Shock wave apparatus for studying minerals at high pressure and impact phenomena on planetary surfaces

Shock wave and experimental impact phenomena research on geological and planetary materials is being carried out using two propellant (18 and 40 mm) guns (up to 2.5 km/sec) and a two‐stage light gas gun (up to 7 km/sec). Equation of state measurements on samples initially at room temperature and at low and high temperatures are being conducted using the 40 mm propellant apparatus in conjunction with Helmholtz coils, and radiative detectors and, in the case of the light gas gun, with streak cameras. The 18 mm propellant gun is used for recovery experiments on minerals, impact on cryogenic targets, and radiative post‐shock temperature measurements

RNAmut: robust identification of somatic mutations in acute myeloid leukemia using RNA-sequencing.

Acute myeloid leukemia (AML) is an aggressive malignancy of haematopoietic stem cells driven by a well-defined set of somatic mutations.1,2 Identifying the mutations driving individual cases is important for assigning the patient to a recognized World Health Organisation category, establishing prognostic risk and tailoring post-consolidation therapy.3 As a result, AML research and diagnostic laboratories apply diverse methodologies to detect important mutations and many are introducing next-generation sequencing (NGS) approaches to study extended panels of genes in order to refine genomic classification and prognostic category.1 Besides the implications of these developments on costs, expertise and reliance on commercial providers, they also do not capture gene expression data, which have independent prognostic value that cannot be inferred from somatic mutation profiles. The ability to detect AML gene mutations as well as gene expression profiles from a single assay, could provide a holistic tool that accelerates research, simplifies diagnostic work-up and helps develop integrated algorithms to refine individual patient prognosis. Here, we show that AML RNA sequencing (RNA-seq) data can be used to reliably detect all types of clinically important mutations and develop a bespoke fast and easy-to-use software (RNAmut) for this purpose that can be readily used by teams/laboratories without in-house bioinformatic expertise