Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegeneration - Nikhil N. Chaudhari; Owen M. Vega; Phoebe Imms; Jaron M. Kawamura; Nahian F. Chowdhury; Tamara Jafar; Andrei Irimia; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; et al. (GeroScience, 2026)
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 find aging-related structural alterations above and beyond cortical thickness and atrophy. Using a novel approach to DNN interpretability, we mapped brain aging progression in 25,539 cognitively normal UK Biobank adults aged 45–83 years. Cortical aging is found to involve anatomic features becoming prominent during the 50s within frontolateral, mesolimbic, cuneal, and occipitotemporal regions. From these foci, aging-related features propagate to adjacent areas at rates peaking in the 60s. Cortical thinning and atrophy do not trend closely with neurodegeneration, but important DNN-identifiable anatomic features have spatiotemporal dynamics that match those of amyloid or tau. Our results challenge the assumption that MRI cannot map anatomic features trending with neurodegeneration. Interpretable DNNs can empower MRI to quantify anatomic aging as a process of spatial feature expansion from focal regions into nearby structures in the sequence of neurodegenerative pathology. Traditional morphometrics explain only ∼1% of variance in DNN-identifiable features, which clarifies why the former are insensitive to anatomic changes involving neurodegeneration. Our results conceptualize brain aging in the context of spatial and temporal parallels between anatomic senescence and neuropathology. These findings may help to map cognitively normal adults’ neurodegenerative anatomy even without PET measurements. Graphical Abstract

SNAPSHOT USA 2024: Year 6 of the Coordinated National Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Daniel J. Herrera; Camilla Price; Phuong‐Thao Nguyen‐Nu; Katrina Adamczyk; Peter D. Alexander; David Allen; Jesse M. Alston; Diego F. Alvarado‐Serrano; et al. (Global Ecology and Biogeography, 2026)
Motivation SNAPSHOT USA is an annual, multi‐contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2024 comprises two .csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.

Sex and APOE genotype specific brain regional vulnerability to Alzheimer's Disease - Qi Zeng; Minghui Wang; Erming Wang; Xianxiao Zhou; Peng Xu; Vahram Haroutunian; Dongming Cai; Bin Zhang; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; et al. (GeroScience, 2026)
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 tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI), and regional vulnerability was assessed with a composite vulnerability score (CVS) derived from associations between diffusion features and AD severity across clinical traits in each of the four sex-APOE groups (female or male, with or without APOE4). Brain parcellation with the Eve atlas revealed regions consistently affected across sex-APOE groups (e.g., parahippocampal and superior temporal gyri) and regions specific to individual groups (e.g., the cingulum in females with APOE4 and the middle frontal gyrus in males without APOE4). Gene co-expression network analysis of the matched blood expression data identified gene subnetworks linked to group-specific regional vulnerability, including a muscle tissue morphogenesis module regulated by NEURL1B and HIST1H2BN associated with middle frontal gyrus vulnerability. These findings demonstrate that sex and APOE genotype jointly shape region-specific WM vulnerability and its molecular signatures in AD. Understanding these interactions provides novel mechanistic insights and may inform precision approaches to drug development, biomarker discovery, and clinical trial design for AD.

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning - Marthe Mieling; Mushfa Yousuf; Nico Bunzeck; Michael Weiner; Paul Aisen; Ronald Petersen; Clifford R. Jack; William Jagust; Susan Landau; Monica Rivera-Mindt; Leslie M. Shaw; Edward B. Lee; et al. (GeroScience, 2025)
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, those with mild cognitive impairment (MCI) and AD dementia patients. Features included structural MRI, CSF status, demographics, and genetic data. Analyses comprised one cross-sectional multi-class classification (CN vs. MCI vs. AD dementia, n = 568) and two longitudinal binary-class classifications (CN-to-MCI converters vs. CN stable, n = 92; MCI-to-AD converters vs. MCI stable, n = 378). All classifications achieved 70–77% accuracy and 61–83% precision. Key features were CSF status, hippocampal volume, entorhinal thickness, and amygdala volume, with a clear dissociation: hippocampal properties contributed to the conversion to MCI, while the entorhinal cortex characterized the conversion to AD dementia. The findings highlight explainable, trajectory-specific insights into AD progression.

Three Pillars of Recovery After Aneurysmal Subarachnoid Hemorrhage: A Narrative Review - Dylan Ryan; Salman Ikramuddin; Sheila Alexander; Christine Buckley; Wuwei Feng (Translational Stroke Research, 2025)

Propranolol or Beta-Blockers for Cerebral Cavernous Malformation: a Systematic Review and Meta-analysis of Literature in Both Preclinical and Clinical Studies - Salman Ikramuddin; Shimeng Liu; Dylan Ryan; Sara Hassani; David Hasan; Wuwei Feng (Translational Stroke Research, 2024)

Mechanochemical degradation of per- and polyfluoroalkyl substances in soil using an industrial-scale horizontal ball mill with comparisons of key operational metrics - Nicholas Battye; David Patch; Iris Koch; Ryan Monteith; Dylan Roberts; Natalia O'Connor; Bernard Kueper; Michael Hulley; Kela Weber (Science of The Total Environment, 2024)

Phytoplankton composition from sPACE: Requirements, opportunities, and challenges - Ivona Cetinić; Cecile S. Rousseaux; Ian T. Carroll; Alison P. Chase; Sasha J. Kramer; P. Jeremy Werdell; David A. Siegel; Heidi M. Dierssen; Dylan Catlett; Aimee Neeley; Inia M. Soto Ramos; Jennifer L. Wolny; et al. (Remote Sensing of Environment, 2024)

Finding Promising Candidates for Wet Growing Conditions: The Effect of Two Row Spacings on Biomass Production of Four Bioenergy Prairie Cordgrass Populations in a Wet Marginal Land - Santanu Thapa; Kayla M. Vittore; Dylan P. Allen; Jia Guo; Ryan A. Boyd; Moon-Sub Lee; D. K. Lee (BioEnergy Research, 2023)

Rebuilding A Collapsed Bivalve Population, Restoring Seagrass Meadows, and Eradicating Harmful Algal Blooms In A Temperate Lagoon Using Spawner Sanctuaries - Christopher J. Gobler; Michael H. Doall; Bradley J. Peterson; Craig S. Young; Flynn DeLaney; Ryan B. Wallace; Stephen J. Tomasetti; Timothy P. Curtin; Brooke K. Morrell; Elizabeth M. Lamoureux; Berry Ueoka; Andrew W. Griffith; et al. (Frontiers in Marine Science, 2022)
During the past century, bivalve populations across the globe have collapsed, resulting in negative ecosystem consequences due to their outsized impact on shallow estuaries. In response, there has been strong interest in the restoration of marine bivalve populations. Here, we present a decade-long restoration effort that sought to rebuild a collapsed (99.5% reduction in harvest) and recruitment-limited population of hard clams ( Mercenaria mercenaria ) in Shinnecock Bay, NY, USA, using spawner sanctuaries: no-harvest zones where adults were planted at high densities (~27 m- 2 ). Between 2012 to 2019, more than 3.2 million clams were planted in 64 discrete sanctuary plots (~1,850 m 2 each) located in zones with maximal larval retention and sediment and seawater characteristics that would maximize the conditioning and spawning of adults. Hydrodynamic models, quantification of hard clam larvae, and spatial recruitment patterns demonstrated larvae spawned within sanctuaries were transported to regions where clam densities significantly increased 18-fold over seven years (2015-2021; p <0.001) and harvests significantly increased more than 16-fold over nine years (2012-2021; p <0.0001). Increases in populations and harvests were caused by smaller clams recruited within the time frame of the creation of spawner sanctuaries. Higher clam densities caused biological filtration times of the bay to decrease from up to three months at the start of the project to as low as 10 days in 2021. Concurrently, concentrations of the harmful brown tide alga, Aureococcus anophagefferens , and chlorophyll a significantly decreased ( p <0.005) while water clarity and the extent of seagrass beds significantly increased ( p <0.05). Increases in clam landings and improvements in water quality were not observed in adjacent lagoonal estuaries where restoration did not occur. Given these outcomes and the global need for rebuilding marine life, the implementation of spawner sanctuaries using the criteria set forth herein may be a promising approach for restoring hard clam and other bivalve populations in estuaries elsewhere.

Sex and Size Influence the Spatiotemporal Distribution of White Sharks, With Implications for Interactions With Fisheries and Spatial Management in the Southwest Indian Ocean - Alison A. Kock; Amanda T. Lombard; Ryan Daly; Victoria Goodall; Michael Meÿer; Ryan Johnson; Chris Fischer; Pieter Koen; Dylan Irion; Enrico Gennari; Alison Towner; Oliver J. D. Jewell; et al. (Frontiers in Marine Science, 2022)
Human activities in the oceans increase the extinction risk of marine megafauna. Interventions require an understanding of movement patterns and the spatiotemporal overlap with threats. We analysed the movement patterns of 33 white sharks ( Carcharodon carcharias ) satellite-tagged in South Africa between 2012 and 2014 to investigate the influence of size, sex and season on movement patterns and the spatial and temporal overlap with longline and gillnet fisheries and marine protected areas (MPAs). We used a hidden Markov model to identify ‘resident’ and ‘transient’ movement states and investigate the effect of covariates on the transition probabilities between states. A model with sex, total length and season had the most support. Tagged sharks were more likely to be in a resident state near the coast and a transient state away from the coast, while the probability of finding a shark in the transient state increased with size. White sharks moved across vast areas of the southwest Indian Ocean, emphasising the need for a regional management plan. White sharks overlapped with longline and gillnet fisheries within 25% of South Africa’s Exclusive Economic Zone and spent 15% of their time exposed to these fisheries during the study period. The demersal shark longline fishery had the highest relative spatial and temporal overlap, followed by the pelagic longline fishery and the KwaZulu-Natal (KZN) shark nets and drumlines. However, the KZN shark nets and drumlines reported the highest white shark catches, emphasising the need to combine shark movement and fishing effort with reliable catch records to assess risks to shark populations accurately. White shark exposure to shark nets and drumlines, by movement state, sex and maturity status, corresponded with the catch composition of the fishery, providing support for a meaningful exposure risk estimate. White sharks spent significantly more time in MPAs than expected by chance, likely due to increased prey abundance or less disturbance, suggesting that MPAs can benefit large, mobile marine megafauna. Conservation of white sharks in Southern Africa can be improved by implementing non-lethal solutions to beach safety, increasing the observer coverage in fisheries, and continued monitoring of movement patterns and existing and emerging threats.

A Numerical Study of Sheet Flow Driven by Skewed-Asymmetric Shoaling Waves Using SedWaveFoam - Yeulwoo Kim; Ryan S. Mieras; Dylan Anderson; Timu Gallien (Journal of Marine Science and Engineering, 2021)
SedWaveFoam, an OpenFOAM-based two-phase model that concurrently resolves the free surface wave field, and the bottom boundary layer is used to investigate sediment transport throughout the entire water column. The numerical model was validated with large-scale wave flume data for sheet flow driven by shoaling skewed-asymmetric waves with two different grain sizes. Newly obtained model results were combined with previous nonbreaking and near-breaking wave cases to develop parameterization methods for time-dependent bed shear stress and sediment transport rate under various sediment sizes and wave conditions. Gonzalez-Rodriguez and Madsen (GRM07) and quasi-steady approaches were compared for intra-wave bed shear stress. The results show that in strongly asymmetric flows, considering the separated boundary layer development processes at each half wave-cycle (i.e., GRM07) is essential to accurately estimating bed shear stress and highlights the impact of phase-lag effects on sediment transport rates. The quasi-steady approach underpredicts (∼60%) sediment transport rates, especially for fine grains under large velocity asymmetry. A modified phase-lag parameter, incorporating velocity asymmetry, sediment stirring, and settling processes is proposed to extend the Meyer-Peter and Mueller type power law formula. The extended formula accurately estimated the enhanced net onshore sediment transport rate observed under skewed-asymmetric wave conditions.

Genetics of resistance in lettuce to races 1 and 2 of Verticillium dahliae from different host species - German V. Sandoya; Suraj Gurung; Dylan P. Short; Krishna V. Subbarao; Richard W. Michelmore; Ryan J. Hayes (Euphytica, 2017)