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

Fertility classification of the cow and peri-estrus sex-steroid hormones is associated with endometrial epithelial cell responses to conceptus and inflammatory signals - Cecilia Constantino Rocha; Mariangela Bueno Cordeiro Maldonado; Fernando S. Mesquita; Alexandra Bennett; Abdul Waheed; Graciana R. Mendina; Gabriela Lomba Dasqueve; Felipe A. C. C. Silva; Marcelo Fábio Gouveia Nogueira; Alan D. Ealy; Thomas Hansen; Mario Binelli (Cell and Tissue Research, 2026)

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.

Bomb radiocarbon reveals keratin growth dynamics in loggerhead (Caretta caretta) and green (Chelonia mydas) turtles - Bethan Linscott; Amy A. Wallace; Lorena Becerra-Valdivia; Matt R. P. Harris; Alexandra L. Fireman; Jenna D. Bennett; William F. Patterson; Hannah B. Vander Zanden (Marine Biology, 2026)
Incrementally formed biological tissues can serve as archives of biochemical information pertaining to the life histories of organisms. The sequential isotopic analysis of marine turtle scute keratin is increasingly used for ecological reconstruction, but the timescales represented by these tissues remain poorly understood. Here, we present a method to establish scute growth rates using sequential radiocarbon ( 14 C) measurements on samples taken from loggerhead ( Caretta caretta ) and green turtles ( Chelonia mydas ) stranded along the Florida coast. Using a Δ 14 C coral-otolith reference series and a Bayesian modelling approach, we reconstructed the rate of keratin formation in 24 individuals (representing 120 radiocarbon measurements) and detected synchronous declines in scute growth rates that may be linked to marine environmental stress. Our results provide a chronological framework for the ecological interpretation of biogeochemical data from green and loggerhead turtle scutes and demonstrate the potential for 14 C analysis to investigate the growth dynamics of other incremental tissues.

Beyond growth: Reshaping fisheries for a wellbeing economy - Ingrid Kelling; Nathan Bennett; Kate Barclay; Andrew Jeffs; Cristina Pita; Birgitte Krogh-Poulsen; Tobias Troll; Evgenia Micha; Julia Cirne Lima Weston; Iain Black; Ibrahim Lawan; Alexandra Leeper; et al. (Marine Policy, 2026)

Assessment and prediction of embryo survival in fertility-classified beef cows - Alexandra Bennett; Cecilia Constantino Rocha; Abdul Waheed; Fernando S. Mesquita; Tatiane S. Maia; McKenzie Lane-Jackson Haimon; Quinn A. Hoorn; Masroor Sagheer; Camila J. Cuellar; Halima Sultana; Oscar Alejandro Ojeda-Rojas; Rebecca Lynn Krisher; et al. (Theriogenology, 2026)

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.

Relationships between activity monitoring device data and ovarian, uterine, hormonal, and pregnancy variables in beef cows - Cecilia Constantino Rocha; Ana Beatriz Montevecchio; Alexandra Bennett; Abdul Waheed; Mackenzie Mazziotta; Tatiane S. Maia; McKenzie Lane-Jackson Haimon; Quinn A. Hoorn; Masroor Sagheer; Camila J. Cuellar; Oscar Alejandro Ojeda-Rojas; Rebecca Lynn Krisher; et al. (Theriogenology, 2025)

Land Use Change Consistently Reduces α‐ But Not β‐ and γ‐Diversity of Bees - Toby P. N. Tsang; A. A. Amado De Santis; Gabriela Armas‐Quiñonez; John S. Ascher; Eva Samanta Ávila‐Gómez; András Báldi; Kimberly M. Ballare; Mario V. Balzan; Weronika Banaszak‐Cibicka; Svenja Bänsch; Yves Basset; Adam J. Bates; et al. (Global Change Biology, 2025)
Land use change threatens global biodiversity and compromises ecosystem functions, including pollination and food production. Reduced taxonomic α‐diversity is often reported under land use change, yet the impacts could be different at larger spatial scales (i.e., γ‐diversity), either due to reduced β‐diversity amplifying diversity loss or increased β‐diversity dampening diversity loss. Additionally, studies often focus on taxonomic diversity, while other important biodiversity components, including phylogenetic diversity, can exhibit differential responses. Here, we evaluated how agricultural and urban land use alters the taxonomic and phylogenetic α‐, β‐, and γ‐diversity of an important pollinator taxon—bees. Using a multicontinental dataset of 3117 bee assemblages from 157 studies, we found that taxonomic α‐diversity was reduced by 16%–18% in both agricultural and urban habitats relative to natural habitats. Phylogenetic α‐diversity was decreased by 11%–12% in agricultural and urban habitats. Compared with natural habitats, taxonomic and phylogenetic β‐diversity increased by 11% and 6% in urban habitats, respectively, but exhibited no systematic change in agricultural habitats. We detected a 22% decline in taxonomic γ‐diversity and a 17% decline in phylogenetic γ‐diversity in agricultural habitats, but γ‐diversity of urban habitats was not significantly different from natural habitats. These findings highlight the threat of agricultural expansions to large‐scale bee diversity due to systematic γ‐diversity decline. In addition, while both urbanization and agriculture lead to consistent declines in α‐diversity, their impacts on β‐ or γ‐diversity vary, highlighting the need to study the effects of land use change at multiple scales.

Dual column chromatography combined with high-resolution mass spectrometry improves coverage of non-targeted analysis of plant root exudates - Alexandra A. Bennett; Teresa Steininger-Mairinger; Çağla Görkem Eroğlu; Aurélie Gfeller; Judith Wirth; Markus Puschenreiter; Stephan Hann (Analytica Chimica Acta, 2024)

Harnessing water fleas for water reclamation: A nature-based tertiary wastewater treatment technology - Muhammad Abdullahi; Iestyn Stead; Sophie Bennett; Rafael Orozco; Mohamed Abou-Elwafa Abdallah; Sara Jabbari; Lynne E. Macaskie; Alexandra Tzella; Stefan Krause; Bushra Al-Duri; Robert G. Lee; Ben Herbert; et al. (Science of The Total Environment, 2023)

Consequences of in vitro benzyl butyl phthalate exposure for blubber gene expression and insulin-induced Akt activation in juvenile grey seals - Alexandra Tranganida; Ailsa J. Hall; Holly C. Armstrong; Simon E.W. Moss; Kimberley A. Bennett (Environmental Pollution, 2023)

Testing a global standard for quantifying species recovery and assessing conservation impact - Molly K. Grace; H. Resit Akçakaya; Elizabeth L. Bennett; Thomas M. Brooks; Anna Heath; Simon Hedges; Craig Hilton‐Taylor; Michael Hoffmann; Axel Hochkirch; Richard Jenkins; David A. Keith; Barney Long; et al. (Conservation Biology, 2021)
Recognizing the imperative to evaluate species recovery and conservation impact, in 2012 the International Union for Conservation of Nature (IUCN) called for development of a “Green List of Species” (now the IUCN Green Status of Species). A draft Green Status framework for assessing species’ progress toward recovery, published in 2018, proposed 2 separate but interlinked components: a standardized method (i.e., measurement against benchmarks of species’ viability, functionality, and preimpact distribution) to determine current species recovery status (herein species recovery score ) and application of that method to estimate past and potential future impacts of conservation based on 4 metrics ( conservation legacy, conservation dependence , conservation gain , and recovery potential ). We tested the framework with 181 species representing diverse taxa, life histories, biomes, and IUCN Red List categories (extinction risk). Based on the observed distribution of species’ recovery scores, we propose the following species recovery categories : fully recovered, slightly depleted, moderately depleted, largely depleted, critically depleted, extinct in the wild, and indeterminate. Fifty‐nine percent of tested species were considered largely or critically depleted. Although there was a negative relationship between extinction risk and species recovery score, variation was considerable. Some species in lower risk categories were assessed as farther from recovery than those at higher risk. This emphasizes that species recovery is conceptually different from extinction risk and reinforces the utility of the IUCN Green Status of Species to more fully understand species conservation status. Although extinction risk did not predict conservation legacy, conservation dependence, or conservation gain, it was positively correlated with recovery potential. Only 1.7% of tested species were categorized as zero across all 4 of these conservation impact metrics , indicating that conservation has, or will, play a role in improving or maintaining species status for the vast majority of these species. Based on our results, we devised an updated assessment framework that introduces the option of using a dynamic baseline to assess future impacts of conservation over the short term to avoid misleading results which were generated in a small number of cases, and redefines short term as 10 years to better align with conservation planning. These changes are reflected in the IUCN Green Status of Species Standard.

Multidisciplinary perspectives on medication-related decision-making for people with advanced dementia living in long-term care: a critical incident analysis - Domenica Disalvo; Tim Luckett; Alexandra Bennett; Patricia M. Davidson; Meera Agar (European Journal of Clinical Pharmacology, 2020)

Continental‐scale variation in seaweed host‐associated bacterial communities is a function of host condition, not geography - Ezequiel M. Marzinelli; Alexandra H. Campbell; Enrique Zozaya Valdes; Adriana Vergés; Shaun Nielsen; Thomas Wernberg; Thibaut de Bettignies; Scott Bennett; J. Gregory Caporaso; Torsten Thomas; Peter D. Steinberg (Environmental Microbiology, 2015)
Summary Interactions between hosts and associated microbial communities can fundamentally shape the development and ecology of ‘holobionts’, from humans to marine habitat‐forming organisms such as seaweeds. In marine systems, planktonic microbial community structure is mainly driven by geography and related environmental factors, but the large‐scale drivers of host‐associated microbial communities are largely unknown. Using 16S‐r RNA gene sequencing, we characterized 260 seaweed‐associated bacterial and archaeal communities on the kelp E cklonia radiata from three biogeographical provinces spanning 10° of latitude and 35° of longitude across the Australian continent. These phylogenetically and taxonomically diverse communities were more strongly and consistently associated with host condition than geographical location or environmental variables, and a ‘core’ microbial community characteristic of healthy kelps appears to be lost when hosts become stressed. Microbial communities on stressed individuals were more similar to each other among locations than those on healthy hosts. In contrast to biogeographical patterns of planktonic marine microbial communities, host traits emerge as critical determinants of associated microbial community structure of these holobionts, even at a continental scale.

A checklist for ecological management of landscapes for conservation - David Lindenmayer; Richard J. Hobbs; Rebecca Montague‐Drake; Jason Alexandra; Andrew Bennett; Mark Burgman; Peter Cale; Aram Calhoun; Viki Cramer; Peter Cullen; Don Driscoll; Lenore Fahrig; et al. (Ecology Letters, 2008)
The management of landscapes for biological conservation and ecologically sustainable natural resource use are crucial global issues. Research for over two decades has resulted in a large literature, yet there is little consensus on the applicability or even the existence of general principles or broad considerations that could guide landscape conservation. We assess six major themes in the ecology and conservation of landscapes. We identify 13 important issues that need to be considered in developing approaches to landscape conservation. They include recognizing the importance of landscape mosaics (including the integration of terrestrial and aquatic areas), recognizing interactions between vegetation cover and vegetation configuration, using an appropriate landscape conceptual model, maintaining the capacity to recover from disturbance and managing landscapes in an adaptive framework. These considerations are influenced by landscape context, species assemblages and management goals and do not translate directly into on‐the‐ground management guidelines but they should be recognized by researchers and resource managers when developing guidelines for specific cases. Two crucial overarching issues are: (i) a clearly articulated vision for landscape conservation and (ii) quantifiable objectives that offer unambiguous signposts for measuring progress.