Anesthesia triggers drug delivery to experimental glioma in mice by hijacking caveolar transport

Abstract Background: Pharmaceutical intervention in the CNS is hampered by the shielding function of the blood-brain barrier (BBB). To induce clinical anesthesia, general anesthetics such as isoflurane readily penetrate the BBB. Here, we investigated whether isoflurane can be utilized for therapeutic drug delivery. Methods: Barrier function in primary endothelial cells was evaluated by transepithelial/transendothelial electrical resistance, and nanoscale STED and SRRF microscopy. In mice, BBB permeability was quantified by extravasation of several fluorescent tracers. Mouse models including the GL261 glioma model were evaluated by MRI, immunohistochemistry, electron microscopy, western blot, and expression analysis. Results: Isoflurane enhances BBB permeability in a time- and concentration-dependent manner. We demonstrate that, mechanistically, isoflurane disturbs the organization of membrane lipid nanodomains and triggers caveolar transport in brain endothelial cells. BBB tightness re-establishes directly after termination of anesthesia, providing a defined window for drug delivery. In a therapeutic glioblastoma trial in mice, simultaneous exposure to isoflurane and cytotoxic agent improves efficacy of chemotherapy. Conclusions: Combination therapy, involving isoflurane-mediated BBB permeation with drug administration has far-reaching therapeutic implications for CNS malignancies

Mechanisms of TSC-mediated Control of Synapse Assembly and Axon Guidance

Tuberous sclerosis complex is a dominant genetic disorder produced by mutations in either of two tumor suppressor genes, TSC1 and TSC2; it is characterized by hamartomatous tumors, and is associated with severe neurological and behavioral disturbances. Mutations in TSC1 or TSC2 deregulate a conserved growth control pathway that includes Ras homolog enriched in brain (Rheb) and Target of Rapamycin (TOR). To understand the function of this pathway in neural development, we have examined the contributions of multiple components of this pathway in both neuromuscular junction assembly and photoreceptor axon guidance in Drosophila. Expression of Rheb in the motoneuron, but not the muscle of the larval neuromuscular junction produced synaptic overgrowth and enhanced synaptic function, while reductions in Rheb function compromised synapse development. Synapse growth produced by Rheb is insensitive to rapamycin, an inhibitor of Tor complex 1, and requires wishful thinking, a bone morphogenetic protein receptor critical for functional synapse expansion. In the visual system, loss of Tsc1 in the developing retina disrupted axon guidance independently of cellular growth. Inhibiting Tor complex 1 with rapamycin or eliminating the Tor complex 1 effector, S6 kinase (S6k), did not rescue axon guidance abnormalities of Tsc1 mosaics, while reductions in Tor function suppressed those phenotypes. These findings show that Tsc-mediated control of axon guidance and synapse assembly occurs via growth-independent signaling mechanisms, and suggest that Tor complex 2, a regulator of actin organization, is critical in these aspects of neuronal development

Search for pair-produced long-lived neutral particles decaying to jets in the ATLAS hadronic calorimeter in ppcollisions at √s=8TeV

The ATLAS detector at the Large Hadron Collider at CERN is used to search for the decay of a scalar boson to a pair of long-lived particles, neutral under the Standard Model gauge group, in 20.3fb−1of data collected in proton–proton collisions at √s=8TeV. This search is sensitive to long-lived particles that decay to Standard Model particles producing jets at the outer edge of the ATLAS electromagnetic calorimeter or inside the hadronic calorimeter. No significant excess of events is observed. Limits are reported on the product of the scalar boson production cross section times branching ratio into long-lived neutral particles as a function of the proper lifetime of the particles. Limits are reported for boson masses from 100 GeVto 900 GeV, and a long-lived neutral particle mass from 10 GeVto 150 GeV

Diet and Energy-Sensing Inputs Affect TorC1-Mediated Axon Misrouting but Not TorC2-Directed Synapse Growth in a Drosophila Model of Tuberous Sclerosis

The Target of Rapamycin (TOR) growth regulatory system is influenced by a number of different inputs, including growth factor signaling, nutrient availability, and cellular energy levels. While the effects of TOR on cell and organismal growth have been well characterized, this pathway also has profound effects on neural development and behavior. Hyperactivation of the TOR pathway by mutations in the upstream TOR inhibitors TSC1 (tuberous sclerosis complex 1) or TSC2 promotes benign tumors and neurological and behavioral deficits, a syndrome known as tuberous sclerosis (TS). In Drosophila, neuron-specific overexpression of Rheb, the direct downstream target inhibited by Tsc1/Tsc2, produced significant synapse overgrowth, axon misrouting, and phototaxis deficits. To understand how misregulation of Tor signaling affects neural and behavioral development, we examined the influence of growth factor, nutrient, and energy sensing inputs on these neurodevelopmental phenotypes. Neural expression of Pi3K, a principal mediator of growth factor inputs to Tor, caused synapse overgrowth similar to Rheb, but did not disrupt axon guidance or phototaxis. Dietary restriction rescued Rheb-mediated behavioral and axon guidance deficits, as did overexpression of AMPK, a component of the cellular energy sensing pathway, but neither was able to rescue synapse overgrowth. While axon guidance and behavioral phenotypes were affected by altering the function of a Tor complex 1 (TorC1) component, Raptor, or a TORC1 downstream element (S6k), synapse overgrowth was only suppressed by reducing the function of Tor complex 2 (TorC2) components (Rictor, Sin1). These findings demonstrate that different inputs to Tor signaling have distinct activities in nervous system development, and that Tor provides an important connection between nutrient-energy sensing systems and patterning of the nervous system

Imbalanced pattern completion vs. separation in cognitive disease: network simulations of synaptic pathologies predict a personalized therapeutics strategy

<p>Abstract</p> <p>Background</p> <p>Diverse Mouse genetic models of neurodevelopmental, neuropsychiatric, and neurodegenerative causes of impaired cognition exhibit at least four convergent points of synaptic malfunction: 1) Strength of long-term potentiation (LTP), 2) Strength of long-term depression (LTD), 3) Relative inhibition levels (Inhibition), and 4) Excitatory connectivity levels (Connectivity).</p> <p>Results</p> <p>To test the hypothesis that pathological increases or decreases in these synaptic properties could underlie imbalances at the level of basic neural network function, we explored each type of malfunction in a simulation of autoassociative memory. These network simulations revealed that one impact of impairments or excesses in each of these synaptic properties is to shift the trade-off between pattern separation and pattern completion performance during memory storage and recall. Each type of synaptic pathology either pushed the network balance towards intolerable error in pattern separation or intolerable error in pattern completion. Imbalances caused by pathological impairments or excesses in LTP, LTD, inhibition, or connectivity, could all be exacerbated, or rescued, by the simultaneous modulation of any of the other three synaptic properties.</p> <p>Conclusions</p> <p>Because appropriate modulation of any of the synaptic properties could help re-balance network function, regardless of the origins of the imbalance, we propose a new strategy of personalized cognitive therapeutics guided by assay of pattern completion vs. pattern separation function. Simulated examples and testable predictions of this theorized approach to cognitive therapeutics are presented.</p

Semantic Web technology for Grid control

Today, semantic technologies are deployed in the representation of knowledge and the development of inference engines that can incorporate reasoning capabilities to the systems. The S-TEN technology is extending the Semantic Web technologies for applications in industrial sectors. In the field of active distribution networks several objectives are addressed: to enable an automatic re-configuration of a microgrid, to improve the integration of dispersed generation by enhanced monitoring and control processes and to facilitate the integration of demand resources into the control of the grid using market mechanisms. The grids of the electrical network of the future will need to be highly automated, will require a reduced human intervention and will have a dynamic characteristic. Dynamic characteristic indicates the possibility of the equipment connected in the network to connect, disconnect and provide services to the central controller for managing the network. This capability will require plug and play capabilities that need the specification of standard protocols and data exchange models. But apart from this it also requires to provide self-describing capabilities to the devices and inference capabilities to the grid controller. Within the EU project S-TEN, co-funded by the European Community's Sixth Framework Programme (FP6), three applications will be developed in the area of power systems, two of them being presented in this paper. One application is dedicated to microgrid control and the other one focuses on the mechanisms for demand side bidding and resources dispatch. A description of the third application committed to the monitoring and control of distributed energy resources is given in [2]. 1. Microgrid control application The application that is going to be developed is related with the secondary control of a microgrid, but taking into account that the knowledge about the components that can be controlled makes the re-configuration of the network simpler. This advantage of adjustable operation facilitates the penetration of renewables, and makes possible an intelligent and distributed reaction to disturbances that can deviate the operation of the microgrid from its intended purpose. In the paper, the components of the microgrid will be described as well as the normal operation scenario and a set of disturbances or deviations from a normal scenario. The kind of disturbances that will be considered are failures of generation sources, the shutdown of modules in charge of scheduling the resources or the failure of generators to give the assigned power to the network. Besides, it will show the ontology used for the selfdescription of one of the components. 2. Demand-Side Bidding Demand-Side Bidding (DSB) enables the supplier to adjust his Spot Market bids. Such optimized exploitation of loads during the planning phase requires appropriate measures during the operation phase in order to guarantee a balanced system. Today DSB is only applied to dedicated large single consumers or groups of large consumers with similar behaviour. An appropriate Control, Metering and Communication (CMC) infrastructure is customized based on a case by case analysis. The S-TEN approach suggests a more generic CMC infrastructure based on Semantic Web technologies. It reduces costs and enables wider DSB participation of smaller consumers. S-TEN technology will support the self-description of devices and the publishing of services on the web, e. g. storage capabilities of heating and cooling devices could be published dynamically on the web. This information will be exploited for improved bids on one hand and a balanced system within a trading period on the other hand. Additional information on the applications and on the project is provided at the project's website.Peer reviewe