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)

Linking Climate and Demography to Predict Population Dynamics and Persistence Under Global Change - Jennifer L. Williams; Amy L. Angert; Aldo Compagnoni; Ali Campbell; Megan L. DeMarche; Margaret E. K. Evans; Joshua C. Fowler; Edgar J. González; Amy M. Iler; Jenna A. Loesberg; Allison M. Louthan; Alexandra B. Martin; et al. (Ecology Letters, 2025)
Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of inference and projection of population dynamics. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate‐demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.

Marine data assimilation in the UK: the past, the present, and the vision for the future - Jozef Skákala; David Ford; Keith Haines; Amos Lawless; Matthew J. Martin; Philip Browne; Marcin Chrust; Stefano Ciavatta; Alison Fowler; Daniel Lea; Matthew Palmer; Andrea Rochner; et al. (Ocean Science, 2025)
In the last 2 decades, UK research institutes have led a wide range of developments in marine data assimilation (MDA), covering areas from operational applications in physics and biogeochemistry to fundamental theory. We highlight the emergence of strong collaboration in the UK MDA community over this period and the increasing unification of its tools. We focus on identifying the MDA stakeholder community and current/future areas of impact, as well as current trends and future opportunities. This includes the rapid growth of machine learning (ML)/artificial intelligence (AI) and digital-twin applications. We articulate a vision for the future, including the need for future types of observational data (whether planned missions or hypothetical) and how the community should respond to increases in computational power and new computer architectures (e.g. exascale computing). We contrast the requirements of different MDA areas, including physics, biogeochemistry, and coupled data assimilation (DA). Although the specifics of the vision depend on each area, common themes emerge. We advocate for balanced redistribution of new computational capability among increased model resolution, model complexity, more sophisticated DA algorithms, and uncertainty representation (e.g. ensembles). We also advocate for integrated approaches, such as strongly coupled DA (ocean–atmosphere, physics–biogeochemistry, and ocean–sea ice) and the use of ML/AI components (e.g. for multivariate increment balancing, bias correction, model emulation, observation re-gridding, or fusion).

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.

Hydrocarbon-degrading microbial populations in permanently cold deep-sea sediments in the NW Atlantic - Oyeboade Adebayo; Srijak Bhatnagar; Jamie Webb; Calvin Campbell; Martin Fowler; Natasha M. MacAdam; Adam Macdonald; Carmen Li; Casey R.J. Hubert (Marine Pollution Bulletin, 2024)

Evolution of white matter hyperintensity segmentation methods and implementation over the past two decades; an incomplete shift towards deep learning - Maryam Rahmani; Donna Dierker; Lauren Yaeger; Andrew Saykin; Patrick H. Luckett; Andrei G. Vlassenko; Christopher Owens; Hussain Jafri; Kyle Womack; Jurgen Fripp; Ying Xia; Duygu Tosun; et al. (Brain Imaging and Behavior, 2024)
This systematic review examines the prevalence, underlying mechanisms, cohort characteristics, evaluation criteria, and cohort types in white matter hyperintensity (WMH) pipeline and implementation literature spanning the last two decades. Following Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we categorized WMH segmentation tools based on their methodologies from January 1, 2000, to November 18, 2022. Inclusion criteria involved articles using openly available techniques with detailed descriptions, focusing on WMH as a primary outcome. Our analysis identified 1007 visual rating scales, 118 pipeline development articles, and 509 implementation articles. These studies predominantly explored aging, dementia, psychiatric disorders, and small vessel disease, with aging and dementia being the most prevalent cohorts. Deep learning emerged as the most frequently developed segmentation technique, indicative of a heightened scrutiny in new technique development over the past two decades. We illustrate observed patterns and discrepancies between published and implemented WMH techniques. Despite increasingly sophisticated quantitative segmentation options, visual rating scales persist, with the SPM technique being the most utilized among quantitative methods and potentially serving as a reference standard for newer techniques. Our findings highlight the need for future standards in WMH segmentation, and we provide recommendations based on these observations.

How uncertain and observable are marine ecosystem indicators in shelf seas? - Jozef Skákala; David Ford; Alison Fowler; Dan Lea; Matthew J. Martin; Stefano Ciavatta (Progress in Oceanography, 2024)

Australian non-perennial rivers: Global lessons and research opportunities - Margaret Shanafield; Melanie Blanchette; Edoardo Daly; Naomi Wells; Ryan M. Burrows; Kathryn Korbel; Gabriel C. Rau; Sarah Bourke; Gresley Wakelin-King; Aleicia Holland; Timothy Ralph; Gavan McGrath; et al. (Journal of Hydrology, 2024)

Developing expert scientific consensus on the environmental and societal effects of marine artificial structures prior to decommissioning - Antony M. Knights; Anaëlle J. Lemasson; Louise B. Firth; Todd Bond; Jeremy Claisse; Joop W.P. Coolen; Andrea Copping; Jennifer Dannheim; Michela De Dominicis; Steven Degraer; Michael Elliott; Paul G. Fernandes; et al. (Journal of Environmental Management, 2024)

To what extent can decommissioning options for marine artificial structures move us toward environmental targets? - Antony M. Knights; Anaëlle J. Lemasson; Louise B. Firth; Nicola Beaumont; Silvana Birchenough; Jeremy Claisse; Joop W.P. Coolen; Andrea Copping; Michela De Dominicis; Steven Degraer; Michael Elliott; Paul G. Fernandes; et al. (Journal of Environmental Management, 2024)

Multi-year seabed environmental baseline in deep-sea offshore oil prospective areas established using microbial biodiversity - Deidra K. Ferguson; Carmen Li; Anirban Chakraborty; Daniel A. Gittins; Martin Fowler; Jamie Webb; Calvin Campbell; Natasha Morrison; Adam MacDonald; Casey R.J. Hubert (Marine Pollution Bulletin, 2023)

Elevated bacterial endospores associated with thermogenic hydrocarbon seeps in deep sea sediments - Jayne E. Rattray; Gretta Elizondo; Kathryn Sloan; Natasha Morrison; Martin Fowler; Daniel A. Gittins; Jamie Webb; D. Calvin Campbell; Adam MacDonald; Casey R.J. Hubert (Organic Geochemistry, 2023)

Bacterial anomalies associated with deep sea hydrocarbon seepage along the Scotian Slope - Carmen Li; Oyeboade Adebayo; Deidra K. Ferguson; Scott Wang; Jayne E. Rattray; Martin Fowler; Jamie Webb; Calvin Campbell; Natasha Morrison; Adam MacDonald; Casey R.J. Hubert (Deep Sea Research Part I: Oceanographic Research Papers, 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.

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.

Progress in Prediction and Interpretation of Clinically Relevant Metabolic Drug-Drug Interactions: a Minireview Illustrating Recent Developments and Current Opportunities - Stephen Fowler; Peter N. Morcos; Yumi Cleary; Meret Martin-Facklam; Neil Parrott; Michael Gertz; Li Yu (Current Pharmacology Reports, 2017)

Performance on the Cogstate Brief Battery Is Related to Amyloid Levels and Hippocampal Volume in Very Mild Dementia - Yen Ying Lim; Victor L. Villemagne; Simon M. Laws; Robert H. Pietrzak; David Ames; Christopher Fowler; Stephanie Rainey-Smith; Peter J. Snyder; Pierrick Bourgeat; Ralph N. Martins; Olivier Salvado; Christopher C. Rowe; et al. (Journal of Molecular Neuroscience, 2016)

Dinosaur teeth from the Jurassic Qigu and Shishugou Formations of the Junggar Basin (Xinjiang/China) and their paleoecologic implications - Oliver Wings; Thomas Tütken; Denver W. Fowler; Thomas Martin; Hans-Ulrich Pfretzschner; Ge Sun (PalZ, 2015)

The Goals and Research of the BioEnergy Sciences Center (BESC): Developing Cost-effective and Sustainable Means of Producing Biofuels by Overcoming Biomass Recalcitrance - Brian H. Davison; Martin Keller; V. Suzy Fowler (BioEnergy Research, 2009)

Phylogeographic differentiation in the mitochondrial control region in the koala, Phascolarctos cinereus (Goldfuss 1817) - Bronwyn A. Houlden; Brian H. Costello; Deirdre Sharkey; Elizabeth V. Fowler; Alistair Melzer; William Ellis; Frank Carrick; Peter R. Baverstock; Martin S. Elphinstone (Molecular Ecology, 1999)
The koala, Phascolarctos cinereus , is a geographically widespread species endemic to Australia, with three currently recognized subspecies: P.c. adustus , P.c. cinereus , and P.c. victor . Intraspecific variation in the mitochondrial DNA (mtDNA) control region was examined in over 200 animals from 16 representative populations throughout the species’ range. Eighteen different haplotypes were defined in the ≈ 860 bp mtDNA control region, as determined by heteroduplex analysis/temperature gradient gel electrophoresis (HDA/TGGE). Any single population typically possessed only one or two haplotypes yielding an average within‐population haplotypic diversity of 0.180 ± 0.003, and nucleotide diversity of 0.16%. Overall, mtDNA control region sequence diversity between populations averaged 0.67%, and ranged from 0% to 1.56%. Nucleotide divergence between populations averaged 0.51%, and ranged from 0% to 1.53%. Neighbour‐joining methods revealed limited phylogenetic distinction between geographically distant populations of koalas, and tentative support for a single evolutionarily significant unit (ESU). This is consistent with previous suggestions that the morphological differences formalized by subspecific taxonomy may be interpreted as clinal variation. Significant differentiation in mtDNA‐haplotype frequencies between localities suggested that little gene flow currently exists among populations. When combined with microsatellite analysis, which has revealed substantial differentiation among koala populations, we conclude that the appropriate short‐term management unit (MU) for koalas is the local population.