Nanoscale imaging of all anatomical structures over whole vertebrates is needed for a systematic understanding of human diseases, but this has not yet been achieved. Here, we demonstrate whole-ExM, which enables nanoscale imaging of all anatomical structures of whole zebrafish larvae by labeling the proteins of the larvae with fluorophores and expanding them four-fold. We first optimize the fluorophore selection and labeling procedure to visualize a broader range of anatomical structures. We then develop an expansion protocol for zebrafish larvae having calcified body parts. Through this process, we visualize the nanoscale details of diverse larvae organs, which have corresponding organ counterparts in humans, over the intact larvae. We show that whole-ExM retains the fluorescence signals of fluorescent proteins, and its resolution is high enough to visualize various structures that can be imaged only with electron microscopy. Whole-ExM would enable the nanoscale study of the molecular mechanisms of human diseases.

Here we report SUPPORT (Statistically Unbiased Prediction utilizing sPatiOtempoRal information in imaging daTa), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatially neighboring pixels in the same time frame, even when its temporally adjacent frames do not provide useful information for statistical prediction. Such spatiotemporal dependency is captured and utilized to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulation and experiments, we show that SUPPORT enables precise denoising of voltage imaging data while preserving the underlying dynamics in the scene.

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Collagen is a prominent target of nonenzymatic glycation, which is a hallmark of aging and causes functional alteration of the matrix. Here, we uncover glycation‐mediated structural and functional changes in the collagen‐enriched meningeal membrane of the human and mouse brain. Using an in vitro culture platform mimicking the meningeal membrane composed of fibrillar collagen, we showed that the accumulation of advanced glycation end products (AGEs) in the collagen membrane is responsible for glycation‐mediated matrix remodeling. These changes influence fibroblast‐matrix interactions, inducing cell‐mediated ECM remodeling. The adherence of meningeal fibroblasts to the glycated collagen membrane was mediated by the discoidin domain‐containing receptor 2 (DDR2), whereas integrin‐mediated adhesion was inhibited. A‐kinase anchoring protein 12 (AKAP12)‐positive meningeal fibroblasts in the meningeal membrane of aged mice exhibited substantially increased expression of DDR2 and depletion of integrin beta‐1 (ITGB1). In the glycated collagen membrane, meningeal fibroblasts increased the expression of matrix metalloproteinase 14 (MMP14) and less tissue inhibitor of metalloproteinase‐1 (TIMP1). In contrast, the cells exhibited decreased expression of type I collagen (COL1A1). These results suggest that glycation modification by meningeal fibroblasts is intimately linked to aging‐related structural and functional alterations in the meningeal membrane.