Age is no barrier: predictors of academic success in older learners

Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50–79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults

α-Tocopheryl succinate and TRAIL selectively synergise in induction of apoptosis in human malignant mesothelioma cells

Malignant mesothelioma (MM) is a fatal type of neoplasia with poor therapeutic prognosis, largely due to resistance to apoptosis. We investigated the apoptotic effect of alpha-tocopheryl succinate (alpha-TOS), a strong proapoptotic agent, in combination with the immunological apoptogen TNF-related apoptosis-inducing ligand (TRAIL) on both MM and nonmalignant mesothelial cells, since MM cells show low susceptibility to the clinically intriguing TRAIL. All MM cell lines tested were sensitive to alpha-TOS-induced apoptosis, and exerted high sensitivity to TRAIL in the presence of subapoptotic doses of the vitamin E analogue. Neither TRAIL or alpha-TOS alone or in combination caused apoptosis in nonmalignant mesothelial cells. Isobologram analysis of the cytotoxicity assays revealed a synergistic interaction between the two agents in MM cells and their antagonistic effect in nonmalignant mesothelial cells. TRAIL-induced apoptosis and its augmentation by alpha-TOS were inhibited by the caspase-8 inhibitor Z-IETD-FMK and the pan-caspase inhibitor Z-VAD-FMK. Activation of caspase-8 was required to induce apoptosis, which was amplified by alpha-TOS via cytochrome c release following Bid cleavage, with ensuing activation of caspase-9. Enhancement of TRAIL-induced apoptosis in MM cells by alpha-TOS was also associated with upregulation of the TRAIL cognate death receptors DR4 and DR5. Our results show that alpha-TOS and TRAIL act in synergism to kill MM cells via mitochondrial pathway, and are nontoxic to nonmalignant mesothelial cells. These findings are indicative of a novel strategy for treatment of thus far fatal MM

The Society for Immunotherapy of Cancer consensus statement on immunotherapy for the treatment of prostate carcinoma

Prostate cancer is the most commonly diagnosed malignancy and second leading cause of cancer death among men in the United States. In recent years, several new agents, including cancer immunotherapies, have been approved or are currently being investigated in late-stage clinical trials for the management of advanced prostate cancer. Therefore, the Society for Immunotherapy of Cancer (SITC) convened a multidisciplinary panel, including physicians, nurses, and patient advocates, to develop consensus recommendations for the clinical application of immunotherapy for prostate cancer patients. To do so, a systematic literature search was performed to identify high-impact papers from 2006 until 2014 and was further supplemented with literature provided by the panel. Results from the consensus panel voting and discussion as well as the literature review were used to rate supporting evidence and generate recommendations for the use of immunotherapy in prostate cancer patients. Sipuleucel-T, an autologous dendritic cell vaccine, is the first and currently only immunotherapeutic agent approved for the clinical management of metastatic castrate resistant prostate cancer (mCRPC). The consensus panel utilized this model to discuss immunotherapy in the treatment of prostate cancer, issues related to patient selection, monitoring of patients during and post treatment, and sequence/combination with other anti-cancer treatments. Potential immunotherapies emerging from late-stage clinical trials are also discussed. As immunotherapy evolves as a therapeutic option for the treatment of prostate cancer, these recommendations will be updated accordingly. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40425-016-0198-x) contains supplementary material, which is available to authorized users

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors

Spectroscopic camera analysis of the roles of molecularly assisted reaction chains during detachment in JET L-mode plasmas

The roles of the molecularly assisted ionization (MAI), recombination (MAR) and dissociation (MAD) reaction chains with respect to the purely atomic ionization and recombination processes were studied experimentally during detachment in low-confinement mode (L-mode) plasmas in JET with the help of experimentally inferred divertor plasma and neutral conditions, extracted previously from filtered camera observations of deuterium Balmer emission, and the reaction coefficients provided by the ADAS, AMJUEL and H2VIBR atomic and molecular databases. The direct contribution of MAI and MAR in the outer divertor particle balance was found to be inferior to the electron-atom ionization (EAI) and electron-ion recombination (EIR). Near the outer strike point, a strong atom source due to the D+2-driven MAD was, however, observed to correlate with the onset of detachment at outer strike point temperatures of Te,osp = 0.9-2.0 eV via increased plasma-neutral interactions before the increasing dominance of EIR at Te,osp < 0.9 eV, followed by increasing degree of detachment. The analysis was supported by predictions from EDGE2D-EIRENE simulations which were in qualitative agreement with the experimental observations

New H-mode regimes with small ELMs and high thermal confinement in the Joint European Torus

New H-mode regimes with high confinement, low core impurity accumulation, and small edge-localized mode perturbations have been obtained in magnetically confined plasmas at the Joint European Torus tokamak. Such regimes are achieved by means of optimized particle fueling conditions at high input power, current, and magnetic field, which lead to a self-organized state with a strong increase in rotation and ion temperature and a decrease in the edge density. An interplay between core and edge plasma regions leads to reduced turbulence levels and outward impurity convection. These results pave the way to an attractive alternative to the standard plasmas considered for fusion energy generation in a tokamak with a metallic wall environment such as the ones expected in ITER.& nbsp;Published under an exclusive license by AIP Publishing

Testing a prediction model for the H-mode density pedestal against JET-ILW pedestals

The neutral ionisation model proposed by Groebner et al (2002 Phys. Plasmas 9 2134) to determine the plasma density profile in the H-mode pedestal, is extended to include charge exchange processes in the pedestal stimulated by the ideas of Mahdavi et al (2003 Phys. Plasmas 10 3984). The model is then tested against JET H-mode pedestal data, both in a 'standalone' version using experimental temperature profiles and also by incorporating it in the Europed version of EPED. The model is able to predict the density pedestal over a wide range of conditions with good accuracy. It is also able to predict the experimentally observed isotope effect on the density pedestal that eludes simpler neutral ionization models

Peripheral temperature gradient screening of high-Z impurities in optimised 'hybrid' scenario H-mode plasmas in JET-ILW

Screening of high-Z (W) impurities from the confined plasma by the temperature gradient at the plasma periphery of fusion-grade H-mode plasmas has been demonstrated in the JET-ILW (ITER-like wall) tokamak. Through careful optimisation of the hybrid-scenario, deuterium plasmas with sufficient heating power (greater than or similar to 32 MW), high enough ion temperature gradients at the H-mode pedestal top can be achieved for the collisional, neo-classical convection of the W impurities to be directed outwards, expelling them from the confined plasma. Measurements of the W impurity fluxes between and during edge-localised modes (ELMs) based on fast bolometry measurements show that in such plasmas there is a net efflux (loss) between ELMs but that ELMs often allow some W back into the confined plasma. Provided steady, high-power heating is maintained, this mechanism allows such plasmas to sustain high performance, with an average D-D neutron rate of similar to 3.2 x 10(16) s(-1) over a period of similar to 3 s, after an initial overshoot (equivalent to a D-T fusion power of similar to 9.4 MW), without an uncontrolled rise in W impurity radiation, giving added confidence that impurity screening by the pedestal may also occur in ITER, as has previously been predicted (Dux et al 2017 Nucl. Mater. Energy 12 28-35)

Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles

In view of the future high power nuclear fusion experiments, the early identification of disruptions is a mandatory requirement, and presently the main goal is moving from the disruption mitigation to disruption avoidance and control. In this work, a deep-convolutional neural network (CNN) is proposed to provide early detection of disruptive events at JET. The CNN ability to learn relevant features, avoiding hand-engineered feature extraction, has been exploited to extract the spatiotemporal information from 1D plasma profiles. The model is trained with regularly terminated discharges and automatically selected disruptive phase of disruptions, coming from the recent ITER-like-wall experiments. The prediction performance is evaluated using a set of discharges representative of different operating scenarios, and an in-depth analysis is made to evaluate the performance evolution with respect to the considered experimental conditions. Finally, as real-time triggers and termination schemes are being developed at JET, the proposed model has been tested on a set of recent experiments dedicated to plasma termination for disruption avoidance and mitigation. The CNN model demonstrates very high performance, and the exploitation of 1D plasma profiles as model input allows us to understand the underlying physical phenomena behind the predictor decision