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.

Estimates of rotation periods for Jupiter Trojans with the Zwicky Transient Facility photometric lightcurves - Zhuofu (Chester) Li; Yasin A. Chowdhury; Željko Ivezić; Ashish Mahabal; Ari Heinze; Lynne Jones; Mercedes S. Thompson; Eric Bellm; Mario Jurić; Andrew J. Connolly; Bryce Bolin; Frank J. Masci; et al. (Icarus, 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.

Net ecosystem carbon budget and net greenhouse gas emissions under diverse crop rotation using cover crops compared to a conventional crop rotation - Keerthika N. Ranathunga; Jacob Evans; Nikolett Toth; Shannon Brown; Laura L. Van Eerd; Claudia Wagner-Riddle (Agriculture, Ecosystems & Environment, 2025)

Cover crops increase belowground N retention substantially in corn cropping systems: Results from a 15N residue swapping experiment - Spencer M. Heuchan; Claudia Wagner-Riddle; Khagendra R. Baral; Katelyn A. Congreves; Richard E. Farrell; Sean Jordan; Hugh A. L. Henry (Plant and Soil, 2025)

Increased N2O emissions by cover crops in a diverse crop rotation can be mediated with dual nitrification and urease inhibitors - Azeem Tariq; Nicole Menheere; Yuanpei Gao; Shannon Brown; Laura L. Van Eerd; John D. Lauzon; Sander Bruun; Claudia Wagner-Riddle (Agriculture, Ecosystems & Environment, 2024)

Snow removal and cover crops influence soil nitrogen transfer to the subsequent corn crop - Spencer M. Heuchan; Claudia Wagner-Riddle; Hugh A. L. Henry (Plant and Soil, 2024)

Distance Education in Nutrition and Dietetics Education over the Past 30 Years: A Narrative Review - Jennifer L. Bueche; Jennifer M.K. Jensen; Kelly Martin; Emily Riddle; Kim S. Stote (Journal of the Academy of Nutrition and Dietetics, 2023)

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.

Predicting Bird Guilds Using Vegetation Composition and Structure on a Wild and Scenic River in Arizona - Erin S. Cubley; Heather L. Bateman; Sidney B. Riddle; Chris Holmquist-Johnson; David M. Merritt (Wetlands, 2020)

Eurasian snow cover variability and links to winter climate in the CMIP5 models - Jason C. Furtado; Judah L. Cohen; Amy H. Butler; Emily E. Riddle; Arun Kumar (Climate Dynamics, 2015)

Climate change and Southern Ocean ecosystems I: how changes in physical habitats directly affect marine biota - Andrew J. Constable; Jessica Melbourne‐Thomas; Stuart P. Corney; Kevin R. Arrigo; Christophe Barbraud; David K. A. Barnes; Nathaniel L. Bindoff; Philip W. Boyd; Angelika Brandt; Daniel P. Costa; Andrew T. Davidson; Hugh W. Ducklow; et al. (Global Change Biology, 2014)
Antarctic and Southern Ocean ( ASO ) marine ecosystems have been changing for at least the last 30 years, including in response to increasing ocean temperatures and changes in the extent and seasonality of sea ice; the magnitude and direction of these changes differ between regions around Antarctica that could see populations of the same species changing differently in different regions. This article reviews current and expected changes in ASO physical habitats in response to climate change. It then reviews how these changes may impact the autecology of marine biota of this polar region: microbes, zooplankton, salps, Antarctic krill, fish, cephalopods, marine mammals, seabirds, and benthos. The general prognosis for ASO marine habitats is for an overall warming and freshening, strengthening of westerly winds, with a potential pole‐ward movement of those winds and the frontal systems, and an increase in ocean eddy activity. Many habitat parameters will have regionally specific changes, particularly relating to sea ice characteristics and seasonal dynamics. Lower trophic levels are expected to move south as the ocean conditions in which they are currently found move pole‐ward. For Antarctic krill and finfish, the latitudinal breadth of their range will depend on their tolerance of warming oceans and changes to productivity. Ocean acidification is a concern not only for calcifying organisms but also for crustaceans such as Antarctic krill; it is also likely to be the most important change in benthic habitats over the coming century. For marine mammals and birds, the expected changes primarily relate to their flexibility in moving to alternative locations for food and the energetic cost of longer or more complex foraging trips for those that are bound to breeding colonies. Few species are sufficiently well studied to make comprehensive species‐specific vulnerability assessments possible. Priorities for future work are discussed.

Gas emissions from liquid dairy manure: complete versus partial storage emptying - J. D. Wood; A. C. VanderZaag; C. Wagner-Riddle; E. L. Smith; R. J. Gordon (Nutrient Cycling in Agroecosystems, 2014)

Effect of fendiline on the maintenance and expression of methamphetamine-induced conditioned place preference in Sprague–Dawley rats - Robin M. Voigt; Jennifer L. Riddle; T. Celeste Napier (Psychopharmacology, 2014)

Light‐driven tipping points in polar ecosystems - Graeme F. Clark; Jonathan S. Stark; Emma L. Johnston; John W. Runcie; Paul M. Goldsworthy; Ben Raymond; Martin J. Riddle (Global Change Biology, 2013)
Some ecosystems can undergo abrupt transformation in response to relatively small environmental change. Identifying imminent ‘tipping points’ is crucial for biodiversity conservation, particularly in the face of climate change. Here, we describe a tipping point mechanism likely to induce widespread regime shifts in polar ecosystems. Seasonal snow and ice‐cover periodically block sunlight reaching polar ecosystems, but the effect of this on annual light depends critically on the timing of cover within the annual solar cycle. At high latitudes, sunlight is strongly seasonal, and ice‐free days around the summer solstice receive orders of magnitude more light than those in winter. Early melt that brings the date of ice‐loss closer to midsummer will cause an exponential increase in the amount of sunlight reaching some ecosystems per year. This is likely to drive ecological tipping points in which primary producers (plants and algae) flourish and out‐compete dark‐adapted communities. We demonstrate this principle on Antarctic shallow seabed ecosystems, which our data suggest are sensitive to small changes in the timing of sea‐ice loss. Algae respond to light thresholds that are easily exceeded by a slight reduction in sea‐ice duration. Earlier sea‐ice loss is likely to cause extensive regime shifts in which endemic shallow‐water invertebrate communities are replaced by algae, reducing coastal biodiversity and fundamentally changing ecosystem functioning. Modeling shows that recent changes in ice and snow cover have already transformed annual light budgets in large areas of the A rctic and A ntarctic, and both aquatic and terrestrial ecosystems are likely to experience further significant change in light. The interaction between ice‐loss and solar irradiance renders polar ecosystems acutely vulnerable to abrupt ecosystem change, as light‐driven tipping points are readily breached by relatively slight shifts in the timing of snow and ice‐loss.

CFSv2 ensemble prediction of the wintertime Arctic Oscillation - Emily E. Riddle; Amy H. Butler; Jason C. Furtado; Judah L. Cohen; Arun Kumar (Climate Dynamics, 2013)

The impact of the MJO on clusters of wintertime circulation anomalies over the North American region - Emily E. Riddle; Marshall B. Stoner; Nathaniel C. Johnson; Michelle L. L’Heureux; Dan C. Collins; Steven B. Feldstein (Climate Dynamics, 2013)

Role of hypoxia-inducible factor-1α in angiogenic–osteogenic coupling - Ryan C. Riddle; Richa Khatri; Ernestina Schipani; Thomas L. Clemens (Journal of Molecular Medicine, 2009)

Effects of a Caenorhabditis elegans Dauer Pheromone Ascaroside on Physiology and Signal Transduction Pathways - Marco Gallo; Donald L. Riddle (Journal of Chemical Ecology, 2009)

Intensive measurement of nitrous oxide emissions from a corn–soybean–wheat rotation under two contrasting management systems over 5 years - CLAUDIA WAGNER‐RIDDLE; ADRIANA FURON; NICOLE L. MCLAUGHLIN; IVAN LEE; JOHN BARBEAU; SUSANTHA JAYASUNDARA; GARY PARKIN; PETER Von BERTOLDI; JON WARLAND (Global Change Biology, 2007)
No‐tillage (NT), a practice that has been shown to increase carbon sequestration in soils, has resulted in contradictory effects on nitrous oxide (N 2 O) emissions. Moreover, it is not clear how mitigation practices for N 2 O emission reduction, such as applying nitrogen (N) fertilizer according to soil N reserves and matching the time of application to crop uptake, interact with NT practices. N 2 O fluxes from two management systems [conventional (CP), and best management practices: NT + reduced fertilizer (BMP)] applied to a corn ( Zea mays L.), soybean ( Glycine max L.), winter‐wheat ( Triticum aestivum L.) rotation in Ontario, Canada, were measured from January 2000 to April 2005, using a micrometeorological method. The superimposition of interannual variability of weather and management resulted in mean monthly N 2 O fluxes ranging from − 1.9 to 61.3 g N ha −1 day −1 . Mean annual N 2 O emissions over the 5‐year period decreased significantly by 0.79 from 2.19 kg N ha −1 for CP to 1.41 kg N ha −1 for BMP. Growing season (May–October) N 2 O emissions were reduced on average by 0.16 kg N ha −1 (20% of total reduction), and this decrease only occurred in the corn year of the rotation. Nongrowing season (November–April) emissions, comprised between 30% and 90% of the annual emissions, mostly due to increased N 2 O fluxes during soil thawing. These emissions were well correlated ( r 2 = 0.90) to the accumulated degree‐hours below 0 °C at 5 cm depth, a measure of duration and intensity of soil freezing. Soil management in BMP (NT) significantly reduced N 2 O emissions during thaw (80% of total reduction) by reducing soil freezing due to the insulating effects of the larger snow cover plus corn and wheat residue during winter. In conclusion, significant reductions in net greenhouse gas emissions can be obtained when NT is combined with a strategy that matches N application rate and timing to crop needs.

Travel Distance and Season of Diagnosis Affect Treatment Choices for Women with Early-stage Breast Cancer in A Predominantly Rural Population (United States) - Maria O. Celaya; Judy R. Rees; Jennifer J. Gibson; Bruce L. Riddle; E. Robert Greenberg (Cancer Causes & Control, 2006)

Mechanisms of methamphetamine-induced dopaminergic neurotoxicity - Evan L. Riddle; Annette E. Fleckenstein; Glen R. Hanson (The AAPS Journal, 2006)

Role of monoamine transporters in mediating psychostimulant effects - Evan L. Riddle; Annette E. Fleckenstein; Glen R. Hanson (The AAPS Journal, 2005)

Toward Improved Coefficients for Predicting Direct N2O Emissions from Soil in Canadian Agroecosystems - B. L. Helgason; H. H. Janzen; M. H. Chantigny; C. F. Drury; B. H. Ellert; E. G. Gregorich; R. L. Lemke; E. Pattey; P. Rochette; C. Wagner-Riddle (Nutrient Cycling in Agroecosystems, 2005)

Biochemical evidence for a P2Y-like receptor in Tetrahymena thermophila - B. N. Rosner; J. N. Bartholomew; C. D. Gaines; M. L. Riddle; H. A. Everett; K. G. Rulapaugh; L. E. Nickerson; M. R. Marshall; H. G. Kuruvilla (Journal of Comparative Physiology A, 2003)

Identification of mustelids using mitochondrial DNA and non-invasive sampling - Ann E. Riddle*; Kristine L. Pilgrim; L. Scott Mills; Kevin S. McKelvey; Leonard F. Ruggiero (Conservation Genetics, 2003)

Ploidy race distributions since the Last Glacial Maximum in the North American desert shrub, Larrea tridentata - Kimberly L. Hunter; Julio L. Betancourt; Brett R. Riddle; Thomas R. Van Devender; Kenneth L. Cole; W. Geoffrey Spaulding (Global Ecology and Biogeography, 2001)
A classic biogeographic pattern is the alignment of diploid, tetraploid and hexaploid races of creosote bush ( Larrea tridentata ) across the Chihuahuan, Sonoran and Mohave Deserts of western North America. We used statistically robust differences in guard cell size of modern plants and fossil leaves from packrat middens to map current and past distributions of these ploidy races since the Last Glacial Maximum (LGM). Glacial/early Holocene (26–10 14 C kyr bp or thousands of radiocarbon years before present) populations included diploids along the lower Rio Grande of west Texas, 650 km removed from sympatric diploids and tetraploids in the lower Colorado River Basin of south‐eastern California/south‐western Arizona. Diploids migrated slowly from lower Rio Grande refugia with expansion into the northern Chihuahuan Desert sites forestalled until after ~4.0 14 C kyr bp . Tetraploids expanded from the lower Colorado River Basin into the northern limits of the Sonoran Desert in central Arizona by 6.4 14 C kyr bp . Hexaploids appeared by 8.5 14 C kyr bp in the lower Colorado River Basin, reaching their northernmost limits (~37°N) in the Mohave Desert between 5.6 and 3.9 14 C kyr bp . Modern diploid isolates may have resulted from both vicariant and dispersal events. In central Baja California and the lower Colorado River Basin, modern diploids probably originated from relict populations near glacial refugia. Founder events in the middle and late Holocene established diploid outposts on isolated limestone outcrops in areas of central and southern Arizona dominated by tetraploid populations. Geographic alignment of the three ploidy races along the modern gradient of increasingly drier and hotter summers is clearly a postglacial phenomenon, but evolution of both higher ploidy races must have happened before the Holocene. The exact timing and mechanism of polyploidy evolution in creosote bush remains a matter of conjecture.