707 research outputs found

    Anti-cancer effects and mechanism of actions of aspirin analogues in the treatment of glioma cancer

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    INTRODUCTION: In the past 25 years only modest advancements in glioma treatment have been made, with patient prognosis and median survival time following diagnosis only increasing from 3 to 7 months. A substantial body of clinical and preclinical evidence has suggested a role for aspirin in the treatment of cancer with multiple mechanisms of action proposed including COX 2 inhibition, down regulation of EGFR expression, and NF-κB signaling affecting Bcl-2 expression. However, with serious side effects such as stroke and gastrointestinal bleeding, aspirin analogues with improved potency and side effect profiles are being developed. METHOD: Effects on cell viability following 24 hr incubation of four aspirin derivatives (PN508, 517, 526 and 529) were compared to cisplatin, aspirin and di-aspirin in four glioma cell lines (U87 MG, SVG P12, GOS – 3, and 1321N1), using the PrestoBlue assay, establishing IC50 and examining the time course of drug effects. RESULTS: All compounds were found to decrease cell viability in a concentration and time dependant manner. Significantly, the analogue PN517 (IC50 2mM) showed approximately a twofold increase in potency when compared to aspirin (3.7mM) and cisplatin (4.3mM) in U87 cells, with similar increased potency in SVG P12 cells. Other analogues demonstrated similar potency to aspirin and cisplatin. CONCLUSION: These results support the further development and characterization of novel NSAID derivatives for the treatment of glioma

    Recent EUROfusion Achievements in Support of Computationally Demanding Multiscale Fusion Physics Simulations and Integrated Modeling

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    Integrated modeling (IM) of present experiments and future tokamak reactors requires the provision of computational resources and numerical tools capable of simulating multiscale spatial phenomena as well as fast transient events and relatively slow plasma evolution within a reasonably short computational time. Recent progress in the implementation of the new computational resources for fusion applications in Europe based on modern supercomputer technologies (supercomputer MARCONI-FUSION), in the optimization and speedup of the EU fusion-related first-principle codes, and in the development of a basis for physics codes/modules integration into a centrally maintained suite of IM tools achieved within the EUROfusion Consortium is presented. Physics phenomena that can now be reasonably modelled in various areas (core turbulence and magnetic reconnection, edge and scrape-off layer physics, radio-frequency heating and current drive, magnetohydrodynamic model, reflectometry simulations) following successful code optimizations and parallelization are briefly described. Development activities in support to IM are summarized. They include support to (1) the local deployment of the IM infrastructure and access to experimental data at various host sites, (2) the management of releases for sophisticated IM workflows involving a large number of components, and (3) the performance optimization of complex IM workflows.This work has been carried out within the framework of the EUROfusion Consortium and has received funding from the Euratom research and training programme 2014 to 2018 under grant agreement 633053. The views and opinions expressed herein do not necessarily reflect those of the European Commission or ITER.Peer ReviewedPostprint (published version

    CovidNeuroOnc: A UK multicenter, prospective cohort study of the impact of the COVID-19 pandemic on the neuro-oncology service

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    BackgroundThe COVID-19 pandemic has profoundly affected cancer services. Our objective was to determine the effect of the COVID-19 pandemic on decision making and the resulting outcomes for patients with newly diagnosed or recurrent intracranial tumors.MethodsWe performed a multicenter prospective study of all adult patients discussed in weekly neuro-oncology and skull base multidisciplinary team meetings who had a newly diagnosed or recurrent intracranial (excluding pituitary) tumor between 01 April and 31 May 2020. All patients had at least 30-day follow-up data. Descriptive statistical reporting was used.ResultsThere were 1357 referrals for newly diagnosed or recurrent intracranial tumors across 15 neuro-oncology centers. Of centers with all intracranial tumors, a change in initial management was reported in 8.6% of cases (n = 104/1210). Decisions to change the management plan reduced over time from a peak of 19% referrals at the start of the study to 0% by the end of the study period. Changes in management were reported in 16% (n = 75/466) of cases previously recommended for surgery and 28% of cases previously recommended for chemotherapy (n = 20/72). The reported SARS-CoV-2 infection rate was similar in surgical and non-surgical patients (2.6% vs. 2.4%, P > .9).ConclusionsDisruption to neuro-oncology services in the UK caused by the COVID-19 pandemic was most marked in the first month, affecting all diagnoses. Patients considered for chemotherapy were most affected. In those recommended surgical treatment this was successfully completed. Longer-term outcome data will evaluate oncological treatments received by these patients and overall survival

    Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

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    Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

    Impact of fast ions on density peaking in JET: fluid and gyrokinetic modeling

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    The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/ trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position ρt_{t}=0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile

    On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

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    A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

    Impact of fast ions on density peaking in JET : fluid and gyrokinetic modeling

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    The effect of fast ions on turbulent particle transport, driven by ion temperature gradient (ITG)/trapped electron mode turbulence, is studied. Two neutral beam injection (NBI) heated JET discharges in different regimes are analyzed at the radial position rho(t) = 0.6, one of them an L-mode and the other one an H-mode discharge. Results obtained from the computationally efficient fluid model EDWM and the gyro-fluid model TGLF are compared to linear and nonlinear gyrokinetic GENE simulations as well as the experimentally obtained density peaking. In these models, the fast ions are treated as a dynamic species with a Maxwellian background distribution. The dependence of the zero particle flux density gradient (peaking factor) on fast ion density, temperature and corresponding gradients, is investigated. The simulations show that the inclusion of a fast ion species has a stabilizing influence on the ITG mode and reduces the peaking of the main ion and electron density profiles in the absence of sources. The models mostly reproduce the experimentally obtained density peaking for the L-mode discharge whereas the H-mode density peaking is significantly underpredicted, indicating the importance of the NBI particle source for the H-mode density profile
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