The association between glucocorticoid therapy and BMI z-score changes in children with acute lymphoblastic leukemia

PURPOSE: Few studies have addressed the common issue of weight gain in children with acute lymphoblastic leukemia (ALL) during early phases of treatment, and even fewer have used the appropriate measure for weight fluctuation in children, BMI-for-age z-scores (BAZs). The purpose of this study is thus to measure the extent of the weight gain in BAZ during the 150 first days of treatment and to identify factors associated with the weight gain. Furthermore, we wish to raise the question of whether changes in treatment protocols automatically should be followed by an evaluation of the nutritional guidelines.METHOD: In this retrospective study, the medical records of 51 children with ALL treated with the NOPHO ALL 2008 protocol at Copenhagen University Hospital were assessed. Patient characteristics were extracted, and height, weight, and age during the first 150 days of treatment were converted to BAZ.RESULTS: During 150 days of treatment, the proportion of overweight/obese patients increased significantly from 9.8 to 33.3 %. The mean change in BAZ (∆BAZ) was +1 standard deviation (0.02 ± 1.16 vs. 1.12 ± 1.44; p &lt; 0.001) and BAZ increased significantly during periods with glucocorticoid (GC) treatment but not in periods without GC. ΔBAZ was larger in boys compared to girls, and ΔBAZ was higher in patients who were under/normal weight at diagnosis, compared to patients who were overweight/obese (1.26 ± 1.29 vs. -0.04 ± 0.41; p = 0.032).CONCLUSION: BAZ increased significantly in children with ALL during the initial treatment with the NOPHO ALL 2008 protocol. This is likely associated with the GC administration and influenced by gender and initial BAZ.</p

Ion cyclotron resonance heating scenarios for DEMO

The present paper offers an overview of the potential of ion cyclotron resonance heating (ICRH) or radio frequency heating for the DEMO machine. It is found that various suitable heating schemes are available. Similar to ITER and in view of the limited bandwidth of about 10 MHz that can be achieved to ensure optimal functioning of the launcher, it is proposed to make core second harmonic tritium heating the key ion heating scheme, assisted by fundamental cyclotron heating He-3 in the early phase of the discharge; for the present design of DEMO-with a static magnetic field strength of B-o = 5.855 T-that places the T and 3He layers in the core for f = 60 MHz and suggests centering the bandwidth around that main operating frequency. In line with earlier studies for hot, dense plasmas in large-size magnetic confinement machines, it is shown that good single pass absorption is achieved but that the size as well as the operating density and temperature of the machine cause the electrons to absorb a non-negligible fraction of the power away from the core when core ion heating is aimed at. Current drive and alternative heating options are briefly discussed and a dedicated computation is done for the traveling wave antenna, proposed for DEMO in view of its compatibility with substantial antenna-plasma distances. The various tasks that ICRH can fulfill are briefly listed. Finally, the impact of transport and the sensitivity of the obtained results to changes in the machine parameters is commented on

Adaptive learning for disruption prediction in non-stationary conditions

For many years, machine learning tools have proved to be very powerful disruption predictors in tokamaks. On the other hand, the vast majority of the techniques deployed assume that the input data is independent and is sampled from exactly the same probability distribution for the training set, the test set and the final real time deployment. This hypothesis is certainly not verified in practice, since the experimental programmes evolve quite rapidly, resulting typically in ageing of the predictors and consequent suboptimal performance. This paper describes various adaptive training strategies that have been tested to maintain the performance of disruption predictors in non-stationary conditions. The proposed approaches have been implemented using new ensembles of classifiers, explicitly developed for the present application. The improvements in performance are unquestionable and, given the difficulties encountered so far in translating predictors from one device to another, the proposed adaptive methods from scratch can therefore be considered a useful option in the arsenal of alternatives envisaged for the next generation of devices, particularly at the very beginning of their operation