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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...
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...
Genetic toxicity testing assesses the potential of compounds to cause DNA damage. There are many genetic toxicology screening assays designed to assess the DNA damaging potential of chemicals in early drug development aiding the identification of promising drugs that have low-risk potential for causing genetic damage contributing to cancer risk in humans. Despite this, in vitro tests generate a high number of misleading positi...
Global mercury concentrations in biota: their use as a basis for a global biomonitoring frameworkNARA Subscribed
An important provision of the Minamata Convention on Mercury is to monitor and evaluate the effectiveness of the adopted measures and its implementation. Here, we describe for the first time currently available biotic mercury (Hg) data on a global scale to improve the understanding of global efforts to reduce the impact of Hg pollution on people and the environment. Data from the peer-reviewed literature were compiled in the G...
Inter-laboratory automation of the in vitro micronucleus assay using imaging flow cytometry and deep learningNARA Subscribed
The in vitro micronucleus assay is a globally significant method for DNA damage quantification used for regulatory compound safety testing in addition to inter-individual monitoring of environmental, lifestyle and occupational factors. However, it relies on time-consuming and user-subjective manual scoring. Here we show that imaging flow cytometry and deep learning image classification represents a capable platform for automat...
Ocean seascapes predict distant‐water fishing vessel incursions into exclusive economic zonesNARA Subscribed
Many of the world's most important fisheries are experiencing illegal, unreported and unregulated (IUU) fishing, thereby undermining efforts to sustainably conserve and manage fish stocks. A major challenge to ending IUU fishing is improving our ability to identify whether a vessel is fishing illegally and where illegal fishing is likely to occur in the ocean. However, monitoring the oceans is costly, time‐consuming, and logis...
The Maximum Entropy Theory of Ecology (METE) predicts the shapes of macroecological metrics in relatively static ecosystems, across spatial scales, taxonomic categories and habitats, using constraints imposed by static state variables. In disturbed ecosystems, however, with time‐varying state variables, its predictions often fail. We extend macroecological theory from static to dynamic by combining the MaxEnt inference procedu...
Motivation The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community‐led open‐source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal...
Building up biogeography: Pattern to processNARA Subscribed
Linking pattern to process across spatial and temporal scales has been a key goal of the field of biogeography. In January 2017, the 8th biennial conference of the International Biogeography Society sponsored a symposium on Building up biogeography—process to pattern that aimed to review progress towards this goal. Here we present a summary of the symposium, in which we identified promising areas of current research and sugges...
The mechanistic origin and shape of body‐size distributions within communities are of considerable interest in ecology. A recently proposed light‐limitation model provides a good fit to the distribution of tree sizes in a tropical forest plot. The maximum entropy theory of ecology (METE) also predicts size distributions, but without explicit mechanistic assumptions, and thus its predictions should hold in ecosystems generally,...
We extend macroecological theory based on the maximum entropy principle from species level to higher taxonomic categories, thereby predicting distributions of species richness across genera or families and the dependence of abundance and metabolic rate distributions on taxonomic tree structure. Predictions agree with qualitative trends reported in studies on hyper‐dominance in tropical tree species, mammalian body size distrib...
Aim The recently proposed maximum entropy theory of ecology predicts that all nested species–area relationships ( SARs ) will collapse to a single, universal curve that exhibits a decreasing log–log slope with increasing scale, suggesting that the power law form of the SAR is invalid at any scale. In this analysis we test the generality of this scale collapse behaviour and determine the scale at which approximate power law beh...
Predicting extinction debt from community patternsNARA Subscribed
A significant challenge in both measuring and predicting species extinction rates at global and local scales is the possibility of extinction debt, time‐delayed extinctions that occur gradually following an initial impact. Here we examine how relative abundance distributions and spatial aggregation combine to influence the likely magnitude of future extinction debt following habitat loss or climate‐driven range contraction. Ou...
Ecosystem responses to climate change can exert positive or negative feedbacks on climate, mediated in part by slow‐moving factors such as shifts in vegetation community composition. Long‐term experimental manipulations can be used to examine such ecosystem responses, but they also present another opportunity: inferring the extent to which contemporary climate change is responsible for slow changes in ecosystems under ambient...
Empirical tests of within‐ and across‐species energetics in a diverse plant communityNARA Subscribed
Many fundamental properties of ecological systems and interactions are tied to body size and a related metric, the metabolic rate distribution, both within and across species. A previously proposed maximum entropy theory of ecology (METE) predicts numerous interrelated macroecological patterns, including spatial distributions of individuals within species, abundance distributions across species, species area relationships, and...
Responses of high‐altitude graminoids and soil fungi to 20 years of experimental warmingNARA Subscribed
High‐elevation ecosystems are expected to be particularly sensitive to climate warming because cold temperatures constrain biological processes. Deeper understanding of the consequences of climate change will come from studies that consider not only the direct effects of temperature on individual species, but also the indirect effects of altered species interactions. Here we show that 20 years of experimental warming has chang...
The shape of a species' spatial abundance distributionNARA Subscribed
Aim The shape of a species' spatial abundance distribution may change with spatial scale. We predict that the shape will typically change from strictly downward‐sloping (falling) to humped (rising then falling) as the spatial scale increases. The prediction, motivated in part by central limit reasoning, is intended for common or abundant species over reasonably homogeneous habitats. We test the prediction using data on 800+ tr...
Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and timeNARA Subscribed
Ecology Letters (2011) Abstract Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site‐specificity of results and uncertainty about the power of short‐term...