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.

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.

Strengths and complementarity of systematic conservation planning and Key Biodiversity Area approaches for spatial planning - Andy Plumptre; Jack Hayes; Daniele Baisero; Rob Rose; S. Holness; Lize von Staden; Robert J. Smith (Conservation Biology, 2025)
Developing biodiversity‐inclusive spatial plans at a national level is the focus of Target 1 of the Kunming–Montreal Global Biodiversity Framework (KMGBF). There are 2 general approaches to identifying areas of value for biodiversity plans: criteria‐based, such as the Key Biodiversity Areas (KBA) process, and systematic conservation planning (SCP) approaches, which apply complementarity to efficiently achieve specific quantitative targets. We examined the benefits of both approaches and considered how the KBA approach can best complement SCP. We reviewed 200 papers articles that applied SCP to real‐world data with the Marxan conservation design software. Our review showed that targets for biodiversity elements are poorly selected in many SCP publications, with more than 75% of the studies applying uniform percentage target amounts to planning elements. Uniform targets favor more widespread species and ecosystems that are likely to be more common and less important for conservation. The strengths and complementarities of KBA and SCP approaches were reviewed and we identified the elements from both approaches that should be considered for spatial planning to achieve Target 1 in the KMGBF. In particular, the global approach of KBAs (i.e., identifying sites of global significance for species or ecosystems) better complements SCP, which often has a national or subnational focus. The KMGBF will fail if conservation of globally significant sites is not targeted and these sites are not incorporated in national spatial planning.

Regional Variation in Winter Foraging Strategies by Weddell Seals in Eastern Antarctica and the Ross Sea - Rob Harcourt; Mark A. Hindell; Clive R. McMahon; Kimberly T. Goetz; Jean-Benoit Charrassin; Karine Heerah; Rachel Holser; Ian D. Jonsen; Michelle R. Shero; Xavier Hoenner; Rose Foster; Baukje Lenting; et al. (Frontiers in Marine Science, 2021)
The relative importance of intrinsic and extrinsic determinants of animal foraging is often difficult to quantify. The most southerly breeding mammal, the Weddell seal, remains in the Antarctic pack-ice year-round. We compared Weddell seals tagged at three geographically and hydrographically distinct locations in East Antarctica (Prydz Bay, Terre Adélie , and the Ross Sea) to quantify the role of individual variability and habitat structure in winter foraging behaviour. Most Weddell seals remained in relatively small areas close to the coast throughout the winter, but some dispersed widely. Individual utilisation distributions ( UDi , a measure of the total area used by an individual seal) ranged from 125 to 20,825 km 2 . This variability was not due to size or sex but may be due to other intrinsic states for example reproductive condition or personality. The type of foraging (benthic vs. pelagic) varied from 56.6 ± 14.9% benthic dives in Prydz Bay through 42.1 ± 9.4% Terre Adélie to only 25.1 ± 8.7% in the Ross Sea reflecting regional hydrographic structure. The probability of benthic diving was less likely the deeper the ocean. Ocean topography was also influential at the population level; seals from Terre Adélie , with its relatively narrow continental shelf, had a core (50%) UD of only 200 km 2 , considerably smaller than the Ross Sea (1650 km 2 ) and Prydz Bay (1700 km 2 ). Sea ice concentration had little influence on the time the seals spent in shallow coastal waters, but in deeper offshore water they used areas of higher ice concentration. Marine Protected Areas (MPAs) in the Ross Sea encompass all the observed Weddell seal habitat, and future MPAs that include the Antarctic continental shelf are likely to effectively protect key Weddell seal habitat.

Functionally richer communities improve ecosystem functioning: Dung removal and secondary seed dispersal by dung beetles in the Western Palaearctic - Tanja Milotić; Christophe Baltzinger; Carsten Eichberg; Amy E. Eycott; Marco Heurich; Jörg Müller; Jorge A. Noriega; Rosa Menendez; Jutta Stadler; Réka Ádám; Tessa Bargmann; Isabelle Bilger; et al. (Journal of Biogeography, 2019)
Aim In several ecosystems, the diversity of functional species traits has been shown to have a stronger effect on ecosystem functioning than taxonomic diversity alone. However, few studies have explored this idea at a large geographical scale. In a multisite experiment, we unravelled the relationship between ecosystem function and functional completeness of species assemblages using dung beetles as a model group, focusing on dung removal and secondary seed dispersal. Location Seventeen grassland locations across the Western Palaearctic. Methods We used a randomized block design with different exclosure types to control the dung and seed removing activities of individual functional groups of the local dung beetle assemblage. We classified dung beetle species according to resource specialization and into functional groups based on dung processing behaviour (dwellers, tunnellers, rollers) and body size (small, large). Additionally, we assessed the role of other soil macro‐invertebrates. By sampling the dung beetle community and measuring the remaining dung and seeds after the experiment, the impact of each functional group was estimated. Results Dung beetle assemblages differed along a north–south and east–west gradient. Dwellers dominated northernmost sites, whereas at lower latitudes we observed more tunnellers and rollers indicating a functional shift. Resource specialists were more abundant in southern and eastern areas. Overall, functional group diversity enhanced dung removal. More dung (+46.9%) and seeds (+32.1%) were removed in the southern sites and tunnellers and rollers were more effective. At the northernmost sites, where tunnellers were scarce or absent, other soil macro‐invertebrates removed the majority of dung. Main conclusions The conservation of functionally complete dung beetle assemblages is crucial to maintain the ecosystem functions provided by dung beetles. Given the latitudinal variation in functional group diversity, it is reasonable to expect compositional changes due to climate change. These changes could lead to increased dung removal and a higher secondary seed dispersal rate in northern regions.

Erratum to: Microsatellite records for volume 7, issue 4 - Rose Komugisha Basiita; J. Henrich Bruggemann; Nianhui Cai; Conchi Cáliz-Campal; Chen Chen; Jiawei Chen; L. Cizek; Pedro J. Cordero; Deborah A. Dawson; Yandong Ding; L. Drag; Anan Duan; et al. (Conservation Genetics Resources, 2016)