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.

Modeling carbon fluxes in tidal forested wetlands in the Mississippi river deltaic plain under various hydrologic conditions: implications for river diversions - Hongqing Wang; Ken W. Krauss; Gary P. Shaffer; Brett A. Patton; Daniel E. Kroes; Gregory B. Noe; Zhaohua Dai; Lindsey Dettwiller; Carl C. Trettin (Wetlands Ecology and Management, 2026)

Population Genomics, Local Adaptation and Cryptic Speciation in a Temperate Reef Fish, the Black Surfperch, Embiotoca jacksoni , Using Genome‐Wide Resequencing - Jason A. Toy; Arthur Oulès; Gary Longo; H. Bradley Shaffer; Giacomo Bernardi (Molecular Ecology, 2025)
The black surfperch, Embiotoca jacksoni , exhibits limited dispersal due to its lack of a pelagic larval stage and offers a unique model for studying local adaptation and potential cryptic speciation in marine species. This study employs medium‐coverage whole genome resequencing to explore population structure, local adaptation, and genetic divergence across a latitudinal gradient from central California to Baja California, Mexico, including offshore islands. We identify strong genetic differentiation between five distinct groups: a coastal group and four island groups (Santa Catalina Island, San Clemente Island, Isla Guadalupe, and Isla San Jerónimo), from Principal Components Analysis (PCA), Fst estimation, ancestry (sNMF), and phylogenetic analyses. For coastal populations, genetic structure correlates with geographic distance, following isolation‐by‐distance (IBD) expectations. Further, we identify numerous outlier loci associated with adaptive traits, particularly genes linked to reproductive isolation, such as Spermine oxidase, Izumo sperm‐egg fusion protein 1, and SPAG1, which are involved in fertilisation success. These loci suggest that reproductive barriers are contributing to divergence among genetic groups. The presence of signatures of both genetic drift and selective pressures, particularly in genes governing fertilisation, indicates that these distinct populations may represent incipient or cryptic species. Our findings highlight the role of low dispersal in fostering local adaptation and speciation in marine systems and underscore the potential for rapid evolutionary responses to environmental gradients. This research provides insights into the complex processes of speciation in marine vertebrates, particularly those with limited gene flow, and offers a baseline for monitoring genetic shifts in response to climate change.

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.

Distinct patterns of altered quantitative T1ρ and functional BOLD response associated with history of suicide attempts in bipolar disorder - Joseph J. Shaffer; Virginia Willour; Jess G. Fiedorowicz; Gary E. Christensen; Jeffrey D. Long; Casey P. Johnson; Samantha L. Schmitz; Aislinn J. Williams; John Wemmie; Vincent A. Magnotta (Brain Imaging and Behavior, 2022)

Bacterial and fungal endophyte communities differ in trees of natural versus wastewater-treatment wetlands - Jennifer Janowsky; Elizabeth Kimbrough; Demetra Kandalepas; Gary Shaffer; Stephen K. Formel; Sunshine A. Van Bael (Wetlands Ecology and Management, 2019)

Response to: Turner, R.E., J.E. Bodker, and C. Schulz. 2017. The belowground intersection of nutrients and buoyancy in a freshwater marsh. Wetlands Ecology & Management: 1–9 - John W. Day; Robert R. Lane; Rachael G. Hunter; Gary P. Shaffer (Wetlands Ecology and Management, 2019)

Assessing effects of non‐native crayfish on mosquito survival - Gary M. Bucciarelli; Daniel Suh; Avery Davis Lamb; Dave Roberts; Debra Sharpton; H. Bradley Shaffer; Robert N. Fisher; Lee B. Kats (Conservation Biology, 2019)
Introductions of non‐native predators often reduce biodiversity and affect natural predator–prey relationships and may increase the abundance of potential disease vectors (e.g., mosquitoes) indirectly through competition or predation cascades. The Santa Monica Mountains (California, U.S.A.), situated in a global biodiversity hotspot, is an area of conservation concern due to climate change, urbanization, and the introduction of non‐native species. We examined the effect of non‐native crayfish ( Procambarus clarkii ) on an existing native predator, dragonfly nymphs ( Aeshna sp.), and their mosquito larvae ( Anopheles sp.) prey. We used laboratory experiments to compare the predation efficiency of both predators, separately and together, and field data on counts of dragonfly nymphs and mosquito larvae sampled from 13 local streams. We predicted a lower predation efficiency of crayfish compared with native dragonfly nymphs and a reduced predation efficiency of dragonfly nymphs in the presence of crayfish. Dragonfly nymphs were an order of magnitude more efficient predators than crayfish, and dragonfly nymph predation efficiency was reduced in the presence of crayfish. Field count data showed that populations of dragonfly nymphs and mosquito larvae were strongly correlated with crayfish presence in streams, such that sites with crayfish tended to have fewer dragonfly nymphs and more mosquito larvae. Under natural conditions, it is likely that crayfish reduce the abundance of dragonfly nymphs and their predation efficiency and thereby, directly and indirectly, lead to higher mosquito populations and a loss of ecosystem services related to disease vector control.

Impaired sensory processing measured by functional MRI in Bipolar disorder manic and depressed mood states - Joseph J. Shaffer; Casey P. Johnson; Jess G. Fiedorowicz; Gary E. Christensen; John A. Wemmie; Vincent A. Magnotta (Brain Imaging and Behavior, 2018)

Rangewide phylogeography and landscape genetics of the Western U.S. endemic frog Rana boylii (Ranidae): implications for the conservation of frogs and rivers - Amy J. Lind; Phillip Q. Spinks; Gary M. Fellers; H. Bradley Shaffer (Conservation Genetics, 2011)

How Abundant are Root-Colonizing Fungi in Southeastern Louisiana’s Degraded Marshes? - Demetra Kandalepas; Kevin J. Stevens; Gary P. Shaffer; William J. Platt (Wetlands, 2010)

The effects of submergence and light on two age classes of baldcypress (Taxodium distichum (L.) Richard) seedlings - Rebecca Faye Souther; Gary P. Shaffer (Wetlands, 2000)

The genetics of amphibian declines: population substructure and molecular differentiation in the Yosemite Toad, Bufo canorus (Anura, Bufonidae) based on single‐strand conformation polymorphism analysis (SSCP) and mitochondrial DNA sequence data - H. Bradley Shaffer; Gary M. Fellers; Allison Magee; S. Randal Voss (Molecular Ecology, 2000)
We present a comprehensive survey of genetic variation across the range of the narrowly distributed endemic Yosemite toad Bufo canorus , a declining amphibian restricted to the Sierra Nevada of California. Based on 322 bp of mitochondrial cytochrome b sequence data, we found limited support for the monophyly of B. canorus and its closely related congener B. exsul to the exclusion of the widespread western toad B. boreas . However, B. exsul was always phylogenetically nested within B. canorus , suggesting that the latter may not be monophyletic. SSCP (single‐strand conformation polymorphism) analysis of 372 individual B. canorus from 28 localities in Yosemite and Kings Canyon National Parks revealed no shared haplotypes among these two regions and lead us to interpret these two parks as distinct management units for B. canorus . Within Yosemite, we found significant genetic substructure both at the level of major drainages and among breeding ponds. Kings Canyon samples show a different pattern, with substantial variation among breeding sites, but no substructure among drainages. Across the range of B. canorus as well as among Yosemite ponds, we found an isolation‐by‐distance pattern suggestive of a stepping stone model of migration. However, in Kings Canyon we found no hint of such a pattern, suggesting that movement patterns of toads may be quite different in these nearby parklands. Our data imply that management for B. canorus should focus at the individual pond level, and effective management may necessitate reintroductions if local extirpations occur. A brief review of other pond‐breeding anurans suggests that highly structured populations are often the case, and thus that our results for B. canorus may be general for other species of frogs and toads.