Christopher Little results 27
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Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion te...
The influence of intrinsic ocean variability on coastal sea level remains largely unexplored but is of potential importance for emerging forecasting efforts. As in weather forecasts, intrinsic variability will amplify uncertainty in initial conditions. However, variability originating from intrinsic processes may be predictable in a forecast system with sufficient resolution and accurate initialization. Here, we examine the sp...
Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learningNARA Subscribed
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, th...
As human activity accelerates the global crisis facing wildlife populations, private land conservation provides an example of wildlife management challenges in social-ecological systems. This study reports on the research phase of ‘WildTracker’ - a co-created citizen science project, involving 160 landholders across three Tasmanian regions. This was a transdisciplinary collaboration between an environmental organisation, unive...
An experimental study of wet-cooking in organic vessels: implications for understanding the evolution of cooking technologiesNARA Subscribed
The ability to control and direct fire is a major evolutionary step in the human story. The development of aceramic cooking technologies is less well understood as they rarely survive in the archaeological record. However, inferential evidence such as fire-cracked rocks, earthen pits and heated bones suggest a variety of cooking methods were used prior to the invention of ceramics. Yet there is a paucity of experimental eviden...
A pathogenic deletion in Forkhead Box L1 (FOXL1) identifies the first otosclerosis (OTSC) geneNARA Subscribed
Otosclerosis is a bone disorder of the otic capsule and common form of late-onset hearing impairment. Considered a complex disease, little is known about its pathogenesis. Over the past 20 years, ten autosomal dominant loci ( OTSC1-10 ) have been mapped but no genes identified. Herein, we map a new OTSC locus to a 9.96 Mb region within the FOX gene cluster on 16q24.1 and identify a 15 bp coding deletion in Forkhead Box L1 co-s...
Greenland’s coastal margins are influenced by the confluence of Arctic and Atlantic waters, sea ice, icebergs, and meltwater from the ice sheet. Hundreds of spectacular glacial fjords cut through the coastline and support thriving marine ecosystems and, in some places, adjacent Greenlandic communities. Rising air and ocean temperatures, as well as glacier and sea-ice retreat, are impacting the conditions that support these sys...
The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previ...
Models of human dimensions of fisheries are important to understanding and predicting how fishing industries respond to changes in marine ecosystems and management institutions. Advances in computation have made it possible to construct agent‐based models (ABMs)—which explicitly describe the behaviour of individual people, firms or vessels in order to understand and predict their aggregate behaviours. ABMs are widely used for...
Geographic Variability of Sea-Level ChangeNARA Subscribed