Analysis of second-generation epigenetic clocks reveals further associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Vincent Doré; Pierrick Bourgeat; Rosita Shishegar; James D. Doecke; Paul Maruff; Christopher C. Rowe; Victor L. Villemagne; Michael Weiner; Paul Aisen; Ronald Petersen; et al. (GeroScience, 2026)

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.

Sensory Evaluation of a Powdered Seaweed Seasoning Blend - T. Sutton; H. Park; K. Crowe-White; A. Ferdous; K. Won; A. Robins; A. Ellis (Journal of the Academy of Nutrition and Dietetics, 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.

Harassment and killing of porpoises (“phocoenacide”) by fish‐eating Southern Resident killer whales ( Orcinus orca ) - Deborah A. Giles; Sarah J. Teman; Samuel Ellis; John K. B. Ford; Monika W. Shields; M. Bradley Hanson; Candice K. Emmons; Paul E. Cottrell; Robin W. Baird; Richard W. Osborne; Michael Weiss; David K. Ellifrit; et al. (Marine Mammal Science, 2024)
Endangered Southern Resident killer whales ( Orcinus orca ) are fish‐eaters that preferentially prey on adult Chinook salmon ( Oncorhynchus tshawytscha ). Despite being salmon specialists, individuals from all three killer whale pods (J, K, L) have been observed harassing and killing porpoises (family Phocoenidae) without consuming them. Retrospectively, we identified and analyzed 78 episodes of Southern Resident killer whales harassing porpoises between 1962 and 2020, of which 28 resulted in the porpoise's death (“phocoenacide”). Fifty‐six episodes involved harbor porpoise ( Phocoena phocoena ), 13 involved Dall's porpoise ( Phocoenoides dalli ), and the porpoise species was unreported for nine episodes. Southern Resident killer whales often targeted young porpoises that were similar in size to adult Chinook salmon. Both sexes participated in porpoise harassment. Juveniles engaged in the behavior the most; however, their rates of engagement were not found to differ significantly from most other age classes. The behavior was passed through generations and social groupings, as it was first observed in L pod and spread to the other two pods. Killer whales are highly complex animals known to exhibit social learning and cultural transmission of learned behaviors, but the reason(s) for this behavior is unknown. Hypotheses include the social and developmental benefits of play, hunting practice, or displaced epimeletic behavior.

Dispersal of the pesticide diuron in the Great Barrier Reef - Jennifer Skerratt; Mark E. Baird; Mathieu Mongin; Robin Ellis; Rachael A. Smith; Melanie Shaw; Andy D.L. Steven (Science of The Total Environment, 2023)

Finding the sweet spot: a qualitative study exploring patients’ acceptability of chatbots in genetic service delivery - Stephanie Luca; Marc Clausen; Angela Shaw; Whiwon Lee; Suvetha Krishnapillai; Ella Adi-Wauran; Hanna Faghfoury; Gregory Costain; Rebekah Jobling; Melyssa Aronson; Eriskay Liston; Josh Silver; et al. (Human Genetics, 2023)

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume - Lidija Milicic; Michael Vacher; Tenielle Porter; Vincent Doré; Samantha C. Burnham; Pierrick Bourgeat; Rosita Shishegar; James Doecke; Nicola J. Armstrong; Rick Tankard; Paul Maruff; Colin L. Masters; et al. (GeroScience, 2022)
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.

Trends in volcano seismology: 2010 to 2020 and beyond - Weston A. Thelen; Robin S. Matoza; Alicia J. Hotovec-Ellis (Bulletin of Volcanology, 2022)

Implications of management on immunogenetic variation in the European grayling (Thymallus thymallus) - Jana Huml; Martin Taylor; W. Harris; Robin Sen; Jonathan Ellis (Frontiers in Marine Science, 2019)

Climate change: Risk and mitigation strategies for European grayling (Thymallus thymallus) - Jana Huml; W. Harris; Martin Taylor; Robin Sen; Jonathan Ellis (Frontiers in Marine Science, 2019)

Neutral variation does not predict immunogenetic variation in the European grayling ( Thymallus thymallus) —implications for management - J. Vanessa Huml; Martin I. Taylor; W. Edwin Harris; Robin Sen; Jonathan S. Ellis (Molecular Ecology, 2018)
Preservation of genetic diversity is critical to successful conservation, and there is increasing demand for the inclusion of ecologically meaningful genetic information in management decisions. Supportive breeding programmes are increasingly implemented to combat declines in many species, yet their effect on adaptive genetic variation is understudied. This is despite the fact that supportive breeding may interfere with natural evolutionary processes. Here, we assessed the performance of neutral and adaptive markers (major histocompatibility complex; MHC ) to inform management of European grayling ( Thymallus thymallus ), which routinely involves supplementation of natural populations with hatchery‐reared fish (stocking). This study is the first to characterize MH II DAA and DAB loci in grayling and to investigate immune genetic variation in relation to management practice in this species. High‐throughput Illumina sequencing of “introduced,” “stocked native” and “non‐stocked native” populations revealed significantly higher levels of allelic richness and heterozygosity for MH markers than microsatellites exclusively in non‐stocked native populations. Likewise, significantly lower differentiation at the MH II than for microsatellites was apparent when considering non‐stocked native populations, but not stocked populations. We developed a simulation model to test the effects of relaxation of selection during the early life stage within captivity. Dependent on the census population size and stocking intensity, there may be long‐term effects of stocking on MH II , but not neutral genetic diversity. This is consistent with our empirical results. This study highlights the necessity for considering adaptive genetic variation in conservation decisions and raises concerns about the efficiency of stocking as a management practice.

A role for artificial night-time lighting in long-term changes in populations of 100 widespread macro-moths in UK and Ireland: a citizen-science study - John Fawcett Wilson; David Baker; Janet Cheney; Mike Cook; Martin Ellis; Roger Freestone; David Gardner; Graham Geen; Robin Hemming; Don Hodgers; Stephen Howarth; Ade Jupp; et al. (Journal of Insect Conservation, 2018)

Risk management to prioritise the eradication of new and emerging invasive non-native species - Olaf Booy; Aileen C. Mill; Helen E. Roy; Alice Hiley; Niall Moore; Pete Robertson; Simon Baker; Matt Brazier; Mathilde Bue; Richard Bullock; Steve Campbell; Dominic Eyre; et al. (Biological Invasions, 2017)

How to Replicate the Functions and Biodiversity of a Threatened Tree Species? The Case of Fraxinus excelsior in Britain - Ruth J. Mitchell; Robin J. Pakeman; Alice Broome; Joan K. Beaton; Paul E. Bellamy; Rob W. Brooker; Chris J. Ellis; Alison J. Hester; Nick G. Hodgetts; Glenn R. Iason; Nick A. Littlewood; Gabor Pozsgai; et al. (Ecosystems, 2016)

Qualitative Assessment of Agritourism Safety Guidelines: A Demonstration Project - Robin Tutor-Marcom; Annette Greer; Maria Clay; Tammy Ellis; Tami Thompson; Esther Seisay Adam-Samura (Journal of Agromedicine, 2013)

Brood comb as a humidity buffer in honeybee nests - Michael B. Ellis; Sue W. Nicolson; Robin M. Crewe; Vincent Dietemann (The Science of Nature, 2010)

Uncertainty in ecological status assessments of lakes and rivers using diatoms - Martyn Kelly; Helen Bennion; Amy Burgess; Julian Ellis; Steve Juggins; Robin Guthrie; Jane Jamieson; Veronique Adriaenssens; Marian Yallop (Hydrobiologia, 2009)

Monophyly of terrestrial adephagan beetles as indicated by three nuclear genes (Coleoptera: Carabidae and Trachypachidae) - David R. Maddison; Wendy Moore; Michael D. Baker; Tana M. Ellis; Karen A. Ober; Jamie J Cannone; Robin R. Gutell (Zoologica Scripta, 2009)
The beetle suborder Adephaga is traditionally divided into two sections on the basis of habitat, terrestrial Geadephaga and aquatic Hydradephaga. Monophyly of both groups is uncertain, and the relationship of the two groups has implications for inferring habitat transitions within Adephaga. Here we examine phylogenetic relationships of these groups using evidence provided by DNA sequences from all four suborders of beetles, including 60 species of Adephaga, 4 Archostemata, 3 Myxophaga, and 10 Polyphaga. We studied 18S ribosomal DNA and 28S ribosomal DNA, aligned with consideration of secondary structure, as well as the nuclear protein‐coding gene wingless . Independent and combined Bayesian, likelihood, and parsimony analyses of all three genes supported placement of Trachypachidae in a monophyletic Geadephaga, although for analyses of 28S rDNA and some parsimony analyses only if Coleoptera is constrained to be monophyletic. Most analyses showed limited support for the monophyly of Hydradephaga. Outside of Adephaga, there is support from the ribosomal genes for a sister group relationship between Adephaga and Polyphaga. Within the small number of sampled Polyphaga, analyses of 18S rDNA, wingless , and the combined matrix supports monophyly of Polyphaga exclusive of Scirtoidea. Unconstrained analyses of the evolution of habitat suggest that Adephaga was ancestrally aquatic with one transition to terrestrial. However, in analyses constrained to disallow changes from aquatic to terrestrial habitat, the phylogenies imply two origins of aquatic habit within Adephaga.

A brain-behaviour initiative for South Africa: the time is right - Dan J. Stein; Willie Daniels; Robin Emsley; Brian Harvey; Jonathan Blackburn; Paul Carey; George Ellis; Nicola Illing; Alan Flisher; Hanlie Moolman-Smook; Kelvin Mwaba; Rajkumar Ramesar; et al. (Metabolic Brain Disease, 2006)

An Aquifer Management Case Study – The Chalk of the English South Downs - N. S. Robins; H. K. Jones; J. Ellis (Water Resources Management, 1999)