Insights on the heterogeneity of thermal transfer in the chalk aquifer using fibre-optic distributed temperature sensing - Katerina Kyrkou; Joseph Kelly; Adam Booth; Fleur Loveridge; David Boon; Edward Hough; Lawrence Scott; Matthew Jackson; Adrian Butler; Daniel Perez; Athena Chalari (Geothermics, 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

SNAPSHOT USA 2024: Year 6 of the Coordinated National Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Daniel J. Herrera; Camilla Price; Phuong‐Thao Nguyen‐Nu; Katrina Adamczyk; Peter D. Alexander; David Allen; Jesse M. Alston; Diego F. Alvarado‐Serrano; et al. (Global Ecology and Biogeography, 2026)
Motivation SNAPSHOT USA is an annual, multi‐contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2024 comprises two .csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.

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.

Most recent surface rupturing earthquake on the Boulder Creek Fault triggered bedrock landslides in the Nooksack River watershed, Whatcom County, Washington - Abigail Underwood; Adam Booth; Sean LaHusen; Erich Herzig; Alison Duvall; Geoffrey Malick; Doug Clark; Ashley Streig (Geomorphology, 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.

Physiological Traits for Predicting Poleward Extensions in Tropical Fishes: From Lab to Management - Adam T. Downie; Curtis Champion; David J. Booth (Global Change Biology, 2025)
Tropicalization, the phenomena by which tropical organisms are extending their distributions poleward into temperate latitudes in response to increasing temperatures and strengthening boundary currents, is occurring globally. Vagrant tropical species have large ecological and economic ramifications for the temperate habitats they invade. However, not all vagrants are able to persist long term in temperate habitats, with the first winter being a potential bottleneck for their persistence. This brings into question how some tropical vagrant species are successful at surviving temperate conditions and the physiology underpinning this success. This provides the opportunity to not only look at the available data introspectively but also forward‐thinking by applying a range of holistic physiological traits relevant for biology and management. Therefore, the aim of our review is twofold: to review the current state‐of‐knowledge of the physiological mechanisms underpinning tropicalization and to develop a physiological framework by which current practices can complement new perspectives and tools. We use range‐expanding tropical reef fishes as a model group of over 100 species undergoing climate‐driven range shifts and eastern Australia as a case‐study location due to it being a primary focal “living laboratory” for understanding tropicalization dynamics since the early 2000s. Current studies suggest that diet, behavior, and metabolic trade‐offs may explain vagrant fish persistence, but these studies focus on whole‐animal traits. Our framework helps expand upon focal traits, life stages, experimental design, physiological traits (e.g., we highlight the value of genetic and cellular markers for metabolic pathway changes under cold stress as potential biomarkers) and species to improve our understanding of the mechanisms underpinning tropicalization. Taken together, our framework places emphasis on measuring a suite of complimentary physiological traits, from cellular to whole‐animal, to help guide future predictions of the long‐term persistence of tropical species in temperate habitats.

Combination and summary of ATLAS dark matter searches interpreted in a 2HDM with a pseudo-scalar mediator using 139 fb−1 of s = 13 TeV pp collision data - G. Aad; B. Abbott; K. Abeling; N.J. Abicht; S.H. Abidi; A. Aboulhorma; H. Abramowicz; H. Abreu; Y. Abulaiti; A.C. Abusleme Hoffman; B.S. Acharya; C. Adam Bourdarios; et al. (Science Bulletin, 2024)

Subglacial bedform and moat initiation beneath Rutford Ice Stream, West Antarctica - Rebecca Schlegel; Alex M. Brisbourne; Andrew M. Smith; Adam D. Booth; Tavi Murray; Edward C. King; Roger A. Clark (Geomorphology, 2024)

The 3D response of a large-scale masonry arch bridge – Part II: Performance at failure - Bowen Liu; Vasilis Sarhosis; Adam D. Booth; Matthew Gilbert (Engineering Structures, 2024)

The sensitivity of seismic refraction velocity models to survey geometry errors, assessed using Monte Carlo analysis - Hannah Watts; Adam D. Booth; Roger A. Clark; Benedict T.I. Reinardy (Journal of Applied Geophysics, 2023)

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)

Unveiling buried aeolian landscapes: reconstructing a late Holocene dune environment using 3D ground‐penetrating radar - Luis Rees‐Hughes; Natasha L. M. Barlow; Adam D. Booth; Landis J. West; George Tuckwell; Tim Grossey (Journal of Quaternary Science, 2021)
Across the UK, sandy beaches and dunes protect coastal infrastructure from waves and extreme water levels during large‐scale storms, while providing important habitats and recreational opportunities. Understanding their long‐term evolution is vital in managing their condition in a changing climate. Recently, ground‐penetrating radar (GPR) methods have grown in popularity in geomorphological applications, yielding centimetre‐scale resolution images of near‐surface stratigraphy and structure, thus allowing landscape evolution to be reconstructed. Additionally, abrupt changes in palaeo‐environments can be visualized in three dimensions. Although often complemented by core data, GPR allows interpretations to be extended into areas with minimal ground‐truth control. Nonetheless, GPR data interpretation can be non‐intuitive and ambiguous, and radargrams may not initially resemble the expected subsurface geometry. Interpretation can be made yet more onerous when handling the large 3D data volumes that are facilitated with modern GPR technology. Here we describe the development of novel semi‐automated GPR feature‐extraction tools, based on ‘edge detection’ and ‘thresholding’ methods, which detect regions of increased GPR reflectivity which can be applied to aid in the reconstruction of a range Quaternary landscapes. Since reflectivity can be related to lithological and/or pore fluid changes, the 3D architecture of the palaeo‐landscape can be reconstructed from the features extracted from a geophysical dataset. We present 500 MHz GPR data collected over a buried Holocene coastal dune system in North Wales, UK, now reclaimed for use as an airfield. Core data from the site, reaching a maximum depth 2 m, suggest rapid vertical changes from sand to silty‐organic units, and GPR profiles suggest similar lateral complexity. By applying thresholding methods to GPR depth slices, these lateral complexities are effectively and automatically mapped. Furthermore, automatic extraction of the local reflection power yields a strong correlation with the depth variation of organic content, suggesting it is a cause of reflectivity contrast. GPR‐interpolated analyses away from core control thus offer a powerful proxy for parameters derived from invasive core logging. The GPR data collected at Llanbedr airfield highlight a complex dune system to a depth of 2.8 m, probably deposited in several phases over ~700 years, similar to elsewhere in North Wales.

The Hooskanaden Landslide: historic and recent surge behavior of an active earthflow on the Oregon Coast - Stefano Alberti; Andrew Senogles; Kara Kingen; Adam Booth; Pete Castro; Jill DeKoekkoek; Kira Glover-Cutter; Curran Mohney; Michael Olsen; Ben Leshchinsky (Landslides, 2020)

In situ recovery of bivalve shell characteristics after temporary exposure to elevated p CO 2 - Jason Grear; Adam Pimenta; Harriet Booth; Doranne Borsay Horowitz; Wilson Mendoza; Matthew Liebman (Limnology and Oceanography, 2020)
Ocean uptake of carbon dioxide (CO 2 ) is causing changes in carbonate chemistry that affects calcification in marine organisms. In coastal areas, this CO 2 ‐enriched seawater mixes with waters affected by seasonal degradation of organic material loaded externally from watersheds or produced as a response to nutrient enrichment. As a result, coastal bivalves often experience strong seasonal changes in carbonate chemistry. In some cases, these changes may resemble those experienced by aquacultured bivalves during translocation activities. We mimicked these changes by exposing juvenile hard clams (500 μ m, Mercenaria mercenaria ) to p CO 2 in laboratory upwellers at levels resembling those already reported for northeastern U.S. estuaries (mean upweller p CO 2 = 773, 1274, and 1838 μ atm) and then transplanting to three grow‐out sites along an expected nutrient gradient in Narragansett Bay, Rhode Island (154 bags of 100 clams). Prior to the field grow‐out, clams exposed to elevated p CO 2 exhibited larger shells but lower dry weight per unit volume (dw/V). However, percent increase in dw/V was highest for this group during the 27‐day field grow‐out, suggesting that individuals with low dw/V after the laboratory treatment accelerated accumulation of dw/V when they were transferred to the bay. Treatments also appeared to affect shell mineral structure and condition of digestive diverticula. Although treatment effects diminished during the field grow‐out, clams that were preexposed for several weeks to high p CO 2 would likely have been temporarily vulnerable to predation or other factors that interact with shell integrity. This would be expected to reduce population recovery from short‐term exposures to high p CO 2 .

Multi-year, three-dimensional landslide surface deformation from repeat lidar and response to precipitation: Mill Gulch earthflow, California - Adam M. Booth; Justin C. McCarley; Joann Nelson (Landslides, 2020)

Integrating diverse geologic and geodetic observations to determine failure mechanisms and deformation rates across a large bedrock landslide complex: the Osmundneset landslide, Sogn og Fjordane, Norway - Adam M. Booth; John Dehls; Trond Eiken; Luzia Fischer; Reginald L. Hermanns; Thierry Oppikofer (Landslides, 2015)

Lithium carbonate in the management of cannabis withdrawal: a randomized placebo-controlled trial in an inpatient setting - Jennifer Johnston; Nicholas Lintzeris; David J. Allsop; Anastasia Suraev; Jessica Booth; Dean S. Carson; David Helliwell; Adam Winstock; Iain S. McGregor (Psychopharmacology, 2014)

Changing forest water yields in response to climate warming: results from long‐term experimental watershed sites across North America - Irena F. Creed; Adam T. Spargo; Julia A. Jones; Jim M. Buttle; Mary B. Adams; Fred D. Beall; Eric G. Booth; John L. Campbell; Dave Clow; Kelly Elder; Mark B. Green; Nancy B. Grimm; et al. (Global Change Biology, 2014)
Climate warming is projected to affect forest water yields but the effects are expected to vary. We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long‐term experimental catchments across Canada and the United States over 5‐year cool and warm periods. Using the theoretical framework of the Budyko curve, we calculated the effects of climate warming on the annual partitioning of precipitation ( P ) into evapotranspiration ( ET ) and water yield. Deviation ( d ) was defined as a catchment's change in actual ET divided by P [ AET / P ; evaporative index ( EI )] coincident with a shift from a cool to a warm period – a positive d indicates an upward shift in EI and smaller than expected water yields, and a negative d indicates a downward shift in EI and larger than expected water yields. Elasticity was defined as the ratio of interannual variation in potential ET divided by P ( PET / P ; dryness index) to interannual variation in the EI – high elasticity indicates low d despite large range in drying index (i.e., resilient water yields), low elasticity indicates high d despite small range in drying index (i.e., nonresilient water yields). Although the data needed to fully evaluate ecosystems based on these metrics are limited, we were able to identify some characteristics of response among forest types. Alpine sites showed the greatest sensitivity to climate warming with any warming leading to increased water yields. Conifer forests included catchments with lowest elasticity and stable to larger water yields. Deciduous forests included catchments with intermediate elasticity and stable to smaller water yields. Mixed coniferous/deciduous forests included catchments with highest elasticity and stable water yields. Forest type appeared to influence the resilience of catchment water yields to climate warming, with conifer and deciduous catchments more susceptible to climate warming than the more diverse mixed forest catchments.

Imaging glacial sediment inclusions in 3‐D using ground‐penetrating radar at Kongsvegen, Svalbard - Tavi Murray; Adam D. Booth (Journal of Quaternary Science, 2010)
The quiescent‐phase surge‐type glacier, Kongsvegen, flows confluent with the continuously fast‐flowing Kronebreen in northwestern Spitsbergen. The lower regions of Kongsvegen overlie glaciomarine sediments, which have been incorporated into the ice during multiple surge events. The resulting englacial structures are exposed at the surface and on a cliff section. These structures have variously been interpreted as thrusts, formed by compression, or sediment‐filled crevasses, formed by extension. We collected a grid of closely spaced ground‐penetrating radar profiles in the area adjacent to the cliff section. Several structures were imaged in 3‐D, including a strong subhorizontal basal reflector, which was underlain by a second, weaker subhorizontal reflector. The basal reflector was occasionally reverse faulted, suggesting compression. Clear englacial features extended upwards from it, dipping up‐glacier at angles of