Rationale for tau aggregation inhibitor therapy in Alzheimer's disease and other tauopathies

Preprin

Tau Aggregation Inhibitor Therapy : An Exploratory Phase 2 Study in Mild or Moderate Alzheimer's Disease

ACKNOWLEDGMENTS We thank patients and their caregivers for their participation in the study and are indebted to all the investigators involved in the study, particularly Drs. Douglas Fowlie and Donald Mowat for their helpful contributions to the clinical execution of the study in Scotland. We thank Sharon Eastwood, Parexel, for assistance in preparing initial drafts of the manuscript. We acknowledge constructive comments provided by Professors G. Wilcock and S. Gauthier on drafts of the article. CMW, CRH, and JMDS are officers of, and hold beneficial interests in, TauRx Therapeutics. RTS, PB, KK, and DJW are paid consultants to TauRx Therapeutics. The study was financed entirely by TauRx TherapeuticsPeer reviewedPublisher PD

Tau-aggregation inhibitor therapy for Alzheimer's disease

Article Accepted Date: 9 December 2013 Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.Peer reviewedPublisher PD

On the path to AI

This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data

On the path to AI

This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age—prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, explainability, and biased data

NUMFabric: Fast and Flexible Bandwidth Allocation in Datacenters

We present xFabric, a novel datacenter transport design that provides flexible and fast bandwidth allocation control. xFabric is flexible: it enables operators to specify how bandwidth is allocated amongst contending flows to optimize for different service-level objectives such as minimizing flow completion times, weighted allocations, different notions of fairness, etc. xFabric is also very fast, it converges to the specified allocation one-to-two order of magnitudes faster than prior schemes. Underlying xFabric, is a novel distributed algorithm that uses in-network packet scheduling to rapidly solve general network utility maximization problems for bandwidth allocation. We evaluate xFabric using realistic datacenter topologies and highly dynamic workloads and show that it is able to provide flexibility and fast convergence in such stressful environments.Google Faculty Research Awar

Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia

Acknowledgments We would like to acknowledge the support of the Maxwell compute cluster funded by the University of Aberdeen. We also gratefully acknowledge study investigators and the generosity of study participants.Peer reviewedPublisher PD

Cellular Models of Aggregation-Dependent Template-Directed Proteolysis to Characterize Tau Aggregation Inhibitors for Treatment of Alzheimer's Disease

Copyright © 2015, The American Society for Biochemistry and Molecular Biology. Acknowledgements-We thank Drs Timo Rager and Rolf Hilfiker (Solvias, Switzerland) for polymorph analyses.Peer reviewedPublisher PD