52 research outputs found

    Doing Science: How to optimise patient and public involvement in your research

    Get PDF
    This paper considers how best to achieve patient and public involvement in research and how to get the most out of it http://ow.ly/R0hwV

    Doing Science: How to optimise patient and public involvement in your research

    Get PDF
    This paper considers how best to achieve patient and public involvement in research and how to get the most out of it http://ow.ly/R0hw

    Doing science: how to get credit for your scientific work.

    Get PDF
    Everyone deserves to be acknowledged for their efforts and contributions to a shared goal, and getting credit for your scientific work should be part of a natural process and should be fair and straightforward. However, credit cannot be objectively measured despite it having a big influence and, unfortunately, getting appropriate credit can occasionally be both complicated and challenging

    Transcriptional profiling of endobronchial ultrasound guided lymph node samples aids diagnosis of mediastinal lymphadenopathy

    Get PDF
    Background: Endobronchial ultrasound (EBUS) guided biopsy is the mainstay for investigation of mediastinal lymphadenopathy for laboratory diagnosis of malignancy, sarcoidosis or tuberculosis. However, improved methods for discriminating between tuberculosis and sarcoidosis and excluding malignancy are still needed. We sought to evaluate the role of genome-wide transcriptional profiling to aid diagnostic processes in this setting. Methods: Mediastinal lymph node samples from 88 individuals were obtained by EBUS guided aspiration for investigation of mediastinal lymphadenopathy and subjected to transcriptional profiling in addition to conventional laboratory assessments. Computational strategies were employed to evaluate the potential for using the transcriptome to distinguish between diagnostic categories. Results: Molecular signatures associated with granulomas or neoplastic and metastatic processes were clearly discernible in granulomatous and malignant lymph node samples respectively. Support vector machine (SVM) learning using differentially expressed genes showed excellent sensitivity and specificity profiles in receiver operating characteristic curve analysis with area under curve values >0.9 for discriminating between granulomatous and non-granulomatous disease, tuberculosis and sarcoidosis, and between cancer and reactive lymphadenopathy. A two-step decision tree using SVM to distinguish granulomatous and non-granulomatous disease, then between tuberculosis and sarcoidosis in granulomatous cases and between cancer and reactive lymphadenopathy in non-granulomatous cases achieved >90% specificity for each diagnosis and afforded greater sensitivity than existing tests to detect tuberculosis and cancer. In some diagnostically ambiguous cases computational classification predicted granulomatous disease or cancer before pathological abnormalities were evident. Conclusions: Machine learning analysis of transcriptional profiling in mediastinal lymphadenopathy may significantly improve the clinical utility of EBUS guided biopsies

    ERS International Congress 2023: highlights from the Thoracic Oncology Assembly

    Get PDF
    Lung cancer is the leading cause of cancer mortality in the world. It greatly affects the patients' quality of life, and is thus a challenge for the daily practice in respiratory medicine. Advances in the genetic knowledge of thoracic tumours' mutational landscape, and the development of targeted therapies and immune checkpoint inhibitors, have led to a paradigm shift in the treatment of lung cancer and pleural mesothelioma. During the 2023 European Respiratory Society Congress in Milan, Italy, experts from all over the world presented their high-quality research and reviewed best clinical practices. Lung cancer screening, management of early stages of lung cancer, application of artificial intelligence and biomarkers were discussed and they will be summarised here

    Migration von /sw vom AFS ins DCE/DFS

    Get PDF
    /sw ist eine verteilte Softwarebereitstellung mit dem Ziel, jedem Benutzer Software zentral zur Verfügung zu stellen, ohne daß er sich darum kümmern muß, woher er seine Software bekommt. Für eine Außenstehenden ergibt sich somit das Bild eines großen Softwarepools, aus dem er sich fertig installierte Software für seine Plattform herunterladen kann. Voraussetzung dafür ist, daß ein Benuzter an seiner Workstation über AFS (Andrew File System), DFS (Distributed File System) oder ftp verfügt. Zur Zeit werden vom /sw für 18 verschiedenen Unix-Plattformen 594 Programme in 1024 verschiedenen Installationen angeboten. Die meisten Architekturen vom /sw liegen im AFS, bis auf die Architekturen DEC ALPHA, IRIX 4.0 und Linux, die im NFS liegen. In Zukunft wird es für die gesamte /sw Software nur noch eine Quelle geben, das DFS. Mit der Migration von /sw aus dem AFS ins DFS entfällt dann die Trennung von /sw in einen AFS-Teil und einem NFS-Teil und damit auch der AFS/NFS-Translators, der recht unstabil läuft. Die gesamte Software von /sw wurde aus dem AFS bzw. NFS ins DFS migriert, so daß für alle vom /sw unterstützten Architekturen nur noch eine Quelle zur Verfügung steht, die Stuttgarter DCE-Zelle. Jeder AFS-Klient hat über den AFS/DFS-Translator Zugriff auf /sw und für die NFS-Klienten wird das /sw-Fi-lesystem exportiert, so daß jeder NFS-Klient die Möglichkeit hat das DFS-Filesystem /sw zu mounten. Eine Workstation kann sowohl AFS- als auch DCE/DFS-Klient sein
    corecore