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.

Vulnerability of marine megafauna to global at‐sea anthropogenic threats - Michelle VanCompernolle; Juliet Morris; Hannah J. Calich; Jorge P. Rodríguez; Sarah A. Marley; Jessica R. Pearce; Briana Abrahms; Katya Abrantes; André S. Afonso; Alex Aguilar; Andrews Agyekumhene; Tomonari Akamatsu; et al. (Conservation Biology, 2026)
Marine megafauna species are affected by a wide range of anthropogenic threats. To evaluate the risk of such threats, species’ vulnerability to each threat must first be determined. We build on the existing threats classification scheme and ranking system of the International Union for Conservation of Nature (IUCN) Red List of Threatened Species by assessing the vulnerability of 256 marine megafauna species to 23 at‐sea threats. The threats we considered included individual fishing gear types, climate‐change‐related subthreats not previously assessed, and threats associated with coastal impacts and maritime disturbances. Our ratings resulted in 70 species having high vulnerability ( v > 0.778 out of 1) to at least 1 threat, primarily drifting longlines, temperature extremes, or fixed gear. These 3 threats were also considered to have the most severe effects (i.e., steepest population declines). Overall, temperature extremes and plastics and other solid waste were rated as affecting the largest proportion of populations. Penguins, pinnipeds, and polar bears had the highest vulnerability to temperature extremes. Bony fishes had the highest vulnerability to drifting longlines and plastics and other solid waste; pelagic cetaceans to 4 maritime disturbance threats; elasmobranchs to 5 fishing threats; and flying birds to drifting longlines and 2 maritime disturbance threats. Sirenians and turtles had the highest vulnerability to at least one threat from all 4 categories. Despite not necessarily having severe effects for most taxonomic groups, temperature extremes were rated among the top threats for all taxa except bony fishes. The vulnerability scores we provide are an important first step in estimating the risk of threats to marine megafauna. Importantly, they help differentiate scope from severity, which is key to identifying threats that should be prioritized for mitigation.

Disentangling metabolite dynamics in extreme environments: life detection strategies for extraterrestrial worlds - Jacob M.C. Shaffer; Lesley-Ann Giddings; Robert Samples; Eli C. Sklute; Abigail Jarratt; Katherine Mateos; M. Darby Dyar; Peter A. Lee; Jill A. Mikucki (Phytochemistry Letters, 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.

Global Marine Flyways Identified for Long‐Distance Migrating Seabirds From Tracking Data - Joanne M. Morten; Ana P. B. Carneiro; Martin Beal; Anne‐Sophie Bonnet‐Lebrun; Maria P. Dias; Marie‐Morgane Rouyer; Autumn‐Lynn Harrison; Jacob González‐Solís; Victoria R. Jones; Virginia A. Garcia Alonso; Michelle Antolos; Javier A. Arata; et al. (Global Ecology and Biogeography, 2025)
Aim To identify the broad‐scale oceanic migration routes (‘marine flyways’) used by multiple pelagic, long‐distance migratory seabirds based on a global compilation of tracking data. Location Global. Time Period 1989–2023. Major Taxa Studied Seabirds (Families: Phaethontidae, Hydrobatidae, Diomedeidae, Procellariidae, Laridae and Stercorariidae). Methods We collated a comprehensive global tracking dataset that included the migratory routes of 48 pelagic and long‐distance migrating seabird species across the Atlantic, Indian, Pacific and Southern Oceans. We grouped individuals that followed similar routes, independent of species or timings of migration, using a dynamic time warping clustering approach. We visualised the routes of each cluster using a line density analysis and used knowledge of seabird spatial ecology to combine the clusters to identify the broad‐scale flyways followed by most pelagic migratory seabirds tracked to‐date at an ocean‐basin scale. Results Six marine flyways were identified across the world's oceans: the Atlantic Ocean Flyway, North Indian Ocean Flyway, East Indian Ocean Flyway, West Pacific Ocean Flyway, Pacific Ocean Flyway and Southern Ocean Flyway. Generally, the flyways were used bidirectionally, and individuals either followed sections of a flyway, a complete flyway, or their movements linked two or more flyways. Transhemispheric figure‐of‐eight routes in the Atlantic and Pacific oceans, and a circumnavigation flyway in the Southern Ocean correspond with major wind ‐ driven ocean currents. Main Conclusions The marine flyways identified demonstrate that pelagic seabirds have similar and repeatable migration routes across ocean‐basin scales. Our study highlights the need to account for connectivity in seabird conservation and provides a framework for international cooperation.

Composition and activity of soil microbial communities in native and non-native vegetation of southern California - George L. Vourlitis; Powers Berry; Juliane Maye Cabuco; Analiza Estrada; Kevin H. García; Brad T. Hunter; Lydia Mastaglio; Elizabeth Murguia; Nicole Nacauili; Melanie Ponce; Loly Saenz; Zaid Salah; et al. (Applied Soil Ecology, 2024)

Mismatches in scale between highly mobile marine megafauna and marine protected areas - Melinda G. Conners; Nicholas B. Sisson; Pierre D. Agamboue; Philip W. Atkinson; Alastair M. M. Baylis; Scott R. Benson; Barbara A. Block; Steven J. Bograd; Pablo Bordino; W. D. Bowen; Paul Brickle; Ignacio M. Bruno; et al. (Frontiers in Marine Science, 2022)
Marine protected areas (MPAs), particularly large MPAs, are increasing in number and size around the globe in part to facilitate the conservation of marine megafauna under the assumption that large-scale MPAs better align with vagile life histories; however, this alignment is not well established. Using a global tracking dataset from 36 species across five taxa, chosen to reflect the span of home range size in highly mobile marine megafauna, we show most MPAs are too small to encompass complete home ranges of most species. Based on size alone, 40% of existing MPAs could encompass the home ranges of the smallest ranged species, while only < 1% of existing MPAs could encompass those of the largest ranged species. Further, where home ranges and MPAs overlapped in real geographic space, MPAs encompassed < 5% of core areas used by all species. Despite most home ranges of mobile marine megafauna being much larger than existing MPAs, we demonstrate how benefits from MPAs are still likely to accrue by targeting seasonal aggregations and critical life history stages and through other management techniques.

Complete genome of the thermophilic purple sulfur Bacterium Thermochromatium tepidum compared to Allochromatium vinosum and other Chromatiaceae - W. Matthew Sattley; Wesley D. Swingley; Brad M. Burchell; Emma D. Dewey; Mackenzie K. Hayward; Tara L. Renbarger; Kathryn N. Shaffer; Lynn M. Stokes; Sonja A. Gurbani; Catrina M. Kujawa; D. Adam Nuccio; Jacob Schladweiler; et al. (Photosynthesis Research, 2022)