235 research outputs found

    Reduced emergent character of neural dynamics in patients with a disrupted connectome

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    High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as “Integrated Information Decomposition,” which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems — including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients’ structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence

    Marked isotopic variability within and between the Amazon River and marine dissolved black carbon pools

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    Riverine dissolved organic carbon (DOC) contains charcoal byproducts, termed black carbon (BC). To determine the significance of BC as a sink of atmospheric CO2 and reconcile budgets, the sources and fate of this large, slow-cycling and elusive carbon pool must be constrained. The Amazon River is a significant part of global BC cycling because it exports an order of magnitude more DOC, and thus dissolved BC (DBC), than any other river. We report spatially resolved DBC quantity and radiocarbon (Δ14C) measurements, paired with molecular-level characterization of dissolved organic matter from the Amazon River and tributaries during low discharge. The proportion of BC-like polycyclic aromatic structures decreases downstream, but marked spatial variability in abundance and Δ14C values of DBC molecular markers imply dynamic sources and cycling in a manner that is incongruent with bulk DOC. We estimate a flux from the Amazon River of 1.9–2.7 Tg DBC yr−1 that is composed of predominately young DBC, suggesting that loss processes of modern DBC are important

    Whole-brain modelling identifies distinct but convergent paths to unconsciousness in anaesthesia and disorders of consciousness

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    The human brain entertains rich spatiotemporal dynamics, which are drastically reconfigured when consciousness is lost due to anaesthesia or disorders of consciousness (DOC). Here, we sought to identify the neurobiological mechanisms that explain how transient pharmacological intervention and chronic neuroanatomical injury can lead to common reconfigurations of neural activity. We developed and systematically perturbed a neurobiologically realistic model of whole-brain haemodynamic signals. By incorporating PET data about the cortical distribution of GABA receptors, our computational model reveals a key role of spatially-specific local inhibition for reproducing the functional MRI activity observed during anaesthesia with the GABA-ergic agent propofol. Additionally, incorporating diffusion MRI data obtained from DOC patients reveals that the dynamics that characterise loss of consciousness can also emerge from randomised neuroanatomical connectivity. Our results generalise between anaesthesia and DOC datasets, demonstrating how increased inhibition and connectome perturbation represent distinct neurobiological paths towards the characteristic activity of the unconscious brain

    The dependence of dijet production on photon virtuality in ep collisions at HERA

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    The dependence of dijet production on the virtuality of the exchanged photon, Q^2, has been studied by measuring dijet cross sections in the range 0 < Q^2 < 2000 GeV^2 with the ZEUS detector at HERA using an integrated luminosity of 38.6 pb^-1. Dijet cross sections were measured for jets with transverse energy E_T^jet > 7.5 and 6.5 GeV and pseudorapidities in the photon-proton centre-of-mass frame in the range -3 < eta^jet <0. The variable xg^obs, a measure of the photon momentum entering the hard process, was used to enhance the sensitivity of the measurement to the photon structure. The Q^2 dependence of the ratio of low- to high-xg^obs events was measured. Next-to-leading-order QCD predictions were found to generally underestimate the low-xg^obs contribution relative to that at high xg^obs. Monte Carlo models based on leading-logarithmic parton-showers, using a partonic structure for the photon which falls smoothly with increasing Q^2, provide a qualitative description of the data.Comment: 35 pages, 6 eps figures, submitted to Eur.Phys.J.

    Beauty photoproduction measured using decays into muons in dijet events in ep collisions at s\sqrt{s}=318 GeV

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    The photoproduction of beauty quarks in events with two jets and a muon has been measured with the ZEUS detector at HERA using an integrated luminosity of 110 pb−1^{- 1}. The fraction of jets containing b quarks was extracted from the transverse momentum distribution of the muon relative to the closest jet. Differential cross sections for beauty production as a function of the transverse momentum and pseudorapidity of the muon, of the associated jet and of xγjetsx_{\gamma}^{jets}, the fraction of the photon's momentum participating in the hard process, are compared with MC models and QCD predictions made at next-to-leading order. The latter give a good description of the data.Comment: 32 pages, 6 tables, 7 figures Table 6 and Figure 7 revised September 200

    Search for a narrow charmed baryonic state decaying to D^*+/- p^-/+ in ep collisions at HERA

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    A resonance search has been made in the D^*+/- p^-/+ invariant-mass spectrum with the ZEUS detector at HERA using an integrated luminosity of 126 pb^-1. The decay channels D^*+ -> D^0 pi^+_s -> (K^- pi^+) pi^+_s and D^*+ -> D^0 pi^+_s -> (K^- pi^+ pi^+ pi^-) pi^+_s (and the corresponding antiparticle decays) were used to identify D^*+/- mesons. No resonance structure was observed in the D^*+/- p^-/+ mass spectrum from more than 60000 reconstructed D^*+/- mesons. The results are not compatible with a report of the H1 Collaboration of a charmed pentaquark, Theta^0_c.Comment: 22 pages, 7 figures, 1 table; minor text revisions; 2 references adde

    Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

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    Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

    Haemodynamics and flow modiïŹcation stents for peripheral arterial disease:a review

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    Endovascular stents are widely used for the treatment of peripheral arterial disease (PAD). However, the development of in-stent restenosis and downstream PAD progression remain a challenge. Stent revascularisation of PAD causes arterial trauma and introduces abnormal haemodynamics, which initiate complicated biological processes detrimental to the arterial wall. The interaction between stent struts and arterial cells in contact, and the blood flow field created in a stented region, are highly affected by stent design. Spiral flow is known as a normal physiologic characteristic of arterial circulation and is believed to prevent the development of flow disturbances. This secondary flow motion is lost in atheromatous disease and its re-introduction after endovascular treatment of PAD has been suggested as a method to induce stabilised and coherent haemodynamics. Stent designs able to generate spiral flow may support endothelial function and therefore increase patency rates. This review is focused on secondary flow phenomena in arteries and the development of flow modification stent technologies for the treatment of PAD

    Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks

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    peer reviewedaudience: researcher, professionalVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods, i.e.multiple linear regression and artificial neural networks, that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods, the uncertainty associated with the model predictions is also evaluated, since such information is important for stochastic groundwater flow and contaminant transport modelling. Artificial neural networks (ANNs) are combined with a generalized likelihood uncertainty estimation (GLUE) approach to predict Ks from grain-size data. The resulting GLUE-ANN hydraulic conductivity predictions and associated uncertainty estimates are compared with those obtained from the multiple linear regression models by a leave-one-out cross-validation. The GLUE-ANN ensemble prediction proved to be slightly better than multiple linear regression. The prediction uncertainty, however, was reduced by half an order of magnitude on average, and decreased at most by an order of magnitude. This demonstrates that the proposed method outperforms classical data-driven modelling techniques. Moreover, a comparison with methods from literature demonstrates the importance of site specific calibration. The dataset used for this purpose originates mainly from unconsolidated sandy sediments of the Neogene aquifer, northern Belgium. The proposed predictive models are developed for 173 grain-size -Ks pairs. Finally, an application with the optimized models is presented for a borehole lacking Ks data

    NGF Is an Essential Survival Factor for Bronchial Epithelial Cells during Respiratory Syncytial Virus Infection

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    Background: Overall expression of neurotrophins in the respiratory tract is upregulated in infants infected by the respiratory syncytial virus (RSV), but it is unclear where (structural vs. inflammatory cells, upper vs. lower airways) and why, these changes occur. We analyzed systematically the expression of neurotrophic factors and receptors following RSV infection of human nasal, tracheal, and bronchial epithelial cells, and tested the hypothesis that neurotrophins work as innate survival factors for infected respiratory epithelia. Methodology: Expression of neurotrophic factors (nerve growth factor, NGF; brain-derived neurotrophic factor, BDNF) and receptors (trkA, trkB, p75) was analyzed at the protein level by immunofluorescence and flow cytometry and at the mRNA level by real-time PCR. Targeted siRNA was utilized to blunt NGF expression, and its effect on virus-induced apoptosis/ necrosis was evaluated by flow cytometry following annexin V/7-AAD staining. Principal Findings: RSV infection was more efficient in cells from more distal (bronchial) vs. more proximal origin. In bronchial cells, RSV infection induced transcript and protein overexpression of NGF and its high-affinity receptor trkA, with concomitant downregulation of the low-affinity p75 NTR. In contrast, tracheal cells exhibited an increase in BDNF, trkA and trkB, and nasal cells increased only trkA. RSV-infected bronchial cells transfected with NGF-specific siRNA exhibited decreased trkA and increased p75 NTR expression. Furthermore, the survival of bronchial epithelial cells was dramaticall
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