Time in the city: long-term urban exposure predicts greater exploration and problem solving in wild red foxes - F. Blake Morton; Dylan Thompson-Jones; Kristy A. Adaway; Koko M. Sutter; Catia Matos; Georgia B. Freer; Georgia A.A. Fletcher; Carl D. Soulsbury (Animal Behaviour, 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.

Cross‐Continental Analysis Shows That Disturbance Effects on Reptile Body Condition Do Not Predict Abundance Responses - Kristina J. Macdonald; Don A. Driscoll; Michael D. Craig; Robert A. Davis; Steven J. Hromada; C. M. Gienger; Lee A. Fitzgerald; Daniel J. Leavitt; Danielle K. Walkup; Rickard Abom; Adrian F. Wayne; Gordon R. Friend; et al. (Global Change Biology, 2025)
Ecological disturbances are discrete events that alter or transform the physical, chemical, or biological characteristics of ecosystems. Disturbance can cause animal populations to decline and, according to the risk‐disturbance hypothesis and population collapse framework, these declines can be predicted by declines in animal body condition. However, no research has empirically examined the general relationship between body condition and abundance, nor their relationship in response to disturbance. We used a combined dataset representing 33 studies and > 42,000 observations of 75 species from Australia, New Zealand, Spain and the United States of America to test predictions relating to the relationship between reptile body condition and abundance. We first investigated the relationship at the site level and then used meta‐analytical models to test whether populations showed linked changes in abundance and body condition in response to disturbance. We further tested whether key environmental and species traits influenced this relationship and whether there was a time‐lagged effect of body condition responses on abundance. We found a positive relationship between mean reptile body condition and abundance at the site level. However, the relationship was largely lost when investigating population responses to disturbance. As such, our results provided no support for the risk‐disturbance hypothesis and limited support for the population collapse framework. Therefore, the impacts of disturbance on reptile body condition cannot be assumed to reflect or predict abundance responses. We provide a new conceptual framework that shows how disturbances can modify or uncouple the relationship between abundance and body condition by influencing underlying drivers, such as predation, competition and resource availability. Monitoring programs that infer population impacts based on changes in body condition should first confirm the relationship between these two variables in the relevant study system.

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.

Climate‐related variation of metabolic rate across the distribution of a broadly tolerant invasive forest pest - Sean D. Powers; Lily M. Thompson; Dylan Parry; Kristine L. Grayson; Eloy Martinez; Salvatore J. Agosta (Journal of Biogeography, 2024)
Aim Metabolic rate is a widely studied physiological species trait related to energetics, climate, and geographical distributions. Hypotheses have been proposed to explain variation in metabolic rate, but evidence has been mixed due to the limited sampling scope of intraspecific studies. Successful biological invasions offer a unique opportunity to examine the development of intraspecific physiological variation and how it relates to climate, invasive spread and species range limits. The aim of this study was to determine if metabolic rate variation across the spongy moth invasive range was consistent with a pattern of adaptation to local climate. Location Northeastern United States of America. Taxon Lymantria dispar dispar L. (Lepidoptera: Erebidae). Methods Larvae were sourced from 14 populations across the invasion front and interior of the current L. d. dispar invasive range and were reared at a constant temperature. Routine metabolic rates (RMR) of larvae were assayed at three ecologically relevant temperatures. These data were analysed to determine if there were differences in RMR and temperature sensitivity of RMR among populations. Population‐level variation in RMR was then analysed as a function of local climate and geographical position to test for patterns consistent with local adaptation. Results Larval RMR showed significant variation among populations across all assay temperatures, but there was no difference in temperature sensitivity (i.e. slope). This variation followed a positive latitudinal cline with RMR increasing from the southern range to the north. This cline also showed a significant relationship with local climate variables. Main Conclusions Larval metabolic rate variation was consistent with a pattern of adaptation by L. d. dispar to divergent climates across its invasive range. These results indicated that thermal adaptation of whole‐organism physiology may play a key role in promoting species spread and expansion for biological invasions like L. d. dispar .

Geographic and taxonomic variation in adaptive capacity among mountain-dwelling small mammals: Implications for conservation status and actions - Erik A. Beever; Jennifer L. Wilkening; Peter D. Billman; Lindsey L. Thurman; Kristina A. Ernest; David H. Wright; Alisha M. Gill; April C. Craighead; Nolan A. Helmstetter; Leona K. Svancara; Meghan J. Camp; Sabuj Bhattacharyya; et al. (Biological Conservation, 2023)

Genetic analyses of gynecological disease identify genetic relationships between uterine fibroids and endometrial cancer, and a novel endometrial cancer genetic risk region at the WNT4 1p36.12 locus - Pik Fang Kho; Sally Mortlock; Frederic Amant; Daniela Annibali; Katie Ashton; John Attia; Paul L. Auer; Matthias W. Beckmann; Amanda Black; Louise Brinton; Daniel D. Buchanan; Stephen J. Chanock; et al. (Human Genetics, 2021)

Climate‐related geographical variation in performance traits across the invasion front of a widespread non‐native insect - Lily M. Thompson; Sean D. Powers; Ashley Appolon; Petra Hafker; Lelia Milner; Dylan Parry; Salvatore J. Agosta; Kristine L. Grayson (Journal of Biogeography, 2021)
Aim Invasive species are ideal systems for testing geographical differences in performance traits and measuring evolutionary responses as a species spreads across divergent climates and habitats. The European gypsy moth, Lymantria dispar dispar L. (Lepidoptera: Erebidae), is a generalist forest defoliator introduced to Medford, Massachusetts, USA in 1869. The invasion front extends from Minnesota to North Carolina and the ability of this species to adapt to local climate may contribute to its continuing spread. We evaluated the performance of populations along the climatic gradient of the invasion front to test for a relationship between climate and ecologically important performance traits. Location Eastern United States of America Taxon Lymantria dispar dispar L. (Lepidoptera: Erebidae) Methods Insects from 14 populations across the US invasion front and interior of the invasive range were reared from hatch to adult emergence in six constant temperature treatments. The responses of survival, pupal mass and larval development time were analysed as a function of source climate (annual mean normal temperature), rearing temperature and their interaction using multiple polynomial regression. Results With the exception of female development time, there were no significant interactions between source climate and rearing temperature, indicating little divergence in the shape of thermal reaction norms among populations. Source population and rearing temperature were significant predictors of survival and pupal mass. Independent of rearing temperature, populations from warmer climates had lower survival than those from colder climates, but attained larger body size despite similar development times. Larval development time was dependent on rearing temperature, but there were not consistent relationships with source climate. Main Conclusions Thermal adaptation can be an important factor shaping the spread of invasive species, particularly in the context of climate change. Our results suggest that L. d. dispar is highly plastic, but has undergone climate‐related adaptation in thermal performance and life‐history traits as it spread across North America.

Effect of carbohydrate–protein supplementation on endurance training adaptations - Abdullah F. Alghannam; Iain Templeman; Joel E. Thomas; Dawid Jedrzejewski; Samuel Griffiths; Joseph Lemon; Thomas Byers; Sue Reeves; Javier T. Gonzalez; Dylan Thompson; James Bilzon; Kostas Tsintzas; et al. (European Journal of Applied Physiology, 2020)
Purpose To examine the influence of post-exercise protein feeding upon the adaptive response to endurance exercise training. Methods In a randomised parallel group design, 25 healthy men and women completed 6 weeks of endurance exercise training by running on a treadmill for 30–60 min at 70–75% maximal oxygen uptake ( V O 2max ) 4 times/week. Participants ingested 1.6 g per kilogram of body mass (g kg BM −1 ) of carbohydrate (CHO) or an isocaloric carbohydrate–protein solution (CHO-P; 0.8 g carbohydrate kg BM −1 + 0.8 g protein kg BM −1 ) immediately and 1 h post-exercise. Expired gas, blood and muscle biopsy samples were taken at baseline and follow-up. Results Exercise training improved V O 2max in both groups ( p ≤ 0.001), but this increment was not different between groups either in absolute terms or relative to body mass (0.2 ± 0.2 L min −1 and 3.0 ± 2 mL kg −1 min −1 , respectively). No change occurred in plasma albumin concentration from baseline to follow-up with CHO-P (4.18 ± 0.18 to 4.23 ± 0.17 g dL −1 ) or CHO (4.17 ± 0.17 to 4.12 ± 0.22 g dL −1 ; interaction: p > 0.05). Mechanistic target of rapamycin (mTOR) gene expression was up-regulated in CHO-P (+ 46%; p = 0.025) relative to CHO (+ 4%) following exercise training. Conclusion Post-exercise protein supplementation up-regulated the expression of mTOR in skeletal muscle over 6 weeks of endurance exercise training. However, the magnitude of improvement in V O 2max was similar between groups.

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.

Evolutionary genomics of gypsy moth populations sampled along a latitudinal gradient - Christopher J. Friedline; Trevor M. Faske; Brandon M. Lind; Erin M. Hobson; Dylan Parry; Rodney J. Dyer; Derek M. Johnson; Lily M. Thompson; Kristine L. Grayson; Andrew J. Eckert (Molecular Ecology, 2019)
The European gypsy moth ( Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large‐scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction‐site associated DNA sequencing and used these data to discover genome‐wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude ( F ST = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range‐edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non‐native species to invade novel environments.

Can gypsy moth stand the heat? A reciprocal transplant experiment with an invasive forest pest across its southern range margin - Trevor M. Faske; Lily M. Thompson; Nana Banahene; Andi Levorse; Melisa Quiroga Herrera; Kayla Sherman; Sarah E. Timko; Banruo Yang; David R. Gray; Dylan Parry; Patrick C. Tobin; Andrew J. Eckert; et al. (Biological Invasions, 2019)

A reduced activity model: a relevant tool for the study of ageing muscle - Oliver Perkin; Polly McGuigan; Dylan Thompson; Keith Stokes (Biogerontology, 2016)

Different responses of selected hormones to three types of exercise in young men - Keith A. Stokes; Kate L. Gilbert; George M. Hall; Robert C. Andrews; Dylan Thompson (European Journal of Applied Physiology, 2013)

Oxidative stress, inflammation and recovery of muscle function after damaging exercise: effect of 6-week mixed antioxidant supplementation - David M. Bailey; Clyde Williams; James A. Betts; Dylan Thompson; Tina L. Hurst (European Journal of Applied Physiology, 2011)

Measurement of postprandial interleukin-6 via a catheter: what does it tell us? - Dylan Thompson; Natalie Dixon (European Journal of Applied Physiology, 2009)

Reply - Dylan Thompson (European Journal of Applied Physiology, 2005)