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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...
Background The root cortex in Poaceae is a diverse, dynamic, and dispensable composite layer of tissue. Early in plant growth, the cortex in Poaceae roots primarily consists of parenchyma cells. However, as the root continues to develop, while encountering varying environmental conditions, the cortex undergoes substantial structural and functional changes. These modifications involve either cell wall modifications or programme...
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...
Repurposing FDA-approved drugs as inhibitors of therapy-induced invadopodia activity in glioblastoma cellsNARA Subscribed
Glioblastoma (GBM) is the most prevalent primary central nervous system tumour in adults. The lethality of GBM lies in its highly invasive, infiltrative, and neurologically destructive nature resulting in treatment failure, tumour recurrence and death. Even with current standard of care treatment with surgery, radiotherapy and chemotherapy, surviving tumour cells invade throughout the brain. We have previously shown that this...
The 2004 Indian Ocean tsunami led to improvements in Thailand’s early warning systems and evacuation procedures. However, there was no consideration of better aid delivery, which critically depends on estimates of the affected population. With the widespread use of geographical information systems (GIS), there has been renewed interest in spatial population estimation. This study has developed an application to determine the n...
Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates f...
Extreme weather events have become a dominant feature of the narrative surrounding changes in global climate with large impacts on ecosystem stability, functioning and resilience; however, understanding of their risk of co‐occurrence at the regional scale is lacking. Based on the UK Met Office’s long‐term temperature and rainfall records, we present the first evidence demonstrating significant increases in the magnitude, direc...
Temporal and spatial influences incur reconfiguration of A rctic heathland soil bacterial community structureNARA Subscribed
Summary Microbial responses to A rctic climate change could radically alter the stability of major stores of soil carbon. However, the sensitivity of plot‐scale experiments simulating climate change effects on A rctic heathland soils to potential confounding effects of spatial and temporal changes in soil microbial communities is unknown. Here, the variation in heathland soil bacterial communities at two survey sites in S wede...
Terrestrial gross primary production inferred from satellite fluorescence and vegetation modelsNARA Subscribed
Determining the spatial and temporal distribution of terrestrial gross primary production (GPP) is a critical step in closing the Earth's carbon budget. Dynamical global vegetation models (DGVMs) provide mechanistic insight into GPP variability but diverge in predicting the response to climate in poorly investigated regions. Recent advances in the remote sensing of solar‐induced chlorophyll fluorescence (SIF) opens up a new po...
Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomesNARA Subscribed
Whether climate change will turn cold biomes from large long‐term carbon sinks into sources is hotly debated because of the great potential for ecosystem‐mediated feedbacks to global climate. Critical are the direction, magnitude and generality of climate responses of plant litter decomposition. Here, we present the first quantitative analysis of the major climate‐change‐related drivers of litter decomposition rates in cold no...
Using metabolic fingerprinting of plants for evaluating nitrogen deposition impacts on the landscape levelNARA Subscribed
Nitrogen emissions and atmospheric deposition are globally significant with the potential to alter ecosystem nutrient balance, provoking changes in vegetation composition. Shifts in plant biochemistry are good indicators of nitrogen pollution and have been used to monitor vegetation health. Fourier transform‐infrared (FT‐IR) spectroscopy has previously been shown to be a rapid and relatively inexpensive method for evaluating l...