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

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.

Turtles and turnarounds: Small animal exclusion fencing effectively reduces turtle road mortality - Tricia M. Markle; Christopher E. Smith; Seth P. Stapleton (Biological Conservation, 2026)

Habitat fidelity in hawksbill sea turtles - Andrew S. Maurer; Julia A. Horrocks; Claudio Bellini; Karen L. Eckert; Alexandra L. Fireman; Mariana M. P. B. Fuentes; Barry Krueger; Kathryn E. Levasseur; Maria A. Marcovaldi; Renata M. A. Ramos; Seth P. Stapleton; Hannah B. Vander Zanden; et al. (Ecology, 2025)
Climate change is altering habitat suitability and driving shifts in species distributions. To understand potential responses by mobile animals, it is essential to assess levels of plasticity in habitat use, ranging from transience to long‐term fidelity. Here, we evaluate the fidelity of hawksbill sea turtles ( Eretmochelys imbricata ) to habitats used while foraging (our primary focus), migrating, and nesting. After satellite tracking 17 adult females from three Western Atlantic nesting areas, we then re‐tracked them in a subsequent year. Of 15 turtles with sufficient data to assess interannual foraging area fidelity, 14 returned to the same home range, exhibiting overlap between successive 50% utilization distributions (UDs); the 15th individual shifted

A global assessment of microplastic abundance and characteristics on marine turtle nesting beaches - Zara L.R. Botterell; Jed Ardren; Elly Dove; Ellen McArthur; David S. Addison; Oyeronke M. Adegbile; Pierre Didier Agamboue; Andrews Agyekumhene; Phil Allman; Alexandra Alterman; Adren Anderson; Theresa Arenholz; et al. (Marine Pollution Bulletin, 2025)

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.

Ecological niche use varies with sea turtle reproductive age - Alexandra L. Fireman; Seth P. Stapleton; Hannah Vander Zanden; Dong Liang; Ryan J. Woodland (Marine Biology, 2024)

Widespread annual occurrence of pesticides within designated critical habitats for endangered prairie butterflies - Erik Runquist; Cale Nordmeyer; Seth Stapleton (Journal of Insect Conservation, 2024)
Insect declines have become pronounced in prairie ecosystems, particularly in areas of agricultural intensification. Non-target pesticide exposure has been raised as a key concern for prairie remnant health. Over seven years, we screened grass and soil samples for the presence and quantities of hundreds of pesticides from five prairies in Minnesota and South Dakota that are designated as Critical Habitat for two globally endangered butterflies: Poweshiek skipperling and Dakota skipper. We documented dozens of pesticides across all sites and years on their larval host grasses. Interiors of prairies were not less likely to have detectable pesticides than along prairie-agriculture edges. Broad-spectrum organophosphate and pyrethroid insecticides were common in late season. Chlorpyrifos quantities were higher at sites where both endangered species have been extirpated. Neonicotinoid insecticides, which have been frequently attributed to declines in insect pollinators, did not present a significant exposure signal in these prairie habitats. Few pesticides were detected in soil or early season grass samples. The prevalence and quantities of pesticides we observed are likely underestimates, and additional research is needed on the landscape of risk at small and large scales. Implications for Conservation: Protected prairies are not immune to the risk of pesticide exposure, which may impact efforts to re-establish lost populations of imperiled prairie insects, including endangered butterflies.

An on-ice aerial survey of the Kane Basin polar bear (Ursus maritimus) subpopulation - Øystein Wiig; Stephen N. Atkinson; Erik W. Born; Seth Stapleton; Todd Arnold; Markus Dyck; Kristin L. Laidre; Nicholas J. Lunn; Eric V. Regehr (Polar Biology, 2022)
There is an imminent need to collect information on distribution and abundance of polar bears ( Ursus maritimus ) to understand how they are affected by the ongoing decrease in Arctic sea ice. The Kane Basin (KB) subpopulation is a group of high-latitude polar bears that ranges between High Arctic Canada and NW Greenland around and north of the North Water polynya (NOW). We conducted a line transect distance sampling aerial survey of KB polar bears during 28 April–12 May 2014. A total of 4160 linear kilometers were flown in a helicopter over fast ice in the fjords and over offshore pack ice between 76° 50′ and 80° N′. Using a mark-recapture distance sampling protocol, the estimated abundance was 190 bears (95% lognormal CI: 87–411; CV 39%). This estimate is likely negatively biased to an unknown degree because the offshore sectors of the NOW with much open water were not surveyed because of logistical and safety reasons. Our study demonstrated that aerial surveys may be a feasible method for obtaining abundance estimates for small subpopulations of polar bears.

Body size and digestive system shape resource selection by ungulates: A cross‐taxa test of the forage maturation hypothesis - Saeideh Esmaeili; Brett R. Jesmer; Shannon E. Albeke; Ellen O. Aikens; Kathryn A. Schoenecker; Sarah R. B. King; Briana Abrahms; Bayarbaatar Buuveibaatar; Jeffrey L. Beck; Randall B. Boone; Francesca Cagnacci; Simon Chamaillé‐Jammes; et al. (Ecology Letters, 2021)
The forage maturation hypothesis (FMH) states that energy intake for ungulates is maximised when forage biomass is at intermediate levels. Nevertheless, metabolic allometry and different digestive systems suggest that resource selection should vary across ungulate species. By combining GPS relocations with remotely sensed data on forage characteristics and surface water, we quantified the effect of body size and digestive system in determining movements of 30 populations of hindgut fermenters (equids) and ruminants across biomes. Selection for intermediate forage biomass was negatively related to body size, regardless of digestive system. Selection for proximity to surface water was stronger for equids relative to ruminants, regardless of body size. To be more generalisable, we suggest that the FMH explicitly incorporate contingencies in body size and digestive system, with small‐bodied ruminants selecting more strongly for potential energy intake, and hindgut fermenters selecting more strongly for surface water.

Estimating the abundance of polar bears on Wrangel Island during late summer using high-resolution satellite imagery: a pilot study - Michelle A. LaRue; Seth Stapleton (Polar Biology, 2018)

Feasibility of using high‐resolution satellite imagery to assess vertebrate wildlife populations - Michelle A. LaRue; Seth Stapleton; Morgan Anderson (Conservation Biology, 2017)
Although remote sensing has been used for >40 years to learn about Earth, use of very high‐resolution satellite imagery (VHR) (

Aerial surveys suggest long‐term stability in the seasonally ice‐free Foxe Basin (Nunavut) polar bear population - Seth Stapleton; Elizabeth Peacock; David Garshelis (Marine Mammal Science, 2016)
Significant information gaps exist regarding the status of polar bears, especially with respect to the impacts of climate change, across large portions of the Arctic. To obtain an updated abundance estimate for the Foxe Basin population, we conducted comprehensive aerial surveys during the 2009 and 2010 ice‐free seasons, when bears are confined to land. We sampled with mark‐recapture distance sampling protocols on inland and coastal transects and surveyed small islands and remnant ice floes. We observed 816 and 1,003 bears in 2009 and 2010, respectively. Although detection functions differed substantially between years, estimates were consistent between analytical methods and years. Averaging four estimates (two from each year) yielded 2,585 (2,096–3,189) bears, which is similar to an estimate from the 1990s. This result, along with robust cub production, suggests a stable and healthy population despite deteriorating sea ice conditions. Collectively, this and other recent on‐land surveys provide a framework for implementing aerial surveys elsewhere. Although aerial surveys do not yield estimates of vital rates or population growth, they enable more rapid and frequent monitoring than mark‐recapture. Integrating them in long‐term monitoring programs will require consideration of ancillary data to infer status and facilitate setting harvest levels.

Estimating the abundance of the Southern Hudson Bay polar bear subpopulation with aerial surveys - Martyn E. Obbard; Seth Stapleton; Kevin R. Middel; Isabelle Thibault; Vincent Brodeur; Charles Jutras (Polar Biology, 2015)