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Background and aims Biological nitrogen fixation (BNF) supplies much of soybean ( Glycine max (L.) Merr.) nitrogen (N) demand, but reported fixation rates vary widely, leading to uncertainty in the soybean N cycle. We quantified whole-plant soybean BNF and N allocation using long-term 15 N labeling to assess whether BNF can offset grain N removal in a high-yielding system, and to quantify root contributions to fixed N. Methods...
This paper presents a flexible and efficient design method for optimizing the mooring systems of floating structures. Mooring system optimization is challenging because of the strong nonlinearity of mooring system behavior and the many technical constraints that must be satisfied. Furthermore, different mooring configurations can have very different design spaces. While some successful examples of mooring design optimization e...
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...
Local and Landscape‐Level Environmental Conditions Drive Habitat Selection Across Terrestrial Mammal SpeciesNARA Subscribed
Aim Animal movements are a fundamental process affecting communities and ecosystems. Quantifying habitat selection across species and habitats is key for understanding how animals respond to environmental change. Currently, we lack comparative studies that examine how habitat selection varies across species traits and landscapes. We aim to quantify global patterns of habitat selection to help understand the fundamental drivers...
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...
Local Adaptation in Climate Tolerance at a Small Geographic Scale Contrasts With Broad Latitudinal PatternsNARA Subscribed
While climate adaptation is typically quantified across broad gradients, the potential for adaptation to the same environmental variables at small scales is rarely tested. If local‐scale environmental heterogeneity can generate patterns of adaptation similar to broad gradients, then we currently underestimate adaptive capacity to global change. We quantified population variation in climate tolerance traits and their plasticity...
The sicker sex is plastic: Thermal plasticity determines sex biases in pathogen transmissionNARA Subscribed
Sex differences are predicted to play an important role in the spread and evolution of pathogens. However, attempts to generalize the “sicker” sex have been challenged by intraspecific variability of sex biases across the infection process. Sex‐specific plasticity provides a framework to resolve this by elucidating how infection is shaped at the sex‐pathogen‐environment interface. Using the Daphnia magna and Pasteuria ramosa s...
For nearly half a century, ecologists have sought to explain animal space use through characteristics of the environment (i.e., habitat). Recent evidence suggests animals also use memory of previous experiences to decide when and where to move. Yet, the relative influence of the two in explaining animal space use has not been resolved. Using six large ungulate species in the Rocky Mountains (USA), we evaluated the performance...
Microplastic pollution is ubiquitous in the oceans. However, little is known about the physiological impact of microplastics on corals, particularly under predicted future ocean conditions. This study investigated the individual impacts of microplastic exposure (MP) and predicted future ocean conditions [ocean acidification and warming (OAW)] as well as the combination of these stressors (OAW+MP) on the growth and physiology o...
Multi-centre normative brain mapping of intracranial EEG lifespan patterns in the human brainNARA Subscribed
Understanding healthy human brain function is crucial to identify and map pathological tissue within it. Whilst previous studies have mapped intracranial EEG (icEEG) from non-epileptogenic brain regions, they often neglect age and sex effects. Further, they are limited by small sample sizes due to the modality’s invasive nature. This study substantially expands the subject pool compared to existing literature, to create a mult...
Identifying high risk seafloor areas to bottom trawling in Aotearoa New Zealand to support marine spatial managementNARA Subscribed
Seafloor species play important ecological roles within marine ecosystems, yet many are vulnerable to the impacts of bottom fishing. Despite the known vulnerability of many seafloor taxa, destructive bottom fishing remains prevalent in many parts of the world given demand for wild-caught seafood. Species Distribution Models (SDMs) are increasingly used to estimate the distribution of vulnerable taxa and estimate possible risk...
Discovering a predictive metabolic signature of drug-induced structural cardiotoxicity in cardiac microtissuesNARA Subscribed
Improved prediction of drug-induced structural cardiotoxicity is required to reduce attrition driven by cardiac safety concerns in drug discovery. Omics measurements are well suited to this need, offering the potential to discover molecular signatures associated with toxicological endpoints. In addition, untargeted metabolomics can simultaneously measure xenobiotic fate within the test system. We present an extensive metabolom...
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...