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.

Solvent-based mid-infrared spectroscopy paired with modern machine learning approaches for saffron authentication - Hadi Parastar; Linus Busse; Andreas Wolf; Philipp Weller (Food Research International, 2025)

Genomic diversity and environmental factors associated with Listeria monocytogenes presence in surface water - Magaly Toro; Daniel Weller; Camila Solar; Ana María Quesille-Villalobos; Hee Yin Kwon; Aiko Adell; Andrea Moreno-Switt; Yi Chen; Rebecca L. Bell; Jianghong Meng; Angélica Reyes-Jara (Science of The Total Environment, 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.

Integrated petrographical and petrophysical studies of sandstones from the Araba Formation for reservoir characterization - Mohamed Kassab; Andreas Weller; Hesham Abuseda (Arabian Journal of Geosciences, 2022)
The present study aims at an integration of both petrographic and petrophysical data of 45 sandstone samples collected from Araba Formation (Lower Paleozoic) for reservoir characterization. The studied Araba Formation is classified into three types of facies: (i) quartz arenite, (ii) sublithic quartz arenite, and (iii) calcareous quartz arenite. The mineralogical composition of the studied sandstone samples includes mainly quartz and detrital clays, some pyrite, and iron oxides as cement. The petrographic investigation of the studied Araba Formation reveals various diagenetic processes including compaction and pressure solution, cementation with iron oxides, carbonates, or clays. The porosity values for investigated samples range from 14.5 to 27.8% and permeability values from 2.4 mD to 8.4 D, the surface area per unit pore volume ( S por ) from 0.011 to 17 µm −1 , the formation factor from 6 to 13, and the dimensionless volumetric magnetic susceptibility from 13 10 −6 to 126 10 −6 . The samples of facies (i) and (ii) are characterized by higher values of porosity and permeability. The samples of facies (iii) indicate increasing permeability with rising porosity. The relationship between permeability and formation factor reflects the effect of porosity changes. The specific surface S por shows an inverse relationship to permeability. The petrophysical investigations provide relationships between permeability and other reservoir parameters such as porosity, formation factor, specific surface, and longitudinal and transverse relaxation time resulting from nuclear magnetic resonance (NMR) relaxometry. The permeability prediction model based on NMR data proves to be applicable for samples from facies (i) and (ii), whereas the predictive quality is considerably lower for facies (iii).

Global Observing Needs in the Deep Ocean - Lisa A. Levin; Brian J. Bett; Andrew R. Gates; Patrick Heimbach; Bruce M. Howe; Felix Janssen; Andrea McCurdy; Henry A. Ruhl; Paul Snelgrove; Karen I. Stocks; David Bailey; Simone Baumann-Pickering; et al. (Frontiers in Marine Science, 2019)

Fractal dimension of pore space in carbonate samples from Tushka area (Egypt) - Yi Ding; Andreas Weller; Zeyu Zhang; Mohamed Kassab (Arabian Journal of Geosciences, 2017)

Petrographic and petrophysical investigation on carbonate samples (Upper Cretaceous) from the Tushka Area (Egypt) with special focus on the effective pore radius - Ümit Öner; Andreas Weller; Carl-Diedrich Sattler; Mohamed A. Kassab (Arabian Journal of Geosciences, 2016)

Petrographical and petrophysical investigations of upper cretaceous sandstones of the South West Sennan field, Western Desert, Egypt - Hesham Abuseda; Andreas Weller; Carl-Diedrich Sattler; Wolfgang Debschütz (Arabian Journal of Geosciences, 2016)

Permeability prediction of four Egyptian sandstone formations - Andreas Weller; Mohamed A. Kassab; Wolfgang Debschütz; Carl-Diedrich Sattler (Arabian Journal of Geosciences, 2014)

Dynamics of soil water content in the rhizosphere - Andrea Carminati; Ahmad B. Moradi; Doris Vetterlein; Peter Vontobel; Eberhard Lehmann; Ulrich Weller; Hans-Jörg Vogel; Sascha E. Oswald (Plant and Soil, 2010)

The Nasca and Palpa geoglyphs: geophysical and geochemical data - Kerstin Hartsch; Andreas Weller; Silvia Rosas; Gunter Reppchen (The Science of Nature, 2009)

Distinct patterns of genetic variation in Pristionchus pacificus and Caenorhabditis elegans , two partially selfing nematodes with cosmopolitan distribution - HANS ZAUNER; WERNER E. MAYER; MATTHIAS HERRMANN; ANDREAS WELLER; MIRJA ERWIG; RALF J. SOMMER (Molecular Ecology, 2007)
Hermaphroditism has evolved several times independently in nematodes. The model organism Caenorhabditis elegans and Pristionchus pacificus are self‐fertile hermaphrodites with rare facultative males. Both species are members of different families: C. elegans belongs to the Rhabditidae and P. pacificus to the Diplogastridae. Also, both species differ in their ecology: C. elegans is a soil‐dwelling nematode that is often found in compost heaps. In contrast, field studies in Europe and North America indicate that Pristionchus nematodes are closely associated with scarab beetles. In C. elegans, several recent studies have found low genetic diversity and rare out‐crossing events. Little is known about diversity levels and population structure in free‐living hermaphroditic nematodes outside the genus Caenorhabditis . Taking a comparative approach, we analyse patterns of molecular diversity and linkage disequilibrium in 18 strains of P. pacificus from eight countries and four continents. Mitochondrial sequence data of P. pacificus isolates reveal a substantially higher genetic diversity on a global scale when compared to C. elegans . A mitochondrial‐derived hermaphrodite phylogeny shows little geographic structuring, indicating several worldwide dispersal events. Amplified fragment length polymorphism and single strand conformation polymorphism analyses demonstrate a high degree of genome‐wide linkage disequilibrium, which also extends to the mitochondrial genome. Together, these findings indicate distinct patterns of genetic variation of the two species. The low level of genetic diversity observed in C. elegans might reflect a recent human‐associated dispersal, whereas the P. pacificus diversity might reflect a long‐lasting and ongoing insect association. Thus, despite similar lifestyle characteristics in the laboratory, the reproductive mode of hermaphroditism with rare facultative males can result in distinct genetic variability patterns in different ecological settings.

Zum Fortgang des Nationalatlas Bundesrepublik Deutschland - Alois Mayr; Sabine Tzschaschel; Michael Weller; Andreas Deutsch (KN - Journal of Cartography and Geographic Information, 1999)