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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...
Waterfowl Move Less in Heterogeneous and Human‐Populated Landscapes, With Implications for Spread of Avian Influenza VirusesNARA Subscribed
Animal movements contribute to the spread of infectious diseases and are driven in part by environmental conditions. We investigated the links among the environment, animal movement, and infectious disease dynamics in waterfowl, which are among the primary wildlife hosts of avian influenza viruses. By combining telemetry data on 4606 individuals from 26 waterfowl species with data on land cover, weather, and vegetation, we fou...
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...
Evaluating models of expert judgment to inform assessment of ecosystem viability and collapseNARA Subscribed
Expert judgment underpins assessment of threatened ecosystems. However, experts are often narrowly defined, and variability in their judgments may be substantial. Models built from structured elicitation with large diverse expert panels can contribute to more consistent and transparent decision‐making. We conducted a structured elicitation under a broad definition of expertise to examine variation in judgments of ecosystem via...
Environmental DNA (eDNA) is frequently used to infer distributions of microorganisms in Antarctica. Their distributions relative to environmental variables are, in turn, sometimes used to infer their physiological range (and a relationship between the two is generally assumed for conservation purposes). We sought to determine whether ecological inferences based on distributions accurately reflect tolerances of the organisms co...
The distinctive weathering crust habitat of a High Arctic glacier comprises discrete microbial micro‐habitatsNARA Subscribed
Sunlight penetrates the ice surfaces of glaciers and ice sheets, forming a water‐bearing porous ice matrix known as the weathering crust. This crust is home to a significant microbial community. Despite the potential implications of microbial processes in the weathering crust for glacial melting, biogeochemical cycles, and downstream ecosystems, there have been few explorations of its microbial communities. In our study, we us...
Identifying threatened ecosystem types is fundamental to conservation and management decision‐making. When identification relies on expert judgment, decisions are vulnerable to inconsistent outcomes and can lack transparency. We elicited judgements of the occurrence of a widespread, critically endangered Australian ecosystem from a diverse pool of 83 experts. We asked 4 questions. First, how many experts are required to reliab...
Uncertain role of clouds in shaping summertime atmosphere-sea ice connections in reanalyses and CMIP6 modelsNARA Subscribed
Downwelling longwave radiation (DLR) driven by the atmospheric and cloud conditions in the troposphere is suggested to be a dominant factor to determine the summertime net surface energy budget over the Arctic Ocean and thus plays a key role to shape the September sea ice. We use reanalyses and the self-organizing map (SOM) method to distinguish CMIP6 model performance in replicating the observed strong atmosphere-DLR connecti...
The Impact of Sleep-Wake Behaviour on Tennis Match Performance in Junior State Grade Tennis PlayersNARA Subscribed
Purpose To date, no study has investigated the extent to which sleep-wake behaviour (SWB) influences match performance in junior tennis players. This study aimed to assess the influence of SWB for the week and night before on match performance, particularly match analytics and activity. Methods This study recruited 10 junior state grade tennis players who wore an actigraphy device and completed a sleep diary for the week befor...
Extensive regional variation in the phenology of insects and their response to temperature across N orth A mericaNARA Subscribed
Climate change models often assume similar responses to temperatures across the range of a species, but local adaptation or phenotypic plasticity can lead plants and animals to respond differently to temperature in different parts of their range. To date, there have been few tests of this assumption at the scale of continents, so it is unclear if this is a large‐scale problem. Here, we examined the assumption that insect taxa...
Our ability to predict sandy shoreline evolution resulting from future changes in regional wave climates is critical for the sustainable management of coastlines worldwide. To this end, the present generation of simple and efficient semi-empirical shoreline change models have shown good skill at predicting shoreline changes from seasons up to several years at a number of diverse sites around the world. However, a key limitatio...
There is an increasing interest in the broad-scale implementation of coastal erosion early warning systems (EWS) with the goal of enhancing community preparedness to extreme coastal storm wave events. These emerging systems typically rely on process-based models to predict the storm-induced morphological change. A key challenge with incorporating these models in EWSs is the need for up-to-date nearshore and surf zone bathymetr...