networks with network data from normal subjects. We also provide a
foundation for the selection of important local features through the
implementation and assessment of three selection approaches: a traditional
p-value based backward selection approach, an information criterion approach
(AIC), and a graphical goodness of fit (GOF) approach. The graphical GOF
approach serves as the best method given the scientific interest in being able
to capture and reproduce the structure of fitted brain networks
Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector
A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13 TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV
Measurement of the cross-section and charge asymmetry of bosons produced in proton-proton collisions at TeV with the ATLAS detector
This paper presents measurements of the and cross-sections and the associated charge asymmetry as a
function of the absolute pseudorapidity of the decay muon. The data were
collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with
the ATLAS experiment at the LHC and correspond to a total integrated luminosity
of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements
varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the
1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured
with an uncertainty between 0.002 and 0.003. The results are compared with
predictions based on next-to-next-to-leading-order calculations with various
parton distribution functions and have the sensitivity to discriminate between
them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables,
submitted to EPJC. All figures including auxiliary figures are available at
https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13
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