49,498 research outputs found

    The differential contribution of tumour necrosis factor to thermal and mechanical hyperalgesia during chronic inflammation

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    Therapies directed against tumour necrosis factor (TNF) are effective for the treatment of rheumatoid arthritis and reduce pain scores in this condition. In this study, we sought to explore mechanisms by which TNF contributes to inflammatory pain in an experimental model of arthritis. The effects of an anti-TNF agent, etanercept, on behavioural pain responses arising from rat monoarthritis induced by complete Freund's adjuvant were assessed and compared with expression of TNF receptors (TNFRs) by dorsal root ganglion (DRG) cells at corresponding time points. Etanercept had no effect on evoked pain responses in normal animals but exerted a differential effect on the thermal and mechanical hyperalgesia associated with rat arthritis induced by complete Freund's adjuvant (CFA). Joint inflammation was associated with increased TNFR1 and TNFR2 expression on DRG cells, which was maintained throughout the time course of the model. TNFR1 expression was increased in neuronal cells of the DRG bilaterally after arthritis induction. In contrast, TNFR2 expression occurred exclusively on nonneuronal cells of the macrophage-monocyte lineage, with cell numbers increasing in a TNF-dependent fashion during CFA-induced arthritis. A strong correlation was observed between numbers of macrophages and the development of mechanical hyperalgesia in CFA-induced arthritis. These results highlight the potential for TNF to play a vital role in inflammatory hyperalgesia, both by a direct action on neurons via TNFR1 and by facilitating the accumulation of macrophages in the DRG via a TNFR2-mediated pathway

    DAzLE: The Dark Ages z (redshift) Lyman-alpha Explorer

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    DAzLE is an near infrared narrowband differential imager being built by the Institute of Astronomy, Cambridge, in collaboration with the Anglo-Australian observatory. It is a special purpose instrument designed with a sole aim; the detection of redshifted Lyman-alpha emission from star forming galaxies at z>7. DAzLE will use pairs of high resolution (R=1000) narrowband filters to exploit low background `windows' in the near infrared sky emission spectrum. This will enable it to reach sensitivities of ~2E-21 W/m^2, thereby allowing the detection of z>7 galaxies with star formation rates as low as a few solar masses per year. The design of the instrument, and in particular the crucial narrowband filters, are presented. The predicted performance of DAzLE, including the sensitivity, volume coverage and expected number counts, is discussed. The current status of the DAzLE project, and its projected timeline, are also presented.Comment: 11 pages, 7 figures, to appear in Proceedings of SPIE Vol. 5492, Ground-based Instrumentation for Astronom

    Optimistic Value Iteration

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    Markov decision processes are widely used for planning and verification in settings that combine controllable or adversarial choices with probabilistic behaviour. The standard analysis algorithm, value iteration, only provides lower bounds on infinite-horizon probabilities and rewards. Two “sound” variations, which also deliver an upper bound, have recently appeared. In this paper, we present a new sound approach that leverages value iteration’s ability to usually deliver good lower bounds: we obtain a lower bound via standard value iteration, use the result to “guess” an upper bound, and prove the latter’s correctness. We present this optimistic value iteration approach for computing reachability probabilities as well as expected rewards. It is easy to implement and performs well, as we show via an extensive experimental evaluation using our implementation within the mcsta model checker of the Modest Toolset

    Ketamine coadministration attenuates morphine tolerance and leads to increased brain concentrations of both drugs in the rat

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    Background and Purpose The effects of ketamine in attenuating morphine tolerance have been suggested to result from a pharmacodynamic interaction. We studied whether ketamine might increase brain morphine concentrations in acute coadministration, in morphine tolerance and morphine withdrawal. Experimental Approach Morphine minipumps (6mg center dot day(-1)) induced tolerance during 5 days in Sprague-Dawley rats, after which s.c. ketamine (10mg center dot kg(-1)) was administered. Tail flick, hot plate and rotarod tests were used for behavioural testing. Serum levels and whole tissue brain and liver concentrations of morphine, morphine-3-glucuronide, ketamine and norketamine were measured using HPLC-tandem mass spectrometry. Key Results In morphine-naive rats, ketamine caused no antinociception whereas in morphine-tolerant rats there was significant antinociception (57% maximum possible effect in the tail flick test 90min after administration) lasting up to 150min. In the brain of morphine-tolerant ketamine-treated rats, the morphine, ketamine and norketamine concentrations were 2.1-, 1.4- and 3.4-fold, respectively, compared with the rats treated with morphine or ketamine only. In the liver of morphine-tolerant ketamine-treated rats, ketamine concentration was sixfold compared with morphine-naive rats. After a 2 day morphine withdrawal period, smaller but parallel concentration changes were observed. In acute coadministration, ketamine increased the brain morphine concentration by 20%, but no increase in ketamine concentrations or increased antinociception was observed. Conclusions and Implications The ability of ketamine to induce antinociception in rats made tolerant to morphine may also be due to increased brain concentrations of morphine, ketamine and norketamine. The relevance of these findings needs to be assessed in humans.Peer reviewe

    Stochastic Gravity: Theory and Applications

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    Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel.In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime: we compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a quasi-static black hole.Comment: 75 pages, no figures, submitted to Living Reviews in Relativit

    Sequence learning in Associative Neuronal-Astrocytic Network

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    The neuronal paradigm of studying the brain has left us with limitations in both our understanding of how neurons process information to achieve biological intelligence and how such knowledge may be translated into artificial intelligence and its most brain-derived branch, neuromorphic computing. Overturning our fundamental assumptions of how the brain works, the recent exploration of astrocytes is revealing that these long-neglected brain cells dynamically regulate learning by interacting with neuronal activity at the synaptic level. Following recent experimental evidence, we designed an associative, Hopfield-type, neuronal-astrocytic network and analyzed the dynamics of the interaction between neurons and astrocytes. We show that astrocytes were sufficient to trigger transitions between learned memories in the neuronal component of the network. Further, we mathematically derived the timing of the transitions that was governed by the dynamics of the calcium-dependent slow-currents in the astrocytic processes. Overall, we provide a brain-morphic mechanism for sequence learning that is inspired by, and aligns with, recent experimental findings. To evaluate our model, we emulated astrocytic atrophy and showed that memory recall becomes significantly impaired after a critical point of affected astrocytes was reached. This brain-inspired and brain-validated approach supports our ongoing efforts to incorporate non-neuronal computing elements in neuromorphic information processing.Comment: 8 pages, 5 figure

    On classical finite and affine W-algebras

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    This paper is meant to be a short review and summary of recent results on the structure of finite and affine classical W-algebras, and the application of the latter to the theory of generalized Drinfeld-Sokolov hierarchies.Comment: 12 page
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