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On 14 June 2017 at 00:54 h, the worst residential fire since the conclusion of the Second World War broke out in Flat 16, 4th floor of the 24-storey residential Grenfell Tower Block of flats, North Kensington, West London, UK. Seventy-one adults and children died, including one stillbirth. All victims of the Grenfell Tower disaster who died at the scene underwent post-mortem computed tomography (PMCT) imaging using a mortuary-sited mobile computed tomography scanner. For the first time, to the authors' knowledge, the disaster victim identification (DVI) radiology reporting was undertaken remote to the mortuary scanning. Over an 11-week period, 119 scans were undertaken on 16 days, with up to 18 scans a day. These were delivered to a remote reporting centre at Leicester on 13 days with between 2 and 20 scans arriving each day. Using a disaster-specific process pathway, a team of 4 reporters, with 3 support staff members, trialled a prototype INTERPOL DVI radiology reporting form and produced full radiology reports and supporting image datasets such that they were able to provide 96% of prototype DVI forms, 99% of image datasets and 86% of preliminary reports to the DVI teams in London within one working day of image receipt. This paper describes the first use of remote radiology reporting for DVI and exemplifies how remote PMCT reporting can be used to support a DVI process of this scale. [ABSTRACT FROM AUTHOR]

Determining whether recurrent but rare cancer mutations are bona fide driver mutations remains a bottleneck in cancer research. Here we present the most comprehensive analysis of murine leukemia virus-driven lymphomagenesis produced to date, sequencing 700,000 mutations from >500 malignancies collected at time points throughout tumor development. This scale of data allows novel statistical approaches for identifying selected mutations and yields a high-resolution, genome-wide map of the selective forces surrounding cancer gene loci. We also demonstrate negative selection of mutations that may be deleterious to tumor development indicating novel avenues for therapy. Screening of two BCL2 transgenic models confirmed known drivers of human non-Hodgkin lymphoma, and implicates novel candidates including modifiers of immunosurveillance and MHC loci. Correlating mutations with genotypic and phenotypic features independently of local variance in mutation density also provides support for weakly evidenced cancer genes. An online resource http://mulv.lms.mrc.ac.uk allows customized queries of the entire dataset. [ABSTRACT FROM AUTHOR]

The original version of this Article contained an error in the hyperlink for the online repository http://mulvdb.org which was incorrectly given as http://mulv.lms.mrc.ac.uk. This has been corrected in both the PDF and HTML versions of the Article. [ABSTRACT FROM AUTHOR]