Acute effects of ischemic preconditioning on maximal strength and neuromuscular function - Sean M. Lubiak; Mason A. Howard; Jeffrey T. Schmidt; Niriham M. Shah; Nihar N. Patel; Anuj J. Prajapati; Emma K. Herring; Ethan C. Hill (European Journal of Applied Physiology, 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

The University of West Florida campus ecosystem study: effects of a persistent canopy opening on regeneration of longleaf pine (Pinus palustris Mill.) - Frank S. Gilliam; Alyssa M. Sosa; Sydney A. Howard; Oliver E. Smith; Emma M. Schelonka (Environmental Monitoring and Assessment, 2026)

Reconstruction of Lateglacial and early postglacial climates and palaeoenvironments from the Trent Valley of Central England - Malcolm T. Greenwood; Paul.C. Buckland; Philip I. Buckland; G. Russell Coope; Ben Gearey; Emma. Hopla; Andy J. Howard; Angela Monckton; Paul J. Wood (Proceedings of the Geologists' Association, 2026)

The effects of temperature, urbanisation, and artificial light on phototaxis in eusocial and non-eusocial bees - Emma Webster; Leslie Ng; Kit Prendergast; Scarlett R. Howard (Journal of Insect Physiology, 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.

A Unified Framework for Trend Uncertainty Assessment in Climate Data Records: Demonstration on Global Mean Sea Level - Kevin Gobron; Roland Hohensinn; Xavier Loizeau; Claire E. Bulgin; Christopher J. Merchant; Emma R. Woolliams; Maurice G. Cox; Wouter Dorigo; Thomas Howard; Mary Langsdale; Adam C. Povey; Michaël Ablain; et al. (Surveys in Geophysics, 2026)

The Toxicology Investigators Consortium 2024 Annual Report - Kim Aldy; Shao Li; Mari Costantini; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; Michael Abesamis; Faiz Ahmed; Salman Ahsan; Peter Akpunonu; Adam Algren; et al. (Journal of Medical Toxicology, 2026)

Genomic infrastructure for cetacean research and conservation: reference genomes for eight families spanning the cetacean tree of life - Phillip A. Morin; Bernhard Bein; Chiara Bortoluzzi; Yury V. Bukhman; Taylor Hains; Dorothea Heimeier; Marcela Uliano-Silva; Dominic E. Absolon; Linelle Abueg; Jessica Antosiewicz-Bourget; Jennifer R. Balacco; Robert K. Bonde; et al. (Frontiers in Marine Science, 2025)
Reference genomes from representative species across families provide the critical infrastructure for research and conservation. The Cetacean Genomes Project (CGP) began in early 2020 to facilitate the generation of near error-free, chromosome-resolved reference genomes for all cetacean species. Towards that goal, and using the methods, goals and genome assembly quality standards of the Vertebrate Genomes Project (VGP), we generated 13 new reference genomes across eight of the 14 cetacean families. Additionally, we summarize the genome assembly characteristics for 18 species, including these newly-generated and five published genome assemblies that meet the completeness and quality standards. We infer ancestral linkage groups (ALG) for cetaceans, showing that the ancestral karyotype of 22 ALGs is largely conserved in extant species, except for Ziphiidae, and for Balaenidae and Kogiidae, which exhibit similar independent fusions. Gene annotation, characterization of historical demography, heterozygosity and runs of homozygosity (ROH) reveal important information for conservation applications. By comparing the new reference genomes to previous draft assemblies, we show that the reference genomes have enhanced characteristics that will support and promote scientific research. Specifically, the genomes improve resolution and characterization of repetitive elements, provide validation (or exclusion) of genes linked to complex traits, and allow more complete characterization of gene regions such as the highly complex Major Histocompatibility Complex (MHC) Class I and II gene clusters that are important for population health.

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.

The Toxicology Investigators Consortium 2023 Annual Report - Adrienne Hughes; Alexandra Amaducci; Sharan L. Campleman; Shao Li; Mari Costantini; Meghan B. Spyres; Hannah Spungen; Jessica Kent; Alyssa Falise; Rachel Culbreth; Paul M. Wax; Jeffery Brent; et al. (Journal of Medical Toxicology, 2024)

The Toxicology Investigators Consortium 2022 Annual Report - Alexandra M. Amaducci; Sharan L. Campleman; Shao Li; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; Rachel E. Culbreth; Paul M. Wax; Jeffrey Brent; Kim Aldy; Jennifer Acciani; et al. (Journal of Medical Toxicology, 2023)

Sexual assault and white matter hyperintensities among midlife women - Rebecca C. Thurston; Karen P. Jakubowski; Minjie Wu; Howard J. Aizenstein; Yuefang Chang; Carol A. Derby; Karestan C. Koenen; Emma Barinas-Mitchell; Pauline M. Maki (Brain Imaging and Behavior, 2022)

Cover Image: Volume 25 Number 3, March 2022 - Joseph A. Tobias; Catherine Sheard; Alex L. Pigot; Adam J. M. Devenish; Jingyi Yang; Ferran Sayol; Montague H. C. Neate‐Clegg; Nico Alioravainen; Thomas L. Weeks; Robert A. Barber; Patrick A. Walkden; Hannah E. A. MacGregor; et al. (Ecology Letters, 2022)

AVONET: morphological, ecological and geographical data for all birds - Joseph A. Tobias; Catherine Sheard; Alex L. Pigot; Adam J. M. Devenish; Jingyi Yang; Ferran Sayol; Montague H. C. Neate‐Clegg; Nico Alioravainen; Thomas L. Weeks; Robert A. Barber; Patrick A. Walkden; Hannah E. A. MacGregor; et al. (Ecology Letters, 2022)
Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species‐level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

Family history of prostate cancer and prostate tumor aggressiveness in black and non-black men;results from an equal access biopsy study - Kimberly R. Jenkins; Taofik Oyekunle; Lauren E. Howard; Emily K. Wiggins; Stephen J. Freedland; Emma H. Allott (Cancer Causes & Control, 2021)
Purpose To test for racial differences in associations between family history (FH) of prostate cancer (PC) and prostate cancer aggressiveness in a racially diverse equal access population undergoing prostate biopsy. Subjects/patients and methods We prospectively enrolled men undergoing prostate biopsy at the Durham Veterans Administration from 2007 to 2018 and assigned case or control status based on biopsy results. Race and FH of PC were self-reported on questionnaires. Logistic regression was used to test the association between FH and PC diagnosis overall and by tumor aggressiveness [high- (Grade Group 3–5) or low-grade (Grade Group 1–2) vs. no cancer], overall, and stratified by race. Models were adjusted for age and year of consent, race, PSA level, digital rectal exam findings, prostate volume, and previous (negative) biopsy receipt. Results Of 1,225 men, 323 had a FH of PC and 652 men were diagnosed with PC on biopsy. On multivariable analysis, FH was associated with increased odds of high-grade PC in black (OR 1.85, p = 0.041) and all men (OR 1.56, p = 0.057) and was unrelated to overall or low-grade PC diagnosis, overall, or stratified by race (all p ≥ 0.325). In sensitivity analyses among men without a previous biopsy, results were slightly more pronounced. Conclusion In this setting of equal access to care, positive FH of PC was associated with increased tumor aggressiveness in black men, but not non-black men undergoing prostate biopsy. Further research is required to tease apart the contribution of genetics from increased PC awareness potentially influencing screening and biopsy rates in men with FH.

Role of ocean mesoscale structures in shaping the Angola-Low pressure system and the southern Africa rainfall - Fabien Desbiolles; Emma Howard; Ross C. Blamey; Rondrotiana Barimalala; Neil C. G. Hart; Chris J. C. Reason (Climate Dynamics, 2020)

A population approach to characterise amisulpride pharmacokinetics in older people and Alzheimer’s disease - Suzanne Reeves; Julie Bertrand; Fabrizia D’Antonio; Emma McLachlan; Akshay Nair; Stuart Brownings; Suki Greaves; Alan Smith; David Taylor; Robert Howard (Psychopharmacology, 2016)

A New Toxicity Test Using the Freshwater Copepod Cyclops vernalis - Emma M. Marus; James R. Elphick; Howard C. Bailey (Bulletin of Environmental Contamination and Toxicology, 2015)

Role of salicylic acid in phosphite-induced protection against Oomycetes; a Phytophthora cinnamomi - Lupinus augustifolius model system - Emma Groves; Kay Howard; Giles Hardy; Treena Burgess (European Journal of Plant Pathology, 2015)

BRCA1/2 mutation analysis in male breast cancer families from North West England - D. G. R. Evans; Mike Bulman; Karen Young; Emma Howard; Stuart Bayliss; Andrew Wallace; Fiona Lalloo (Familial Cancer, 2008)

Molecular distinction between true centric fission and pericentric duplication-fission - Jo Perry; Sara Nouri; Phung La; Art Daniel; Zhanhe Wu; Stuart Purvis-Smith; Emma Northrop; K. H. Andy Choo; Howard R. Slater (Human Genetics, 2005)