Julie Bennett

Aug 17, 2024 | nature.com | Matthias Wagner |Khashayar Namdar |Julie Bennett |Liana Nobre |Uri Tabori |Cynthia Hawkins | +3 more

The use of targeted agents in the treatment of pediatric low-grade gliomas (pLGGs) relies on the determination of molecular status. It has been shown that genetic alterations in pLGG can be identified non-invasively using MRI-based radiomic features or convolutional neural networks (CNNs). We aimed to build and assess a combined radiomics and CNN non-invasive pLGG molecular status identification model. This retrospective study used the tumor regions, manually segmented from T2-FLAIR MR images, of 336 patients treated for pLGG between 1999 and 2018. We designed a CNN and Random Forest radiomics model, along with a model relying on a combination of CNN and radiomic features, to predict the genetic status of pLGG. Additionally, we investigated whether CNNs could predict radiomic feature values from MR images. The combined model (mean AUC: 0.824) outperformed the radiomics model (0.802) and CNN (0.764). The differences in model performance were statistically significant (p-values < 0.05). The CNN was able to learn predictive radiomic features such as surface-to-volume ratio (average correlation: 0.864), and difference matrix dependence non-uniformity normalized (0.924) well but was unable to learn others such as run-length matrix variance (− 0.017) and non-uniformity normalized (− 0.042). Our results show that a model relying on both CNN and radiomic-based features performs better than either approach separately in differentiating the genetic status of pLGGs, and that CNNs are unable to express all handcrafted features.

Jul 9, 2024 | nature.com | Nicholas Fernandez |Vijay Ramaswamy |Julie Bennett |Robert Siddaway |Uri Tabori

AbstractWith the success of immunotherapy in cancer, understanding the tumor immune microenvironment (TIME) has become increasingly important; however in pediatric brain tumors this remains poorly characterized. Accordingly, we developed a clinical immune-oncology gene expression assay and used it to profile a diverse range of 1382 samples with detailed clinical and molecular annotation.

Mar 25, 2024 | phcc.org.nz | Amanda Kvalsvig |John Potter |Mona Jeffreys |Julie Bennett

Covid-19 can cause longer-term changes in health, collectively known as Long Covid. With only four years of follow-up time to observe this evolving new virus we cannot yet see the full picture of Long Covid, but its impacts are already substantial and measurable in individuals, sectors, and societies. Evidence consistently shows that Long Covid is common, affects all ages, and frequently results in prolonged illness that can be disabling.

Oct 8, 2023 | onlinelibrary.wiley.com | Caroline Fyfe |Lucy Barnard |Philippa Howden-Chapman |Julie Bennett

1 INTRODUCTION Airbnb was launched in San Francisco in 2008, and operates as an international digital platform using a ‘peer to peer’ or ‘sharing economy’ business model (Crommelin et al., 2018; Li et al., 2019). Alongside similar but less well known online platforms like HomeAway and Bookings.com, Airbnb connects potential private hosts with visitors looking for short-term accommodation.

Aug 11, 2023 | wwwnc.cdc.gov | Jennifer Summers |Amanda Kvalsvig |Lucy Barnard |Julie Bennett

Mathieu  E, Ritchie  H, Rodés-Guirao  L, Appel  C, Gavrilov  D, Giattino  C, et al. Coronavirus pandemic (COVID-19) []. https://ourworldindata.org/coronavirusJha  P, Brown  PE, Ansumana  R. Counting the global COVID-19 dead. Lancet. 2022;399:1937–8. DOIPubMedGoogle ScholarSummers  J, Cheng  H-Y, Lin  H-H, Barnard  LT, Kvalsvig  A, Wilson  N, et al. Potential lessons from the Taiwan and New Zealand health responses to the COVID-19 pandemic. Lancet Reg Health West Pac. 2020;4:100044.