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Osteoporosis, characterized by low bone mineral density (BMD) and increased fracture risk, is common yet underdiagnosed in older adults. Medications such as corticosteroids, levothyroxine, and antiepileptic drugs are well-documented contributors to BMD loss. This study examines how long-term use of these medications affects osteoporosis prevalence, specifically focusing on sex and age differences. This retrospective electronic...
Soil organic carbon (SOC) sequestration is vital for food security and climate mitigation. However, its long‐term response to fertilisation remains unclear. Using the 180‐year Broadbalk Experiment (the world's longest‐running fertilisation trial; Rothamsted, UK), combined with 14 C labelling and metagenomics, we identified fundamentally distinct mechanisms of SOC accumulation: a microbially mediated dual pathway under organic...
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...
An Integrated Modelling Framework to Determine Terrestrial Carbon Dioxide Removal via Enhanced Rock WeatheringNARA Subscribed
Enhanced rock weathering (ERW) is an emerging carbon dioxide removal (CDR) strategy that can support net‐zero emission targets. However, current ERW modelling efforts rely on assumptions that introduce substantial variation in CDR estimates across varying ecosystems and hydroclimatic conditions. They typically ignore or oversimplify plant–soil interactions and high‐frequency hydrological dynamics, obscuring short‐term weatheri...
Coastal managers worldwide must prepare for changes in annual wave overtopping events due to climate change and sea-level rise. Research often assesses overtopping discharges by extreme events at a sea wall crest, typically using data from physical models or empirical rules based on scaled experiments. Here, we analyse a unique 1-year field dataset of coastal wave overtopping, from SW England, to determine the number of indivi...
Seagrasses have been entwined with human culture for millennia, constituting a natural resource that has supported humanity throughout this history. Understanding the societal value of seagrass fosters appreciation of these ecosystems, encouraging conservation and restoration actions to counteract historic and predicted losses. This study overviews the plethora of seagrass use in human history, ranging from spiritual and cerem...
The Impact of Exposure Dosage and Host Genetics on the Shedding Kinetics of Flavobacterium psychrophilum in Rainbow TroutNARA Subscribed
Flavobacterium psychrophilum , the causative agent of bacterial cold water disease (BCWD), is one of the leading pathogens in rainbow trout ( Oncorhynchus mykiss ) aquaculture. To date, there is little knowledge of the transmission kinetics of F. psychrophilum over the course of infection. In particular, how transmission is affected by host genotype and pathogen exposure dosage are not well studied. In order to fill in these k...
Combining Observations and Models: A Review of the CARDAMOM Framework for Data‐Constrained Terrestrial Ecosystem ModelingNARA Subscribed
The rapid increase in the volume and variety of terrestrial biosphere observations (i.e., remote sensing data and in situ measurements) offers a unique opportunity to derive ecological insights, refine process‐based models, and improve forecasting for decision support. However, despite their potential, ecological observations have primarily been used to benchmark process‐based models, as many past and current models lack the c...
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...
Optimising Instrumented Mouthguard Data Analysis: Video Synchronisation Using a Cross-correlation ApproachNARA Subscribed
Purpose Head acceleration events (HAEs) are a growing concern in contact sports, prompting two rugby governing bodies to mandate instrumented mouthguards (iMGs). This has resulted in an influx of data imposing financial and time constraints. This study presents two computational methods that leverage a dataset of video-coded match events: cross-correlation synchronisation aligns iMG data to a video recording, by providing play...