Dependence of subseasonal to seasonal precipitation prediction on atmospheric and land initial conditions in the Energy Exascale Earth System Model - Dongze Xu; Zhaoxia Pu; Shixuan Zhang; Jeffrey Anderson; L. Ruby Leung (Climate Dynamics, 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

Monitoring beach face morphology from stereo satellite imagery - Shannon Brown; Annika O'Dea; Jeffrey Ruby; Erwin W.J. Bergsma; Rafael Almar; Katherine Brodie (Coastal Engineering, 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.

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)

Multivariate environmental and trait-based controls of transpiration in the Central Amazon Rainforest - Yilin Fang; Cristina Santos da Silva; Adam Collins; Bruno O. Gimenez; Kolby Jardine; Robinson I. Negrón-Juárez; Regison Oliveira; Valdiek da Silva Menezes; Kurt Solander; Gustavo Spanner; Jeffrey M. Warren; Cynthia L. Wright; et al. (Agricultural and Forest Meteorology, 2026)

Have popular ready meals become more obesogenic? Little change in energy density and carbohydrate-to-fat ratio over a 15-year period - Ruby L. Pallon; Jeffrey M. Brunstrom; Annika N. Flynn; Callum McBride (Appetite, 2025)

The Cost of Antivenom: A Cost Minimization Study using the North American Snakebite Registry - Benjamin Herzel; Neev Batavia; Paul Gavaza; Tammy Phan; Emmelyn Samones; Anne-Michelle Ruha; Jakub Furmaga; Christopher Hoyte; Brian J. Wolk; Peter Akpunonu; Adam Algren; Alexandra Amaducci; et al. (Journal of Medical Toxicology, 2025)
Envenomation is a global health issue, with over 9,000 encounters managed in the United States yearly. The introduction of immunoglobulin fragment antivenom has reduced the risk of hypersensitivity. This study compares treatment costs of crotaline envenomation using the Fab and F(ab’) 2 antivenoms as reported to the North American Snakebite Registry (NASBR), a nationwide surveillance tool. Methods This was a retrospective analysis of NASBR data between 2018 and 2020. The following data points were assessed: patient demographics (age, gender, race), snake species, type of antivenom used, and treatment costs. Unit costs were estimated based on United States Centers for Medicare and Medicaid Services data. Average (mean) per patient costs from the payer perspective were calculated by multiplying resources by the unit costs. Sensitivity analyses were performed regarding cost variance and snake species. All costs reported in this study are in U.S. dollars. Results The average total cost of treatment was $31,343 per person, with medications contributing 72% of the total. Average total cost among patients who received Fab treatments was $33,347 per person compared to $19,747 among patients who received F(ab’) 2 . Antivenom costs accounted for 75% of the total cost in the Fab group and 42% in the F(ab’) 2 group. F(ab’) 2 required more vials than Fab (median 18 versus 10). Non-antivenom costs such as hospitalizations were higher in the F(ab’) 2 group. Using average sale prices increased average total cost to $52,572; Fab remained more expensive. Conclusion Antivenom is the primary cost driver in snakebite treatment in North America. Treatment with F(ab’) 2 resulted in lower overall costs, driven by lower cost of antivenom. F(ab’) 2 did not significantly lower overall resource use except for blood product administration.

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.

Systemic toxicity after rattlesnake envenomation in patients using angiotensin converting enzyme inhibitors: A North American Snakebite Registry study - A.M. Ruha; M.B. Spyres; R. Culbreth; B. Wolk; C. Hoyte; S. Campleman; Peter Akpunonu; Adam Algren; Alexandra Amaducci; Sukhshant Atti; Connie Aubin; Kevin Baumgartner; et al. (Toxicon, 2025)

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)

The Toxicology Investigators Consortium Case Registry—the 2021 Annual Report - Jennifer S. Love; Dana L. Karshenas; Meghan B. Spyres; Lynn A. Farrugia; A. Min Kang; HoanVu Nguyen; Sharan L. Campleman; Shao Li; Paul M. Wax; Jeffery Brent; Kim Aldy; Michael Abesamis; et al. (Journal of Medical Toxicology, 2022)