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.

Spatiotemporal properties of intrinsic sea level variability along the southeastern United States coastline - Carmine Donatelli; Christopher M. Little; Rui M. Ponte; Stephen G. Yeager (Ocean Science, 2025)
The influence of intrinsic ocean variability on coastal sea level remains largely unexplored but is of potential importance for emerging forecasting efforts. As in weather forecasts, intrinsic variability will amplify uncertainty in initial conditions. However, variability originating from intrinsic processes may be predictable in a forecast system with sufficient resolution and accurate initialization. Here, we examine the spatiotemporal properties of intrinsic sea level variability along the southeastern United States coast using a suite of global ocean/sea-ice simulations at 0.1° horizontal resolution. In model simulations, intrinsic variability is a dominant component of the monthly de-seasonalized and detrended sea level variability in deep waters, but it is damped along continental shelves, where it comprises ∼ 10 %–30 % of the sea level standard deviation. Our analyses demonstrate that US East Coast and Gulf of Mexico shelves exhibit a common intrinsic mode, with maximal amplitude in the South Atlantic Bight and almost no expression north of Cape Hatteras. This intrinsic coastal mode is coherent with sea level along the Gulf Stream axis after detachment from Cape Hatteras. Intrinsic sea level variability in the detached Gulf Stream leads the coastal mode by 2–3 months, suggesting that intrinsic coastal sea level variability may exhibit predictability.

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.

Wildlife Conservation on Private Land: A Social-Ecological Systems Study - Matthew Taylor; Barry Brook; Christopher Johnson; Siobhan de Little (Environmental Management, 2024)
As human activity accelerates the global crisis facing wildlife populations, private land conservation provides an example of wildlife management challenges in social-ecological systems. This study reports on the research phase of ‘WildTracker’ - a co-created citizen science project, involving 160 landholders across three Tasmanian regions. This was a transdisciplinary collaboration between an environmental organisation, university researchers, and local landholders. Focusing on mammal and bird species, the project integrated diverse data types and technologies: social surveys, quantitative ecology, motion sensor cameras, acoustic recorders, and advanced machine-learning analytics. An iterative analytical methodology encompassed Pearson and point-biserial correlation for interrelationships, Non-Metric Multidimensional Scaling (NMDS) for clustering, and Random Forest machine learning for variable importance and prediction. Taken together, these analyses revealed complex relationships between wildlife populations and a suite of ecological, socio-economic, and land management variables. Both site-scale habitat characteristics and landscape-scale vegetation patterns were useful predictors of mammal and bird activity, but these relationships were different for mammals and birds. Four focal mammal species showed variation in their response to ecological and land management drivers. Unexpectedly, threatened species, such as the eastern quoll ( Dasyurus viverrinus) , favoured locations where habitat was substantially modified by human activities. The research provides actionable insights for landowners, and highlights the importance of ‘messy,’ ecologically heterogeneous, mixed agricultural landscapes for wildlife conservation. The identification of thresholds in habitat fragmentation reinforced the importance of collaboration across private landscapes. Participatory research models such as WildTracker can complement efforts to address the wicked problem of wildlife conservation in the Anthropocene.

An experimental study of wet-cooking in organic vessels: implications for understanding the evolution of cooking technologies - Andy Langley; Andy Needham; Roland Kröger; Gabriel Cifuentes-Alcobendas; Mette Adegeest; Jess Cousen; Christopher Lance; Hannah Benton; Amy-Rose Mansbridge; Amanda Satchell; Lewis Tomlinson; Francesca Rockall-Birtles; et al. (Archaeological and Anthropological Sciences, 2023)
The ability to control and direct fire is a major evolutionary step in the human story. The development of aceramic cooking technologies is less well understood as they rarely survive in the archaeological record. However, inferential evidence such as fire-cracked rocks, earthen pits and heated bones suggest a variety of cooking methods were used prior to the invention of ceramics. Yet there is a paucity of experimental evidence testing the efficacy of perishable organic containers in tasks involving their use with heat. The study presents experimental results of organic containers and their use for heating water related to cooking. Containers were made from deer hide and pig stomach and water was heated using two different techniques: placing the container directly above a fire and placing hot stones into the container. The results suggest that different organic containers and heating types could attain and maintain a sub-boiling cooking temperature; however, not all could reach boiling point. It is argued that these sub-boiling methods may be as, or perhaps more, desirable than boiling, with potential implications for the development of vessels prior to the adoption of ceramics.

A pathogenic deletion in Forkhead Box L1 (FOXL1) identifies the first otosclerosis (OTSC) gene - Nelly Abdelfatah; Ahmed A. Mostafa; Curtis R. French; Lance P. Doucette; Cindy Penney; Matthew B. Lucas; Anne Griffin; Valerie Booth; Christopher Rowley; Jessica E. Besaw; Lisbeth Tranebjærg; Nanna Dahl Rendtorff; et al. (Human Genetics, 2022)
Otosclerosis is a bone disorder of the otic capsule and common form of late-onset hearing impairment. Considered a complex disease, little is known about its pathogenesis. Over the past 20 years, ten autosomal dominant loci ( OTSC1-10 ) have been mapped but no genes identified. Herein, we map a new OTSC locus to a 9.96 Mb region within the FOX gene cluster on 16q24.1 and identify a 15 bp coding deletion in Forkhead Box L1 co-segregating with otosclerosis in a Caucasian family. Pre-operative phenotype ranges from moderate to severe hearing loss to profound sensorineural loss requiring a cochlear implant. Mutant FOXL1 is both transcribed and translated and correctly locates to the cell nucleus. However, the deletion of 5 residues in the C-terminus of mutant FOXL1 causes a complete loss of transcriptional activity due to loss of secondary (alpha helix) structure. FOXL1 (rs764026385) was identified in a second unrelated case on a shared background. We conclude that FOXL1 (rs764026385) is pathogenic and causes autosomal dominant otosclerosis and propose a key inhibitory role for wildtype Foxl1 in bone remodelling in the otic capsule. New insights into the molecular pathology of otosclerosis from this study provide molecular targets for non-invasive therapeutic interventions.

An Interdisciplinary Perspective on Greenland’s Changing Coastal Margins - Fiammetta Straneo; Donald Slater; Caroline Bouchard; Mattias Cape; Mark Carey; Lorenzo Ciannelli; James Holte; Patricia Matrai; Kristin Laidre; Christopher Little; Lorenz Meire; Helene Seroussi; et al. (Oceanography, 2022)
Greenland’s coastal margins are influenced by the confluence of Arctic and Atlantic waters, sea ice, icebergs, and meltwater from the ice sheet. Hundreds of spectacular glacial fjords cut through the coastline and support thriving marine ecosystems and, in some places, adjacent Greenlandic communities. Rising air and ocean temperatures, as well as glacier and sea-ice retreat, are impacting the conditions that support these systems. Projecting how these regions and their communities will evolve requires understanding both the large-scale climate variability and the regional-scale web of physical, biological, and social interactions. Here, we describe pan-Greenland physical, biological, and social settings and show how they are shaped by the ocean, the atmosphere, and the ice sheet. Next, we focus on two communities, Qaanaaq in Northwest Greenland, exposed to Arctic variability, and Ammassalik in Southeast Greenland, exposed to Atlantic variability. We show that while their climates today are similar to those of the warm 1930s–1940s, temperatures are projected to soon exceed those of the last 100 years at both locations. Existing biological records, including fisheries, provide some insight on ecosystem variability, but they are too short to discern robust patterns. To determine how these systems will evolve in the future requires an improved understanding of the linkages and external factors shaping the ecosystem and community response. This interdisciplinary study exemplifies a first step in a systems approach to investigating the evolution of Greenland’s coastal margins.

A clustering-based approach to ocean model–data comparison around Antarctica - Qiang Sun; Christopher M. Little; Alice M. Barthel; Laurie Padman (Ocean Science, 2021)
The Antarctic Continental Shelf seas (ACSS) are a critical, rapidly changing element of the Earth system. Analyses of global-scale general circulation model (GCM) simulations, including those available through the Coupled Model Intercomparison Project, Phase 6 (CMIP6), can help reveal the origins of observed changes and predict the future evolution of the ACSS. However, an evaluation of ACSS hydrography in GCMs is vital: previous CMIP ensembles exhibit substantial mean-state biases (reflecting, for example, misplaced water masses) with a wide inter-model spread. Because the ACSS are also a sparely sampled region, grid-point-based model assessments are of limited value. Our goal is to demonstrate the utility of clustering tools for identifying hydrographic regimes that are common to different source fields (model or data), while allowing for biases in other metrics (e.g., water mass core properties) and shifts in region boundaries. We apply K-means clustering to hydrographic metrics based on the stratification from one GCM (Community Earth System Model version 2; CESM2) and one observation-based product (World Ocean Atlas 2018; WOA), focusing on the Amundsen, Bellingshausen and Ross seas. When applied to WOA temperature and salinity profiles, clustering identifies “primary” and “mixed” regimes that have physically interpretable bases. For example, meltwater-freshened coastal currents in the Amundsen Sea and a region of high-salinity shelf water formation in the southwestern Ross Sea emerge naturally from the algorithm. Both regions also exhibit clearly differentiated inner- and outer-shelf regimes. The same analysis applied to CESM2 demonstrates that, although mean-state model biases in water mass T–S characteristics can be substantial, using a clustering approach highlights that the relative differences between regimes and the locations where each regime dominates are well represented in the model. CESM2 is generally fresher and warmer than WOA and has a limited fresh-water-enriched coastal regimes. Given the sparsity of observations of the ACSS, this technique is a promising tool for the evaluation of a larger model ensemble (e.g., CMIP6) on a circum-Antarctic basis.

Scenarios for Global Aquaculture and Its Role in Human Nutrition - Jessica A. Gephart; Christopher D. Golden; Frank Asche; Ben Belton; Cecile Brugere; Halley E. Froehlich; Jillian P. Fry; Benjamin S. Halpern; Christina C. Hicks; Robert C. Jones; Dane H. Klinger; David C. Little; et al. (Reviews in Fisheries Science & Aquaculture, 2021)

Correction to: Variation in stalk rot resistance and physiological traits of sorghum genotypes in the field under high temperature - Ramasamy Perumal; Sandeep S. Tomar; Ananda Bandara; Djanaguiraman Maduraimuthu; Tesfaye T. Tesso; P. V. Vara Prasad; Hari D. Upadhyaya; Christopher R. Little (Journal of General Plant Pathology, 2020)

Variation in stalk rot resistance and physiological traits of sorghum genotypes in the field under high temperature - Ramasamy Perumal; Sandeep S. Tomar; Ananda Bandara; Djanaguiraman Maduraimuthu; Tesfaye T. Tesso; P. V. Vara Prasad; Hari D. Upadhyaya; Christopher R. Little (Journal of General Plant Pathology, 2020)

Opportunities for agent‐based modelling in human dimensions of fisheries - Matthew G. Burgess; Ernesto Carrella; Michael Drexler; Robert L. Axtell; Richard M. Bailey; James R. Watson; Reniel B. Cabral; Michaela Clemence; Christopher Costello; Chris Dorsett; Steven D. Gaines; Emily S. Klein; et al. (Fish and Fisheries, 2020)
Models of human dimensions of fisheries are important to understanding and predicting how fishing industries respond to changes in marine ecosystems and management institutions. Advances in computation have made it possible to construct agent‐based models (ABMs)—which explicitly describe the behaviour of individual people, firms or vessels in order to understand and predict their aggregate behaviours. ABMs are widely used for both academic and applied purposes in many settings including finance, urban planning and the military, but are not yet mainstream in fisheries science and management, despite a growing literature. ABMs are well suited to understanding emergent consequences of fisher interactions, heterogeneity and bounded rationality, especially in complex ecological, social and institutional contexts. For these reasons, we argue that ABMs of human behaviour can contribute significantly to human dimensions of fisheries in three areas: (a) understanding interactions between multiple management institutions; (b) incorporating cognitive and behavioural sciences into fisheries science and practice; and (c) understanding and projecting the social consequences of management institutions. We provide simple examples illustrating the potential for ABMs in each of these areas, using conceptual (“toy”) versions of the POSEIDON model. We argue that salient strategic advances in these areas could pave the way for increased tactical use of ABMs in fishery management settings. We review common ABM development and application challenges, with the aim of providing guidance to beginning ABM developers and users studying human dimensions of fisheries.

Towards Comprehensive Observing and Modeling Systems for Monitoring and Predicting Regional to Coastal Sea Level - Rui M. Ponte; Mark Carson; Mauro Cirano; Catia M. Domingues; Svetlana Jevrejeva; Marta Marcos; Gary Mitchum; R. S. W. van de Wal; Philip L. Woodworth; Michaël Ablain; Fabrice Ardhuin; Valérie Ballu; et al. (Frontiers in Marine Science, 2019)

Fusarium verticillioides inoculum potential influences soybean seed quality - Rodrigo Pedrozo; Christopher R. Little (European Journal of Plant Pathology, 2017)

European Marine Biodiversity Monitoring Networks: Strengths, Weaknesses, Opportunities and Threats - Joana Patrício; Sally Little; Krysia Mazik; Konstantia-Nadia Papadopoulou; Christopher J. Smith; Heliana Teixeira; Helene Hoffmann; Maria C. Uyarra; Oihana Solaun; Argyro Zenetos; Gokhan Kaboglu; Olga Kryvenko; et al. (Frontiers in Marine Science, 2016)

Managing the Marine Environment, Conceptual Models and Assessment Considerations for the European Marine Strategy Framework Directive - Christopher J. Smith; Konstantia-Nadia Papadopoulou; Steve Barnard; Krysia Mazik; Michael Elliott; Joana Patrício; Oihana Solaun; Sally Little; Natasha Bhatia; Angel Borja (Frontiers in Marine Science, 2016)

Macrofaunal Ecology of Sedimented Hydrothermal Vents in the Bransfield Strait, Antarctica - James B. Bell; Clare Woulds; Lee E. Brown; Christopher J. Sweeting; William D. K. Reid; Crispin T. S. Little; Adrian G. Glover (Frontiers in Marine Science, 2016)

Geographic Variability of Sea-Level Change - Robert E. Kopp; Carling C. Hay; Christopher M. Little; Jerry X. Mitrovica (Current Climate Change Reports, 2015)

Evaluation of Gambian and Malian sorghum germplasm against downy mildew pathogen, Peronosclerospora sorghi, in Mexico and the USA - Louis K. Prom; Ramasamy Perumal; Noe Montes-Garcia; Thomas Isakeit; Gary N. Odvody; William L. Rooney; Christopher R. Little; Clint Magill (Journal of General Plant Pathology, 2015)

Large Molecule Run Acceptance: Recommendation for Best Practices and Harmonization from the Global Bioanalysis Consortium Harmonization Team - Marian Kelley; Christopher Beaver; Lauren F. Stevenson; Ross Bamford; Paula Gegwich; Yamamoto Katsuhiko; Dongbei Li; Samantha Little; Arumugam Muruganandam; Daniela Stoellner; Ravi Kumar Trivedi (The AAPS Journal, 2014)

The ovine newborn and human foetal intervertebral disc contain perlecan and aggrecan variably substituted with native 7D4 CS sulphation motif: spatiotemporal immunolocalisation and co-distribution with Notch-1 in the human foetal disc - Cindy Shu; Clare Hughes; Susan M. Smith; Margaret M. Smith; Anthony Hayes; Bruce Caterson; Christopher B. Little; James Melrose (Glycoconjugate Journal, 2013)

Priming concerns about pathogen threat versus resource scarcity: dissociable effects on women’s perceptions of men’s attractiveness and dominance - Christopher D. Watkins; Lisa M DeBruine; Anthony C. Little; David R. Feinberg; Benedict C. Jones (Behavioral Ecology and Sociobiology, 2012)

Chondroitin sulphate and heparan sulphate sulphation motifs and their proteoglycans are involved in articular cartilage formation during human foetal knee joint development - James Melrose; Marc D. Isaacs; Susan M. Smith; Clare E. Hughes; Christopher B. Little; Bruce Caterson; Anthony J. Hayes (Histochemistry and Cell Biology, 2012)

Skier and Snowboarder Motivations and Knowledge Related to Voluntary Environmental Programs at an Alpine Ski Area - Christopher M. Little; Mark D. Needham (Environmental Management, 2011)

Topographical variation in the distributions of versican, aggrecan and perlecan in the foetal human spine reflects their diverse functional roles in spinal development - Susan M. Smith; John M. Whitelock; Renato V. Iozzo; Christopher B. Little; James Melrose (Histochemistry and Cell Biology, 2009)

Global assessment of coral bleaching and required rates of adaptation under climate change - SIMON D. DONNER; WILLIAM J. SKIRVING; CHRISTOPHER M. LITTLE; MICHAEL OPPENHEIMER; OVE HOEGH‐GULDBERG (Global Change Biology, 2005)
Elevated ocean temperatures can cause coral bleaching, the loss of colour from reef‐building corals because of a breakdown of the symbiosis with the dinoflagellate Symbiodinium . Recent studies have warned that global climate change could increase the frequency of coral bleaching and threaten the long‐term viability of coral reefs. These assertions are based on projecting the coarse output from atmosphere–ocean general circulation models (GCMs) to the local conditions around representative coral reefs. Here, we conduct the first comprehensive global assessment of coral bleaching under climate change by adapting the NOAA Coral Reef Watch bleaching prediction method to the output of a low‐ and high‐climate sensitivity GCM. First, we develop and test algorithms for predicting mass coral bleaching with GCM‐resolution sea surface temperatures for thousands of coral reefs, using a global coral reef map and 1985–2002 bleaching prediction data. We then use the algorithms to determine the frequency of coral bleaching and required thermal adaptation by corals and their endosymbionts under two different emissions scenarios. The results indicate that bleaching could become an annual or biannual event for the vast majority of the world's coral reefs in the next 30–50 years without an increase in thermal tolerance of 0.2–1.0°C per decade. The geographic variability in required thermal adaptation found in each model and emissions scenario suggests that coral reefs in some regions, like Micronesia and western Polynesia, may be particularly vulnerable to climate change. Advances in modelling and monitoring will refine the forecast for individual reefs, but this assessment concludes that the global prognosis is unlikely to change without an accelerated effort to stabilize atmospheric greenhouse gas concentrations.