Characterizing ferrous versus ferric iron in Alzheimer's disease using X-ray fluorescence imaging and XANES spectroscopy Dean Tran, Marios Georgiadis, Philip DiGiacomo, Jeff Nirschl, Inma Cobos, et al. Journal of Alzheimer S Disease, 2026 Background The accumulation of iron, such as ferrous Fe 2+ , in the Alzheimer's disease (AD) brain may contribute to neurodegeneration by driving oxidative stress. While elevated iron in AD has been shown, the oxidation state of iron and its regional distribution in AD, particularly in the hippocampus, is unclear. Objective To characterize the oxidation state and spatial distribution of iron in the hippocampus of AD and control brains, and to assess the effect of tissue thawing on ferrous iron measurements. Methods We utilized X-ray fluorescence imaging and X-ray absorption near edge structure spectroscopy to localize and analyze iron deposition in fresh-frozen human hippocampal specimens stratified by AD disease stage. To assess the effect of thawing on iron oxidation, we used a cryo-chamber to keep three specimens frozen while their respective deposits were being scanned. These specimens were then allowed to thaw and their same deposits were rescanned for comparison. Results Compared to control brains, AD specimens exhibited elevated levels of ferrous iron (Fe 2 + ) in the cornu ammonis 1 (CA1)-subiculum subfields—regions known to degenerate early in AD. We also measured a decrease in Fe 2+ levels in AD and control specimens scanned after being thawed. Conclusions Our findings support the association between elevated Fe 2+ and AD, consistent with existing hypotheses linking redox-active iron to oxidative stress and neuroinflammation. The observed reduction in Fe 2+ levels following thawing suggests that studies using thawed brain samples may underestimate Fe 2+ levels.
AI-enabled virtual spatial proteomics from histopathology for interpretable biomarker discovery in lung cancer Zhe Li, Yuchen Li, Jinxi Xiang, Xiyue Wang, Sen Yang, et al. Nature Medicine, 2026 Spatial proteomics enables high-resolution mapping of protein expression and can transform our understanding of biology and disease. However, major challenges remain for clinical translation, including cost, complexity and scalability. Here we present H&E to protein expression (HEX), an AI model designed to computationally generate spatial proteomics profiles from standard histopathology slides. Trained and validated on 819,000 histopathology image tiles with matched protein expression from 382 tumor samples, HEX accurately predicts the expression of 40 biomarkers encompassing immune, structural and functional programs. HEX demonstrates substantial performance gains over alternative methods for protein expression prediction from H&E images. We develop a multimodal data integration approach that combines the original H&E image and AI-derived virtual spatial proteomics to enhance outcome prediction. Applied to six independent non-small-cell lung cancer cohorts totaling 2,298 patients, HEX-enabled multimodal integration improved prognostic accuracy by 22% and immunotherapy response prediction by 24–39% compared with conventional clinicopathological and molecular biomarkers. Biological interpretation revealed spatially organized tumor–immune niches predictive of therapeutic response, including the co-localization of T helper cells and cytotoxic T cells in responders, and immunosuppressive tumor-associated macrophage and neutrophil aggregates in non-responders. HEX provides a low-cost and scalable approach to study spatial biology and enables the discovery and clinical translation of interpretable biomarkers for precision medicine.
Micron-resolution fiber mapping in histology independent of sample preparation Marios Georgiadis, Franca auf der Heiden, Hamed Abbasi, Loes Ettema, Jeffrey Nirschl, et al. Nature Communications, 2025 Mapping the brain’s fiber network is crucial for understanding its function and malfunction, but resolving nerve trajectories over large fields of view is challenging. Here, we show that computational scattered light imaging (ComSLI) can map fiber networks in histology independent of sample preparation, also in formalin-fixed paraffin-embedded (FFPE) tissues including whole human brain sections. We showcase this method in new and archived, animal and human brain sections, for different sample preparations (in paraffin, deparaffinized, various stains, unstained fresh-frozen). We convert microscopic orientations to microstructure-informed fiber orientation distributions (μFODs). Adapting tractography tools from diffusion magnetic resonance imaging (dMRI), we trace axonal trajectories revealing white and gray matter connectivity. These allow us to identify altered microstructure or deficient tracts in demyelinating or neurodegenerating pathology, and to show key advantages over dMRI, polarization microscopy, and structure tensor analysis. Finally, we map fibers in non-brain tissues, including muscle, bone, and blood vessels, unveiling the tissue’s function. Our cost-effective, versatile approach enables micron-resolution studies of intricate fiber networks across tissues, species, diseases, and sample preparations, offering new dimensions to neuroscientific and biomedical research.
Precise MRI-histology coregistration of paraffin-embedded tissue with blockface imaging Yixin Wang, William Ho, Istvan N. Huszar, Phillip DiGiacomo, Hossein Moein Taghavi, et al. Imaging Neuroscience, 2025 Magnetic resonance imaging (MRI) provides 3D spatial information on tissue, yet it lacks at the molecular level. In contrast, histology provides cellular and molecular information, but it lacks the 3D spatial context and direct in vivo translation. Coregistering the two is key for the 3D embedding of histological details, validating pathological MRI findings, and identifying quantitative imaging biomarkers of neurodegenerative diseases. However, coregistration is challenging due to non-linear distortions of the tissue from histological processing and sectioning leading to microscopic and macroscopic nonlinear 3D deformations between specimen MRI and stained histology sections. To address this, we developed a novel pipeline, named Brewster’s Blockface Quantification (BBQ), integrating robust optical approaches with innovative 2D and 3D registration algorithms to achieve precise volumetric alignment of specimen MRI data with histological images. On a variety of brain tissue specimens from distinct anatomical regions and across multiple species, our methodology generated blockface volumes with minimal distortion and artifacts. Using these blockface volumes as an intermediary, we achieve a precise alignment between MRI and histology slides, yielding registration results with an overlapping Dice score of ~90% for whole tissue alignment between MRI and blockface volumes, and >95% for 2D MRI-histology registration. This correlative MRI-histology pipeline with robust 2D and 3D coregistration methods promises to enhance our understanding of neurodegenerative diseases and aid the development of MRI-based disease biomarkers.
The impact of arteriolosclerosis on cognitive impairment in decedents without severe dementia from the National Alzheimer's Coordinating Center Cellas A. Hayes, Christina B. Young, Carla Abdelnour, Alexis Reeves, Michelle C. Odden, et al. Alzheimer S and Dementia, 2025 INTRODUCTIONAlzheimer's disease neuropathologic change (ADNC), Lewy body disease (LBD), and vascular neuropathologies occur together. Previous studies have been limited by a large majority of participants with severe dementia or advanced stages of pathologies, which limits the detectability of cognitive effects from vascular neuropathologies.METHODSUsing neuropathology data from the National Alzheimer's Coordinating Center, we examined the association of vascular neuropathologies with cognitive scores in participants without severe dementia (N = 1526) using multivariable linear regression.RESULTSControlling for age, sex, education, LBD, and ADNC, arteriolosclerosis was associated with lower memory (β = −0.16 ± 0.06, p < 0.001), executive function (β = −0.25 ± 0.05, p < 0.001), and language scores (β = −0.20 ± 0.05, p < 0.001). The effects of arteriolosclerosis remained when controlling for vascular risk factors.DISCUSSIONVascular neuropathologies exhibit distinct relationships with cognition. Arteriolosclerosis is an independent contributor to cognition. Further research should be conducted on whether arteriolosclerosis can serve as a surrogate marker for cognitive decline in early disease stages.Highlights In individuals who do not have severe dementia, vascular neuropathologies are common, and the combination of pathologies is heterogeneous in a convenience sample from the Alzheimer's Disease Research Center that reported all the neuropathology data elements for this investigation. Arteriolosclerosis is associated with several cognitive domain scores, including memory, executive function, and language when controlling for the effects of Alzheimer's disease neuropathologic change and Lewy body disease. These results reinforce the importance of vascular pathology for cognition among people along the Alzheimer's disease spectrum.
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A large-scale vision-language dataset derived from open scientific literature to advance biomedical generalist ai A Lozano, MW Sun, J Burgess, JJ Nirschl, C Polzak, Y Zhang, L Chen, ... arXiv preprint arXiv:2503.22727 , 2025 2025 Citations: 5
143 Artificial Intelligence-enabled Spatial Tumor Microenvironment Profiling Predicts Response to Immunotherapy in Invasive Breast Carcinoma F Eweje, Z Li, K Yuan, F Olguin, C Bergstrom, J Nirschl, R Li Laboratory Investigation 105 (3) , 2025 2025
The impact of arteriolosclerosis on cognitive impairment in decedents without severe dementia from the National Alzheimer's Coordinating Center CA Hayes, CB Young, C Abdelnour, A Reeves, MC Odden, J Nirschl, ... Alzheimer's & Dementia 21 (3), e70059 , 2025 2025 Citations: 13
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Molecular, histologic, and clinical characterization of methylation class pleomorphic xanthoastrocytoma: An analysis of 469 tumors CH Dampier, N Shah, K Galbraith, A Ebrahimi, OLA Neto, Z Abdullaev, ... Neuro-Oncology Advances 7 (1), vdaf089 , 2025 2025 Citations: 4
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