KAT6B-related disorder in a patient with a novel frameshift variant (c.3925dup)

Heterozygous pathogenic variants in the KAT6B gene, which encodes lysine acetyltransferase 6B, have been identified in patients with congenital rare disorders, including genitopatellar syndrome and Say-Barber-Biesecker-Young-Simpson syndrome. Herein, we report another Japanese patient with a KAT6B-related disorder and a novel de novo heterozygous variant in exon 18 of KAT6B [c.3925dup, p.(Glu1309fs*33)], providing further evidence that truncating variants in exon 17 and in the proximal region of exon 18 are associated with genitopatellar syndrome-like phenotypes

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization

Overview of JET results for optimising ITER operation

The JET 2019-2020 scientific and technological programme exploited the results of years of concerted scientific and engineering work, including the ITER-like wall (ILW: Be wall and W divertor) installed in 2010, improved diagnostic capabilities now fully available, a major neutral beam injection upgrade providing record power in 2019-2020, and tested the technical and procedural preparation for safe operation with tritium. Research along three complementary axes yielded a wealth of new results. Firstly, the JET plasma programme delivered scenarios suitable for high fusion power and alpha particle (alpha) physics in the coming D-T campaign (DTE2), with record sustained neutron rates, as well as plasmas for clarifying the impact of isotope mass on plasma core, edge and plasma-wall interactions, and for ITER pre-fusion power operation. The efficacy of the newly installed shattered pellet injector for mitigating disruption forces and runaway electrons was demonstrated. Secondly, research on the consequences of long-term exposure to JET-ILW plasma was completed, with emphasis on wall damage and fuel retention, and with analyses of wall materials and dust particles that will help validate assumptions and codes for design and operation of ITER and DEMO. Thirdly, the nuclear technology programme aiming to deliver maximum technological return from operations in D, T and D-T benefited from the highest D-D neutron yield in years, securing results for validating radiation transport and activation codes, and nuclear data for ITER

Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfv\ue9nic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfv\ue9nic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity

Fast-ion orbit sensitivity of neutron and gamma-ray diagnostics for one-step fusion reactions

Fast ions in the MeV-range can be diagnosed by neutron emission spectroscopy (NES) and gamma-ray spectroscopy (GRS). In this work, we present orbit weight functions for one-step fusion reactions, using NES and GRS diagnostics on perpendicular and oblique lines-of-sight (LOS) at Joint European Torus (JET) as examples. The orbit weight functions allow us to express the sensitivities of the diagnostics in terms of fast-ion (FI) orbits and can be used to swiftly reproduce synthetic signals that have been computed by established codes. For diagnostically relevant neutron energies for the D(D, n)He-3 reaction, the orbit sensitivities of the NES diagnostics follow a predictable pattern. As the neutron energy of interest increases, the pattern shifts upwards in FI energy. For the GRS diagnostic and the T(p,gamma)He-4 reaction, the orbit sensitivity is shown to be qualitatively different for red-shifted, blue-shifted and nominal gamma birth energies. Finally, we demonstrate how orbit weight functions can be used to decompose diagnostic signals into the contributions from different orbit types. For a TRANSP simulation of the JET discharge (a three-ion ICRF scenario) considered in this work, the NES signals for both the perpendicular and oblique LOS are shown to originate mostly from co-passing orbits. In addition, a significant fraction of the NES signal for the oblique LOS is shown to originate from stagnation orbits

Enhanced performance in fusion plasmas through turbulence suppression by megaelectronvolt ions

Alpha particles with energies on the order of megaelectronvolts will be the main source of plasma heating in future magnetic confinement fusion reactors. Instead of heating fuel ions, most of the energy of alpha particles is transferred to electrons in the plasma. Furthermore, alpha particles can also excite Alfvenic instabilities, which were previously considered to be detrimental to the performance of the fusion device. Here we report improved thermal ion confinement in the presence of megaelectronvolts ions and strong fast ion-driven Alfvenic instabilities in recent experiments on the Joint European Torus. Detailed transport analysis of these experiments reveals turbulence suppression through a complex multi-scale mechanism that generates large-scale zonal flows. This holds promise for more economical operation of fusion reactors with dominant alpha particle heating and ultimately cheaper fusion electricity