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.

The effect of Asparagopsis oil supplementation level on tissue residues and meat quality of Merino sheep fed high- or low-quality basal diets - Charlotte Adam; Emma Doyle; Jillian Dawson; Frances Cowley; Nigel Tomkins; Lewis Kahn; James Preston; Daniel Korir Sitienei; Matthew Tom Harrison; Benjamin W.B. Holman (Small Ruminant Research, 2026)

Opportunities to better integrate inland fish and fisheries in multilateral environmental agreements - Abigail J. Lynch; Devin Bartley; T. Douglas Beard, Jr.; Gabriel Borba; Steven J. Cooke; Ian G. Cowx; Vittoria Elliott; Holly Embke; Edith Gondwe; Zeb Hogan; Jonathan G. Low; Jamie C. Madden; et al. (Environmental Science & Policy, 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.

Overcoming Shifting Baselines: Paleo‐Behaviour Reveals Industrial Revolution as Tipping Point - Julian Lilkendey; Jens Hegg; Matthew Campbell; Jingjing Zhang; Harrison Raby; Malcolm Reid; Monica Tromp; Emma Ash; Louise Furey; Lindsey White; Richard Walter; Armagan Sabetian (Global Change Biology, 2025)
Human activities have significantly altered coastal ecosystems worldwide. The phenomenon of shifting baselines syndrome (SBS) complicates our understanding of these changes, masking the true scale of human impacts. This study investigates the long‐term ecological effects of anthropogenic activities on New Zealand's coastal ecosystems over 800 years using fish otolith microchemical profiling and dynamic time warping across an entire stock unit. Results reveal a shift in snapper ( Chrysophrys auratus ; Sparidae) habitat‐use behaviour, transitioning from low‐salinity estuarine environments to higher‐salinity habitats, correlating with ongoing land‐use changes. This shift coincided with New Zealand's localised Industrial Revolution, which served as a tipping point for widespread ecosystem transformation. By comparing current coastal fish movement profiles with historical baselines, we provide evidence to address SBS and guide conservation strategies. Re‐establishing pre‐industrial habitat‐use behaviours in snapper will indicate successful habitat restoration, promoting overall ecosystem connectivity and resilience. Our findings enable more effective habitat restoration measures and sustainable management practices, informing policies for maintaining coastal biodiversity and ecosystem function.

Time-resolved fluorescence of oils and oil distillates in artificial seawater at low excitation wavelengths: Assessing the use of lifetimes to decouple oil and dissolved organic matter (DOM) fluorophores in natural waters - Warren J. de Bruyn; Aaron W. Harrison; Emma Kocik; Dhivya Manickam; Ethan Truong; Catherine D. Clark (Marine Pollution Bulletin, 2024)

Sex differences in the association between skeletal muscle energetics and perceived physical fatigability: the Study of Muscle, Mobility and Aging (SOMMA) - Emma L. Gay; Paul M. Coen; Stephanie Harrison; Reagan E. Garcia; Yujia Qiao; Bret H. Goodpaster; Daniel E. Forman; Frederico G. S. Toledo; Giovanna Distefano; Philip A. Kramer; Sofhia V. Ramos; Anthony J. A. Molina; et al. (GeroScience, 2024)

Defying the flat-Earth myth: Soil organic carbon monitoring in topographically complex temperate pasture landscapes - Franco Bilotto; Ronaldo Vibart; Alec Mackay; Dongwen Luo; Zachary Dewhurst; Brian Devantier; Emma Noakes; Matthew Tom Harrison (CATENA, 2024)

Adverse consequences of herbicide residues on legumes in dryland agriculture - Ronald J. Yates; Emma J. Steel; Tom J. Edwards; Robert J. Harrison; Belinda F. Hackney; John G. Howieson (Field Crops Research, 2024)

Genetic variation is associated with differences in facilitative and competitive interactions in the Rhizobium leguminosarum species complex - Bryden Fields; Emma K. Moffat; Ellie Harrison; Stig U. Andersen; J. Peter W. Young; Ville‐Petri Friman (Environmental Microbiology, 2022)
Summary Competitive and facilitative interactions influence bacterial community composition, diversity and functioning. However, the role of genetic diversity for determining interactions between coexisting strains of the same, or closely related, species remains poorly understood. Here, we investigated the type (facilitative/inhibitory) and potential underlying mechanisms of pairwise interactions between 24 genetically diverse bacterial strains belonging to three genospecies (gsA,C,E) of the Rhizobium leguminosarum species complex. Interactions were determined indirectly, based on secreted compounds in cell‐free supernatants, and directly, as growth inhibition in cocultures. We found supernatants mediated both facilitative and inhibitory interactions that varied greatly between strains and genospecies. Overall, gsE strains indirectly suppressed growth of gsA strains, while their own growth was facilitated by other genospecies' supernatants. Similar genospecies‐level patterns were observed in direct competition, where gsA showed the highest susceptibility and gsE the highest inhibition capacity. At the genetic level, increased gsA susceptibility was associated with a non‐random distribution of quorum sensing and secondary metabolite genes across genospecies. Together, our results suggest that genetic variation is associated with facilitative and competitive interactions, which could be important ecological mechanisms explaining R . leguminosarum diversity.

Entering Negotiations: Early-Career Perspectives on the UN Conference of Parties and the Unfolding Climate Crisis - Erica M. Ferrer; Leticia M. Cavole; Simona Clausnitzer; Daniela F. Dias; Tashiana C. Osborne; Rishi Sugla; Emma Harrison (Frontiers in Marine Science, 2021)
As the pressure to address the climate crisis builds, scientists must walk the line between research and activism. This was apparent at the 2019 United Nations (UN) Framework Convention on Climate Change – Conference of the Parties (UNFCCC – COP), the largest annual meeting to address the climate crisis via supranational policymaking. COP has convened annually since 1995 in effort to establish international agreements for the reduction of greenhouse gas emissions, and in 2015, was the launch pad for the UN Paris Climate Agreement (PCA). Here, we present our collective perspective as early-career researchers on COP, an institution that we believe plays a critical role in the future of our oceans. Given the current pledges from signatories to the PCA, Earth is expected to warm ∼3°C by 2100, with the majority of anthropogenic heat content stored throughout the ocean. For this reason, among others, we feel it is crucial for ocean scientists to have a baseline understanding of the negotiations unfolding at COP and within the UNFCCC. We also provide evidence that certain features/structures of COP formalize colonial hierarchies, marginalize certain groups, and threaten to perpetuate the drivers of the environmental crises we all face. Thus, we urge that the future of such gatherings include purposeful and self-reflective acts of restructuring the space they occupy, the solutions they advocate, and the ways in which power is distributed amongst participants. We balance our critique with examples of how this has already been successful at COP, particularly with respect to organizing around ocean-climate issues.

Multi-frequency bioimpedance: a non-invasive tool for muscle-health assessment of adults with cerebral palsy - Jessica Pingel; Adrian Harrison; Ferdinand Von Walden; Emma Hjalmarsson; Else Marie Bartels (Journal of Muscle Research and Cell Motility, 2020)

Systematic review and meta-analysis of the associations between body mass index, prostate cancer, advanced prostate cancer, and prostate-specific antigen - Sean Harrison; Kate Tilling; Emma L. Turner; Richard M. Martin; Rosie Lennon; J. Athene Lane; Jenny L. Donovan; Freddie C. Hamdy; David E. Neal; J. L. H. Ruud Bosch; Hayley E. Jones (Cancer Causes & Control, 2020)
Purpose The relationship between body mass index (BMI) and prostate cancer remains unclear. However, there is an inverse association between BMI and prostate-specific antigen (PSA), used for prostate cancer screening. We conducted this review to estimate the associations between BMI and (1) prostate cancer, (2) advanced prostate cancer, and (3) PSA. Methods We searched PubMed and Embase for studies until 02 October 2017 and obtained individual participant data from four studies. In total, 78 studies were identified for the association between BMI and prostate cancer, 21 for BMI and advanced prostate cancer, and 35 for BMI and PSA. We performed random-effects meta-analysis of linear associations of log-PSA and prostate cancer with BMI and, to examine potential non-linearity, of associations between categories of BMI and each outcome. Results In the meta-analyses with continuous BMI, a 5 kg/m 2 increase in BMI was associated with a percentage change in PSA of − 5.88% (95% CI − 6.87 to − 4.87). Using BMI categories, compared to normal weight men the PSA levels of overweight men were 3.43% lower (95% CI − 5.57 to − 1.23), and obese men were 12.9% lower (95% CI − 15.2 to − 10.7). Prostate cancer and advanced prostate cancer analyses showed little or no evidence associations. Conclusion There is little or no evidence of an association between BMI and risk of prostate cancer or advanced prostate cancer, and strong evidence of an inverse and non-linear association between BMI and PSA. The association between BMI and prostate cancer is likely biased if missed diagnoses are not considered.

TRY plant trait database – enhanced coverage and open access - Jens Kattge; Gerhard Bönisch; Sandra Díaz; Sandra Lavorel; Iain Colin Prentice; Paul Leadley; Susanne Tautenhahn; Gijsbert D. A. Werner; Tuomas Aakala; Mehdi Abedi; Alicia T. R. Acosta; George C. Adamidis; et al. (Global Change Biology, 2020)
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Investigating the prostate specific antigen, body mass index and age relationship: is an age–BMI-adjusted PSA model clinically useful? - Sean Harrison; Kate Tilling; Emma L. Turner; J. Athene Lane; Andrew Simpkin; Michael Davis; Jenny Donovan; Freddie C. Hamdy; David E. Neal; Richard M. Martin (Cancer Causes & Control, 2016)

Green and hawksbill turtles in the Lesser Antilles demonstrate behavioural plasticity in inter-nesting behaviour and post-nesting migration - Nicole Esteban; Robert P. van Dam; Emma Harrison; Arturo Herrera; Jessica Berkel (Marine Biology, 2015)

Erratum to: Cancer Health Professionals Need Funding, Time, Research Knowledge and Skills to be Involved in Health Services Research - Claire Johnson; Catalina Lizama; Megan Harrison; Emma Bayly; Joshua Bowyer; Livia Haddow (Journal of Cancer Education, 2014)

Cancer Health Professionals Need Funding, Time, Research Knowledge and Skills to be Involved in Health Services Research - Claire Johnson; Catalina Lizama; Megan Harrison; Emma Bayly; Joshua Bowyer (Journal of Cancer Education, 2014)

Abiotic drivers and plant traits explain landscape‐scale patterns in soil microbial communities - Franciska T. de Vries; Pete Manning; Jerry R. B. Tallowin; Simon R. Mortimer; Emma S. Pilgrim; Kathryn A. Harrison; Phil J. Hobbs; Helen Quirk; Bill Shipley; Johannes H. C. Cornelissen; Jens Kattge; Richard D. Bardgett (Ecology Letters, 2012)
The controls on aboveground community composition and diversity have been extensively studied, but our understanding of the drivers of belowground microbial communities is relatively lacking, despite their importance for ecosystem functioning. In this study, we fitted statistical models to explain landscape‐scale variation in soil microbial community composition using data from 180 sites covering a broad range of grassland types, soil and climatic conditions in England. We found that variation in soil microbial communities was explained by abiotic factors like climate, pH and soil properties. Biotic factors, namely community‐weighted means (CWM) of plant functional traits, also explained variation in soil microbial communities. In particular, more bacterial‐dominated microbial communities were associated with exploitative plant traits versus fungal‐dominated communities with resource‐conservative traits, showing that plant functional traits and soil microbial communities are closely related at the landscape scale.

Pacific Rim Forestry / Silviculture and Forest Ecology - Vishal Singh Negi; Archana Pal; Ratnesh Singh; Dulal Borthakur; Archana Pala; Vishal Singh Negi; Dulal Borthakur; Isabel Rushanaedy; Tyler Jones; Nicklos Dudley; Dulal Borthakur; Jannai Yafuso; et al. (Journal of Forestry, 2011)
Leucaena leucocephala (leucaena) is an important agroforestry tree of tropics and subtropics due to its protein rich foliages, ability to grow on poor soils, and high level of tolerance to various stresses including drought and diseases. We hypothesized that leucaena have a unique set of genes which confer tolerance to various abiotic and biotic stresses and these genes are either absent or not expressed in other legumes that are susceptible to these stress conditions. Interspecies suppression subtractive hybridization (iSSH) was performed to identify some unique genes from leucaena using cDNAs from leucaena and Acacia confusa (acacia) as the tester and driver, respectively. We identified 100 leucaena genes showing homology to various plant genes with known functions, of which 23 genes had homology to various stress-related proteins including chitinase, PR-10 protein, wound-stress protein, type-2 metallothionein, thaumatin-like protein, disease resistance response protein, cysteine proteinase, and kunitz trypsin inhibitor. We also identified 50 leucaena genes which either had homology to hypothetical proteins (HyPs) or had no homology at all. Putative functions of 15 HyPs were predicted using conserved domain and PSI-BLAST analyses. Linear motif analyses identified 17 HyPs with MAPK recognition motif, which is involved in signaling pathways, including stress responses. This study identified 23 known and some putative unique stress-related genes from leucaena which may serve as a useful source of stress-tolerance genes for tree and crop improvement in the future.

Migration of green turtles Chelonia mydas from Tortuguero, Costa Rica - Sebastian Troëng; Daniel R. Evans; Emma Harrison; Cynthia J. Lagueux (Marine Biology, 2005)