Pulsed, Photonuclear-induced, Neutron Measurements of Nuclear Materials with Composite Shielding

Active measurements were performed using a 10-MeV electron accelerator with inspection objects containing various nuclear and nonnuclear materials available at the Idaho National Laboratory’s Zero Power Physics Reactor (ZPPR) facility. The inspection objects were assembled from ZPPR reactor plate materials to evaluate the measurement technologies for the characterization of plutonium, depleted uranium or highly enriched uranium shielded by both nuclear and non-nuclear materials. A series of pulsed photonuclear, time-correlated measurements were performed with unshielded calibration materials and then compared with the more complex composite shield configurations. The measurements used multiple 3He detectors that are designed to detect fission neutrons between pulses of an electron linear accelerator. The accelerator produced 10-MeV bremsstrahlung X-rays at a repetition rate of 125 Hz (8 ms between pulses) with a 4-us pulse width. All inspected objects were positioned on beam centerline and 100 cm from the X-ray source. The time-correlated data was collected in parallel using both a Los Alamos National Laboratory-designed list-mode acquisition system and a commercial multichannel scaler analyzer. A combination of different measurement configurations and data analysis methods enabled the identification of each object. This paper describes the experimental configuration, the ZPPR inspection objects used, and the various measurement and analysis results for each inspected object

Estimation of tumor cell total mRNA expression in 15 cancer types predicts disease progression

Single-cell RNA sequencing studies have suggested that total mRNA content correlates with tumor phenotypes. Technical and analytical challenges, however, have so far impeded at-scale pan-cancer examination of total mRNA content. Here we present a method to quantify tumor-specific total mRNA expression (TmS) from bulk sequencing data, taking into account tumor transcript proportion, purity and ploidy, which are estimated through transcriptomic/genomic deconvolution. We estimate and validate TmS in 6,590 patient tumors across 15 cancer types, identifying significant inter-tumor variability. Across cancers, high TmS is associated with increased risk of disease progression and death. TmS is influenced by cancer-specific patterns of gene alteration and intra-tumor genetic heterogeneity as well as by pan-cancer trends in metabolic dysregulation. Taken together, our results indicate that measuring cell-type-specific total mRNA expression in tumor cells predicts tumor phenotypes and clinical outcomes.publishedVersionPeer reviewe