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.

Harnessing the value of near-term actions for achieving climate-ready fishery management - Michael Drexler; Elizabeth B. Cerny-Chipman; Megan J. Peterson Williams; Meredith Moore; Corey Ridings (Frontiers in Marine Science, 2025)
Climate change requires managers to bolster long-term resilience of fisheries and concurrently improve short-term responsiveness of management systems to prevailing ecological conditions, all while avoiding unintended harm to stocks in a highly uncertain context. There has been substantial effort dedicated to developing the scientific information and tools needed to inform climate-ready fisheries, yet implementation of these approaches has been limited in the United States management system. Meanwhile, climate impacts on fisheries are already occurring, making fish and fishing communities highly vulnerable to sudden, and often detrimental, changes. There is a need to accelerate adaptation efforts, and near-term action is critical even without the full complement of information and tools in hand. Here, existing climate-ready approaches were compiled and synthesized to offer a comprehensive and structured perspective on priority actions that can be taken in the next 1-2 years to increase the resilience and adaptability of fish stocks and communities that rely on them. From the review there are three main findings: 1) 45% of the management actions can be implemented in this short timeframe, 2) Nearly all actions identified can be implemented in the current fishery and regulatory framework, and 3) While new approaches are needed, managers should proceed with caution to avoid maladaptation and choose a no- or low- maladaptation risk approach wherever possible.

Investigation of heterotrophs reveals new insights in dinoflagellate evolution - Elizabeth C. Cooney; Corey C. Holt; Elisabeth Hehenberger; Jayd A. Adams; Brian S. Leander; Patrick J. Keeling (Molecular Phylogenetics and Evolution, 2024)

SNAPSHOT USA 2021: A third coordinated national camera trap survey of the U nited S tates - Hila Shamon; Roi Maor; Michael V. Cove; Roland Kays; Jessie Adley; Peter D. Alexander; David N. Allen; Maximilian L. Allen; Cara L. Appel; Evan Barr; Erika L. Barthelmess; Carolina Baruzzi; et al. (Ecology, 2024)
SNAPSHOT USA is a multicontributor, long‐term camera trap survey designed to survey mammals across the United States. Participants are recruited through community networks and directly through a website application ( https://www.snapshot-usa.org/ ). The growing Snapshot dataset is useful, for example, for tracking wildlife population responses to land use, land cover, and climate changes across spatial and temporal scales. Here we present the SNAPSHOT USA 2021 dataset, the third national camera trap survey across the US. Data were collected across 109 camera trap arrays and included 1711 camera sites. The total effort equaled 71,519 camera trap nights and resulted in 172,507 sequences of animal observations. Sampling effort varied among camera trap arrays, with a minimum of 126 camera trap nights, a maximum of 3355 nights, a median 546 nights, and a mean 656 ± 431 nights. This third dataset comprises 51 camera trap arrays that were surveyed during 2019, 2020, and 2021, along with 71 camera trap arrays that were surveyed in 2020 and 2021. All raw data and accompanying metadata are stored on Wildlife Insights ( https://www.wildlifeinsights.org/ ), and are publicly available upon acceptance of the data papers. SNAPSHOT USA aims to sample multiple ecoregions in the United States with adequate representation of each ecoregion according to its relative size. Currently, the relative density of camera trap arrays varies by an order of magnitude for the various ecoregions (0.22–5.9 arrays per 100,000 km 2 ), emphasizing the need to increase sampling effort by further recruiting and retaining contributors. There are no copyright restrictions on these data. We request that authors cite this paper when using these data, or a subset of these data, for publication. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government.

Lower cardiac output is associated with neurodegeneration among older adults with normal cognition but not mild cognitive impairment - Elizabeth E. Moore; Dandan Liu; Corey W. Bown; Hailey A. Kresge; Deepak K. Gupta; Kimberly R. Pechman; Lisa A. Mendes; L. Taylor Davis; Katherine A. Gifford; Adam W. Anderson; Thomas J. Wang; Bennett A. Landman; et al. (Brain Imaging and Behavior, 2021)

Correlates of bird collisions with buildings across three North American countries - Jared A. Elmore; Stephen B. Hager; Bradley J. Cosentino; Timothy J. O'Connell; Corey S. Riding; Michelle L. Anderson; Marja H. Bakermans; Than J. Boves; David Brandes; Eric M. Butler; Michael W. Butler; Nicolette L. Cagle; et al. (Conservation Biology, 2021)
Collisions with buildings cause up to 1 billion bird fatalities annually in the United States and Canada. However, efforts to reduce collisions would benefit from studies conducted at large spatial scales across multiple study sites with standardized methods and consideration of species‐ and life‐history‐related variation and correlates of collisions. We addressed these research needs through coordinated collection of data on bird collisions with buildings at sites in the United States (35), Canada (3), and Mexico (2). We collected all carcasses and identified species. After removing records for unidentified carcasses, species lacking distribution‐wide population estimates, and species with distributions overlapping fewer than 10 sites, we retained 269 carcasses of 64 species for analysis. We estimated collision vulnerability for 40 bird species with ≥2 fatalities based on their North American population abundance, distribution overlap in study sites, and sampling effort. Of 10 species we identified as most vulnerable to collisions, some have been identified previously (e.g., Black‐throated Blue Warbler [ Setophaga caerulescens ]), whereas others emerged for the first time (e.g., White‐breasted Nuthatch [ Sitta carolinensis ]), possibly because we used a more standardized sampling approach than past studies. Building size and glass area were positively associated with number of collisions for 5 of 8 species with enough observations to analyze independently. Vegetation around buildings influenced collisions for only 1 of those 8 species (Swainson's Thrush [ Catharus ustulatus ]). Life history predicted collisions; numbers of collisions were greatest for migratory, insectivorous, and woodland‐inhabiting species. Our results provide new insight into the species most vulnerable to building collisions, making them potentially in greatest need of conservation attention to reduce collisions and into species‐ and life‐history‐related variation and correlates of building collisions, information that can help refine collision management.

Correction to: CpG‑creating mutations are costly in many human viruses - Victoria R. Caudill; Sarina Qin; Ryan Winstead; Jasmeen Kaur; Kaho Tisthammer; E. Geo Pineda; Caroline Solis; Sarah Cobey; Trevor Bedford; Oana Carja; Rosalind M. Eggo; Katia Koelle; et al. (Evolutionary Ecology, 2020)

CpG-creating mutations are costly in many human viruses - Victoria R. Caudill; Sarina Qin; Ryan Winstead; Jasmeen Kaur; Kaho Tisthammer; E. Geo Pineda; Caroline Solis; Sarah Cobey; Trevor Bedford; Oana Carja; Rosalind M. Eggo; Katia Koelle; et al. (Evolutionary Ecology, 2020)
Mutations can occur throughout the virus genome and may be beneficial, neutral or deleterious. We are interested in mutations that yield a C next to a G, producing CpG sites. CpG sites are rare in eukaryotic and viral genomes. For the eukaryotes, it is thought that CpG sites are rare because they are prone to mutation when methylated. In viruses, we know less about why CpG sites are rare. A previous study in HIV suggested that CpG-creating transition mutations are more costly than similar non-CpG-creating mutations. To determine if this is the case in other viruses, we analyzed the allele frequencies of CpG-creating and non-CpG-creating mutations across various strains, subtypes, and genes of viruses using existing data obtained from Genbank, HIV Databases, and Virus Pathogen Resource. Our results suggest that CpG sites are indeed costly for most viruses. By understanding the cost of CpG sites, we can obtain further insights into the evolution and adaptation of viruses.

Evidence of adoption, monozygotic twinning, and low inbreeding rates in a large genetic pedigree of polar bears - René M. Malenfant; David W. Coltman; Evan S. Richardson; Nicholas J. Lunn; Ian Stirling; Elizabeth Adamowicz; Corey S. Davis (Polar Biology, 2016)

Temporal and spatial variation in the distribution of life history phases of Chondrus crispus (Gigartinales, Rhodophyta) - David J. Garbary; Elizabeth Tompkins; Katelyn White; Peter Corey; Jang-K. Kim (Algae, 2011)

Quantitative trait loci for hip dysplasia in a crossbreed canine pedigree - Rory J. Todhunter; Raluca Mateescu; George Lust; Nancy I. Burton-Wurster; Nathan L. Dykes; Stuart P. Bliss; Alma J. Williams; Margaret Vernier-Singer; Elizabeth Corey; Carlos Harjes; Richard L. Quaas; Zhiwu Zhang; et al. (Mammalian Genome, 2005)

Variation at the major histocompatibility complex in Savannah sparrows - Corey R. Freeman‐Gallant; Elizabeth M. Johnson; Fiorella Saponara; Matthew Stanger (Molecular Ecology, 2002)
The class I and class II genes of the major histocompatibility complex ( Mhc ) encode dimeric glycoproteins responsible for eliciting the adaptive immune response of vertebrates. Recent work with birds suggests that the number, size, and arrangement of these genes can differ markedly across species, although the extent of this variation, and its causes and consequences, are poorly understood. We have used a 157‐base‐pair (bp) portion of the second exon of a class II B gene to probe the Mhc in a free‐living population of Savannah sparrows ( Passerculus sandwichensis ). Segregation analysis of Mhc bands suggests that class II B genes can be found in two independently assorting clusters, as previously described for domestic chickens ( Gallus gallus ) and ring‐necked pheasants ( Phasianus colchicus ) but unlike gene organization in mammals. The Mhc in Savannah sparrows appears large (with many class II B genes) and variable; we found 42 unique genotypes among 48 adults breeding on Kent Island, New Brunswick, Canada in 1995. Savannah sparrows are long‐distance migrants, and these results support recent predictions that migratory birds should show higher levels of Mhc polymorphism and/or a greater number of genes than sedentary species. Savannah sparrows are also socially polygynous with high levels of extra‐pair paternity, suggesting that a history of sexual selection might also influence the size and/or structure of the avian Mhc .