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Tracing spatial mid-size Eastern U.S. cities road dust pollution: insights from source apportionment and health risk assessmentNARA Subscribed
As urban areas expand in eastern USA, the convergence of historical and modern anthropogenic source inputs has resulted in a complex geochemical signature of road dust pollution, while representing a critical public health issue for communities. In this study, road dust collected at seven (7) cities in eastern USA was analyzed for 11 potential toxic elements (PTEs, e.g., Cu, Zn, As, Se, Ni, Fe, Mo, V, Co, Cd, Pb) and examined...
Global patterns and regional insights into kelp forest protection, restoration, and stewardshipNARA Subscribed
Kelp forests are among the most extensive and productive coastal ecosystems, yet they remain underrepresented in global conservation policy despite widespread declines driven by interacting global- (i.e., ocean warming, marine heatwaves) to local-scale stressors. At the same time, kelp conservation and restoration efforts are expanding rapidly across regions, but measures of success and syntheses tend to primarily focus on eco...
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...
Dehydrating microhabitats increase mite activity and intensify ectoparasitism of DrosophilaNARA Subscribed
Parasites interact with their host in variable environments that are often subject to water scarcity and dehydration. Drosophilid fruit flies and associated ectoparasitic mites interact across a range of microhabitats, typically in decaying organic matter, such as fallen fruit and cactus tissue, that dries out and deteriorates over periods ranging from days to months. Here, we report that mite parasitism of Drosophila increase...
Identification of Ischemic Stroke Patients Based on Plasma Concentrations of Extracellular VesiclesNARA Subscribed
Patients presenting with stroke symptoms suffer from either ischemic stroke, hemorrhagic stroke, transient ischemic attacks (TIA), or “stroke mimics,” which include benign headaches, epilepsy, and vestibular disorders. As ischemic and hemorrhagic stroke patients require different medical treatments, early identification of the underlying cause of symptoms is essential for tailored and urgent medical intervention. This study in...
Activating transcription factor 4 (ATF4) is a transcription factor that mediates the response to stress at the cellular, tissue, and organism level. We deleted the gene encoding ATF4 in the proximal tubules of the mouse kidney by using a temporal and cell type-specific approach. We show that ATF4 plays a major role in regulating the transcriptome and proteome, which, in turn, influences the metabolome and kidney functions. Gen...
Using multiple sources, we provide the conceptual justification and statistical support for a multimorbidity outcome associated with obesity-related conditions, which we term the Health Conditions Index (HCI). This index was designed to capture the health effects of multi-year studies of caloric restriction for older adults with BMIs in the overweight or obesity classification. We used a subset of participants in the Health, A...
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...