Achieving Health Equity in Embedded Pragmatic Trials for People Living with Dementia and Their Family Caregivers

Embedded pragmatic clinical trials (ePCTs) advance research on Alzheimer's disease/Alzheimer's disease and related dementias (AD/ADRD) in real-world contexts; however, health equity issues have not yet been fully considered, assessed, or integrated into ePCT designs. Health disparity populations may not be well represented in ePCTs without special efforts to identify and successfully recruit sites of care that serve larger numbers of these populations. The National Institute on Aging (NIA) Imbedded Pragmatic Alzheimer's disease (AD) and AD-Related Dementias (AD/ADRD) Clinical Trials (IMPACT) Collaboratory's Health Equity Team will contribute to the overall mission of the collaboratory by developing and implementing strategies to address health equity in the conduct of ePCTs and ensure the collaboratory is a national resource for all Americans with dementia. As a first step toward meeting these goals, this article reviews what is currently known about the inclusion of health disparities populations of people living with dementia (PLWD) and their caregivers in ePCTs, highlights unique challenges related to health equity in the conduct of ePCTs, and suggests priority areas in the design and implementation of ePCTs to increase the awareness and avoidance of pitfalls that may perpetuate and magnify healthcare disparities

FOXA1 and adaptive response determinants to HER2 targeted therapy in TBCRC 036

Inhibition of the HER2/ERBB2 receptor is a keystone to treating HER2-positive malignancies, particularly breast cancer, but a significant fraction of HER2-positive (HER2+) breast cancers recur or fail to respond. Anti-HER2 monoclonal antibodies, like trastuzumab or pertuzumab, and ATP active site inhibitors like lapatinib, commonly lack durability because of adaptive changes in the tumor leading to resistance. HER2+ cell line responses to inhibition with lapatinib were analyzed by RNAseq and ChIPseq to characterize transcriptional and epigenetic changes. Motif analysis of lapatinib-responsive genomic regions implicated the pioneer transcription factor FOXA1 as a mediator of adaptive responses. Lapatinib in combination with FOXA1 depletion led to dysregulation of enhancers, impaired adaptive upregulation of HER3, and decreased proliferation. HER2-directed therapy using clinically relevant drugs (trastuzumab with or without lapatinib or pertuzumab) in a 7-day clinical trial designed to examine early pharmacodynamic response to antibody-based anti-HER2 therapy showed reduced FOXA1 expression was coincident with decreased HER2 and HER3 levels, decreased proliferation gene signatures, and increased immune gene signatures. This highlights the importance of the immune response to anti-HER2 antibodies and suggests that inhibiting FOXA1-mediated adaptive responses in combination with HER2 targeting is a potential therapeutic strategy

Recent developments in the modelling of radionuclide uptake, radiation dose and effects in wildlife

Of the ~600 scientific publications on the Fukushima event, more than 80% relate to themes of transport of radionuclides in environmental media, transfer to wildlife and foodstuffs, and dose to environmental receptors. This focus reflects a continued need for development and harmonisation of radiological modelling approaches such as has been underway through recent IAEA and ICRP initiatives (e.g. EMRAS I and II, MODARIA). Key developments in improving the understanding of uptake of radionuclides in wildlife include establishing the Wildlife Transfer Parameter Database and related IAEA handbook on transfer to wildlife. These sources provide access to a comprehensive collection of transfer parameters, including input from Australian sources (www.wildlifetransferdatabase.org). Key improvements were highlighted in a recent Journal of Environmental Radioactivity special issue (Vol. 121). Dose modelling for wildlife continues to be challenged by the high diversity of biotic types (plankton to whales) and the breadth of exposure scenarios in diverse ecosystems. Modelling codes (e.g. ERICA Tool, RESRAD-Biota) are undergoing updates of their transfer parameters, improvement of capabilities such as probabilistic analysis (e.g. Monte Carlo), and harmonization of approaches through IAEA model testing exercises (e.g., Little Forest Burial Ground biota dose modelling assessment). A recent development has been the use of voxel dosimetry approaches which build on the standard simplified ellipsoid approach by modelling the absorbed doses in individual organs. Recent improvements in defining dose effects to environmental receptors have focused on updating the FREDERICA Radiation Effects Database. The more comprehensive data have allowed for the updating/development of new Species Sensitivity Distributions that better support the benchmark values for potential dose effects, and for improving estimation of population effects (rather than individuals) upon which the environmental protection strategies are based

Batch Reinforcement Learning

Abstract Batch reinforcement learning is a subfield of dynamic programming-based reinforcement learning. Originally defined as the task of learning the best possible policy from a fixed set of a priori-known transition samples, the (batch) algorithms developed in this field can be easily adapted to the classical online case, where the agent interacts with the environment while learning. Due to the efficient use of collected data and the stability of the learning process, this research area has attracted a lot of attention recently. In this chapter, we introduce the basic principles and the theory behind batch reinforcement learning, describe the most important algorithms, exemplarily discuss ongoing research within this field, and briefly survey real-world applications of batch reinforcement learning.