Historical Documents of the Irish Avant-Garde

The contributors who wrote the texts and scores are: John Berndt, Felicity Ford, Panos Ghikas, Paul Gilgunn, Stephen Graham, Majella Munro, Simon O’Connor, Rían O’Rahallaigh, Nick Roth, Benedict Schlepper-Connolly, Jennifer Walshe. Thanks very much to Richard Devine for his recordings which brought Zaftig to life and Jack McMahon for his performance as Ultan O’Farrell, and to Malcolm Tyrrell for his dream of an episode of Hands focussing on Irish performance art.Before you begin reading the articles in this book and listening to the recordings on the Aisteach Foundation’s website, I have a confession to make – all of the composers and artists are fictional. The Aisteach Foundation and the Historical Documents of the Irish Avant-Garde are a communal thought experiment, a revisionist exercise in “what if?”, a huge effort by many people to create an alternative history of avant-garde music in Ireland, to write our ancestors into being and shape their stories with care. We played fast and loose with history and the truth and we like to think Flann O’Brien would have approved. I am extremely grateful to the Arts Council of Ireland for funding this project and allowing me to collaborate with the contributors listed below. If you feel there’s something we missed, something you want to have happened and would like to bring into being, please let us know. This project is dedicated with love to Bob Gilmore. Dr. Jennifer Walshe, President, Aisteach FoundationArts Council of Irelandhttp://www.lulu.com/shop/http://www.lulu.com/shop/jennifer-walshe/historical-documents-of-the-irish-avant-garde/paperback/product-22906851.html#productDetail

Predictions for the future of kallikrein-related peptidases in molecular diagnostics

Kallikrein-related peptidases (KLKs) form a cancer-related ensemble of serine proteases. This multigene family hosts the most widely used cancer biomarker that is PSA-KLK3, with millions of tests performed annually worldwide. The present report provides an overview of the biomarker potential of the extended KLK family (KLK1-KLK15) in various disease settings and envisages approaches that could lead to additional KLK-driven applications in future molecular diagnostics. Particular focus is given on the inclusion of KLKs into multifaceted cancer biomarker panels that provide enhanced diagnostic, prognostic and/or predictive accuracy in several human malignancies. Such panels have been described so far for prostate, ovarian, lung and colorectal cancers. The role of KLKs as biomarkers in non-malignant disease settings, such as Alzheimer’s disease and multiple sclerosis, is also commented upon. Predictions are given on the challenges and future directions regarding clinically oriented KLK research

Historical documents of the Irish avant-garde

Album, book publication and website curated by Jennifer Walshe and funded by the Irish Arts Council. The album features work composed improvised and performed by Panos Ghikas, Nick Roth and Jennifer Walshe and is available on Migro Records. Produced by Panos Ghikas

Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer

Classifying indolent prostate cancer represents a significant clinical challenge. We investigated whether integrating data from different omic platforms could identify a biomarker panel with improved performance compared to individual platforms alone. DNA methylation, transcripts, protein and glycosylation biomarkers were assessed in a single cohort of patients treated by radical prostatectomy. Novel multiblock statistical data integration approaches were used to deal with missing data and modelled via stepwise multinomial logistic regression, or LASSO. After applying leave‐one‐out cross‐validation to each model, the probabilistic predictions of disease type for each individual panel were aggregated to improve prediction accuracy using all available information for a given patient. Through assessment of three performance parameters of area under the curve (AUC) values, calibration and decision curve analysis, the study identified an integrated biomarker panel which predicts disease type with a high level of accuracy, with Multi AUC value of 0.91 (0.89, 0.94) and Ordinal C‐Index (ORC) value of 0.94 (0.91, 0.96), which was significantly improved compared to the values for the clinical panel alone of 0.67 (0.62, 0.72) Multi AUC and 0.72 (0.67, 0.78) ORC. Biomarker integration across different omic platforms significantly improves prediction accuracy. We provide a novel multiplatform approach for the analysis, determination and performance assessment of novel panels which can be applied to other diseases. With further refinement and validation, this panel could form a tool to help inform appropriate treatment strategies impacting on patient outcome in early stage prostate cancer