Quality Assurance of Spectral Ultraviolet Measurements in Europe Through the Development of a Transportable Unit (QASUME)

QASUME is a European Commission funded project that aims to develop and test a transportable unit for providing quality assurance to UV spectroradiometric measurements conducted in Europe. The comparisons will be performed at the home sites of the instruments, thus avoiding the risk of transporting instruments to participate in intercomparison campaigns. Spectral measurements obtained at each of the stations will be compared, following detailed and objective comparison protocols, against collocated measurements performed by a thoroughly tested and validated travelling unit. The transportable unit comprises a spectroradiometer, its calibrator with a set of calibration lamps traceable to the sources of different Standards Laboratories, and devices for determining the slit function and the angular response of the local spectroradiometers. The unit will be transported by road to about 25 UV stations over a period of about two years. The spectroradiometer of the transportable unit is compared in an intercomparison campaign with six instruments to establish a relation, which would then be used as a reference for its calibration over the period of its regular operation at the European stations. Different weather patterns (from clear skies to heavy rain) were present during the campaign, allowing the performance of the spectroradiometers to be evaluated under unfavourable conditions (as may be experienced at home sites) as well as the more desirable dry conditions. Measurements in the laboratory revealed that the calibration standards of the spectroradiometers differ by up to 10%. The evaluation is completed through comparisons with the same six instruments at their homes sites

Spectral aerosol optical depth from SI-traceable spectral solar irradiance measurements

Spectroradiometric measurements of direct solar irradiance traceable to the SI were performed by three spectroradiometer systems during a 3-week campaign in September 2022 at the Izaña Atmospheric Observatory (IZO) located on the island of Tenerife, Canary Islands, Spain. The spectroradiometers provided direct spectral irradiance measurements in the spectral ranges 300 to 550 nm (QASUME), 550 to 1700 nm (QASUME-IR), 300 to 2150 nm (BiTec Sensor, BTS), and 316 to 1030 nm (Precision Solar Spectroradiometer, PSR), with relative standard uncertainties of 0.7 %, 0.9 %, and 1 % for QASUME/QASUME-IR, the PSR, and the BTS respectively. The calibration of QASUME and QASUME-IR was validated prior to this campaign at Physikalisch-Technische Bundesanstalt (PTB) by measuring the spectral irradiance from two spectral irradiance sources, the high-temperature blackbody BB3200pg as a national primary standard and the tuneable laser facility TULIP

Physarum nitric oxide synthases: genomic structures and enzymology of recombinant proteins

Physarum polycephalum expresses two closely related, calcium-independent NOSs (nitric oxide synthases). In our previous work, we showed that both NOSs are induced during starvation and apparently play a functional role in sporulation. In the present study, we characterized the genomic structures of both Physarum NOSs, expressed both enzymes recombinantly in bacteria and characterized their biochemical properties. Whereas the overall genomic organization of Physarum NOS genes is comparable with various animal NOSs, none of the exon–intron boundaries are conserved. Recombinant expression of clones with various N-termini identified N-terminal amino acids essential for enzyme activity, but not required for haem binding or dimerization, and suggests the usage of non-AUG start codons for Physarum NOSs. Biochemical characterization of the two Physarum isoenzymes revealed different affinities for L-arginine, FMN and 6R-5,6,7,8-tetrahydro-L-biopterin

Therapeutic targeting of ependymoma as informed by oncogenic enhancer profiling

Genomic sequencing has driven precision-based oncology therapy; however, the genetic drivers of many malignancies remain unknown or non-targetable, so alternative approaches to the identification of therapeutic leads are necessary. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Intracranial ependymomas are segregated on the basis of anatomical location (supratentorial region or posterior fossa) and further divided into distinct molecular subgroups that reflect differences in the age of onset, gender predominance and response to therapy1,2,3. The most common and aggressive subgroup, posterior fossa ependymoma group A (PF-EPN-A), occurs in young children and appears to lack recurrent somatic mutations2. Conversely, posterior fossa ependymoma group B (PF-EPN-B) tumours display frequent large-scale copy number gains and losses but have favourable clinical outcomes1,3. More than 70% of supratentorial ependymomas are defined by highly recurrent gene fusions in the NF-κB subunit gene RELA (ST-EPN-RELA), and a smaller number involve fusion of the gene encoding the transcriptional activator YAP1 (ST-EPN-YAP1)1,3,4. Subependymomas, a distinct histologic variant, can also be found within the supratetorial and posterior fossa compartments, and account for the majority of tumours in the molecular subgroups ST-EPN-SE and PF-EPN-SE. Here we describe mapping of active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts, with the goal of identifying essential super-enhancer-associated genes on which tumour cells depend. Enhancer regions revealed putative oncogenes, molecular targets and pathways; inhibition of these targets with small molecule inhibitors or short hairpin RNA diminished the proliferation of patient-derived neurospheres and increased survival in mouse models of ependymomas. Through profiling of transcriptional enhancers, our study provides a framework for target and drug discovery in other cancers that lack known genetic drivers and are therefore difficult to treat.This work was supported by an Alex's Lemonade Stand Young Investigator Award (S.C.M.), The CIHR Banting Fellowship (S.C.M.), The Cancer Prevention Research Institute of Texas (S.C.M., RR170023), Sibylle Assmus Award for Neurooncology (K.W.P.), the DKFZ-MOST (Ministry of Science, Technology & Space, Israel) program in cancer research (H.W.), James S. McDonnell Foundation (J.N.R.) and NIH grants: CA154130 (J.N.R.), R01 CA169117 (J.N.R.), R01 CA171652 (J.N.R.), R01 NS087913 (J.N.R.) and R01 NS089272 (J.N.R.). R.C.G. is supported by NIH grants T32GM00725 and F30CA217065. M.D.T. is supported by The Garron Family Chair in Childhood Cancer Research, and grants from the Pediatric Brain Tumour Foundation, Grand Challenge Award from CureSearch for Children’s Cancer, the National Institutes of Health (R01CA148699, R01CA159859), The Terry Fox Research Institute and Brainchild. M.D.T. is also supported by a Stand Up To Cancer St. Baldrick’s Pediatric Dream Team Translational Research Grant (SU2C-AACR-DT1113)

A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.

As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.We thank the DKFZ Genomics and Proteomics Core Facility and the OICR Genome Technologies Platform for provision of sequencing services. Financial support was provided by the consortium projects READNA under grant agreement FP7 Health-F4-2008-201418, ESGI under grant agreement 262055, GEUVADIS under grant agreement 261123 of the European Commission Framework Programme 7, ICGC-CLL through the Spanish Ministry of Science and Innovation (MICINN), the Instituto de Salud Carlos III (ISCIII) and the Generalitat de Catalunya. Additional financial support was provided by the PedBrain Tumor Project contributing to the International Cancer Genome Consortium, funded by German Cancer Aid (109252) and by the German Federal Ministry of Education and Research (BMBF, grants #01KU1201A, MedSys #0315416C and NGFNplus #01GS0883; the Ontario Institute for Cancer Research to PCB and JDM through funding provided by the Government of Ontario, Ministry of Research and Innovation; Genome Canada; the Canada Foundation for Innovation and Prostate Cancer Canada with funding from the Movember Foundation (PCB). PCB was also supported by a Terry Fox Research Institute New Investigator Award, a CIHR New Investigator Award and a Genome Canada Large-Scale Applied Project Contract. The Synergie Lyon Cancer platform has received support from the French National Institute of Cancer (INCa) and from the ABS4NGS ANR project (ANR-11-BINF-0001-06). The ICGC RIKEN study was supported partially by RIKEN President’s Fund 2011, and the supercomputing resource for the RIKEN study was provided by the Human Genome Center, University of Tokyo. MDE, LB, AGL and CLA were supported by Cancer Research UK, the University of Cambridge and Hutchison-Whampoa Limited. SD is supported by the Torres Quevedo subprogram (MI CINN) under grant agreement PTQ-12-05391. EH is supported by the Research Council of Norway under grant agreements 221580 and 218241 and by the Norwegian Cancer Society under grant agreement 71220-PR-2006-0433. Very special thanks go to Jennifer Jennings for administrating the activity of the ICGC Verification Working Group and Anna Borrell for administrative support.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1000

Optimizing Employee Schedules by a Hybrid Genetic Algorithm

Creating an employee schedule means taking into account many heavy constraints like employee contracts or minimal stang levels on the one hand and many global, difficult to formalize constraints like aspects of fairness on the other hand. Optimisation is quite difficult especially when fix rostering schemata cannot be used, e.g. because of frequently varying stang levels. In this paper we present how real-life employee scheduling problems can be solved by applying a Hybrid Genetic Algorithm that uses problem specific knowledge. First we briefly describe the given problem domain, then the idea and implementation of the Genetic Algorithm is presented. Finally we show some application results and the outlook

Rostering with a Hybrid Genetic Algorithm

Human workforce is an expensive resource and therefore should be used as efficient as possible. This optimization task is quite difficult especially in situations where staff members are different in their skills, qualifications or the details of their employment contracts, i.e. these constraints make the optimization of rosters a challenging and difficult task. In this paper we show how Genetic Algorithms combined with problem specific knowledge can be successfully applied to solve such scheduling and planning problems