Explore the vast range of titles available.

State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.Tissue-clearing methods are now allowing 3D imaging of intact tissues and some entire mammals. In this Review, Ueda and colleagues discuss the various tissue-clearing methods, related techniques and data analysis and management, as well as the application of these methods in neuroscience.

This protocol describes how to perform CUBIC (Clear, Unobstructed Brain/Body Imaging Cocktails and Computational analysis), a simple and efficient method for organ clearing, imaging by light-sheet microscopy, and quantitative imaging analysis. Here we describe a protocol for advanced CUBIC (Clear, Unobstructed Brain/Body Imaging Cocktails and Computational analysis). The CUBIC protocol enables simple and efficient organ clearing, rapid imaging by light-sheet microscopy and quantitative imaging analysis of multiple samples. The organ or body is cleared by immersion for 1–14 d, with the exact time required dependent on the sample type and the experimental purposes. A single imaging set can be completed in 30–60 min. Image processing and analysis can take <1 d, but it is dependent on the number of samples in the data set. The CUBIC clearing protocol can process multiple samples simultaneously. We previously used CUBIC to image whole-brain neural activities at single-cell resolution using Arc-dVenus transgenic (Tg) mice. CUBIC informatics calculated the Venus signal subtraction, comparing different brains at a whole-organ scale. These protocols provide a platform for organism-level systems biology by comprehensively detecting cells in a whole organ or body.

Understanding synaptic dynamics during the sleep–wake cycle in the cortex is crucial yet remains controversial. The synaptic homeostasis hypothesis (SHY) suggests synaptic depression during non-rapid eye movement (NREM) sleep, while other studies report synaptic potentiation or synaptic changes during NREM sleep depending on activities in wakefulness. To find boundary conditions between these contradictory observations, we focused on learning rules and firing patterns that contribute to the synaptic dynamics. Using computational models considering mammalian cortical neurons, we found that under Hebbian and spike-timing dependent plasticity (STDP), wake-like firing patterns decrease synaptic weights, while sleep-like patterns strengthen synaptic weights. We refer to this tendency as Wake Inhibition and Sleep Excitation (WISE). Conversely, under Anti-Hebbian and Anti-STDP, synaptic depression during NREM sleep was observed, aligning with the conventional synaptic homeostasis hypothesis. Moreover, synaptic changes depended on firing rate differences between NREM sleep and wakefulness. We provide a unified framework that could explain synaptic homeodynamics under the sleep–wake cycle.

Tissue-clearing techniques are powerful tools for biological research and pathological diagnosis. Here, we describe advanced clear, unobstructed brain imaging cocktails and computational analysis (CUBIC) procedures that can be applied to biomedical research. This protocol enables preparation of high-transparency organs that retain fluorescent protein signals within 7–21 d by immersion in CUBIC reagents. A transparent mouse organ can then be imaged by a high-speed imaging system (>0.5 TB/h/color). In addition, to improve the understanding and simplify handling of the data, the positions of all detected cells in an organ (3–12 GB) can be extracted from a large image dataset (2.5–14 TB) within 3–12 h. As an example of how the protocol can be used, we counted the number of cells in an adult whole mouse brain and other distinct anatomical regions and determined the number of cells transduced with mCherry following whole-brain infection with adeno-associated virus (AAV)-PHP.eB. The improved throughput offered by this protocol allows analysis of numerous samples (e.g., >100 mouse brains per study), providing a platform for next-generation biomedical research. Transparent organs are obtained, with retained fluorescent protein signals, upon clearing by immersion in the appropriate CUBIC reagent. The positions of all the cells can be determined using the described software.

A three-dimensional single-cell-resolution mammalian brain atlas will accelerate systems-level identification and analysis of cellular circuits underlying various brain functions. However, its construction requires efficient subcellular-resolution imaging throughout the entire brain. To address this challenge, we developed a fluorescent-protein-compatible, whole-organ clearing and homogeneous expansion protocol based on an aqueous chemical solution (CUBIC-X). The expanded, well-cleared brain enabled us to construct a point-based mouse brain atlas with single-cell annotation (CUBIC-Atlas). CUBIC-Atlas reflects inhomogeneous whole-brain development, revealing a significant decrease in the cerebral visual and somatosensory cortical areas during postnatal development. Probabilistic activity mapping of pharmacologically stimulated Arc-dVenus reporter mouse brains onto CUBIC-Atlas revealed the existence of distinct functional structures in the hippocampal dentate gyrus. CUBIC-Atlas is shareable by an open-source web-based viewer, providing a new platform for whole-brain cell profiling.

Antibodies are extensively used in biomedical research, clinical fields, and disease treatment. However, to enhance the reproducibility and reliability of antibody-based experiments, it is crucial to have a detailed understanding of the antibody’s target specificity and epitope. In this study, we developed a high-throughput and precise epitope analysis method, DECODE (Decoding Epitope Composition by Optimized-mRNA-display, Data analysis, and Expression sequencing). This method allowed identifying patterns of epitopes recognized by monoclonal or polyclonal antibodies at single amino acid resolution and predicted cross-reactivity against the entire protein database. By applying the obtained epitope information, it has become possible to develop a new 3D immunostaining method that increases the penetration of antibodies deep into tissues. Furthermore, to demonstrate the applicability of DECODE to more complex blood antibodies, we performed epitope analysis using serum antibodies from mice with experimental autoimmune encephalomyelitis (EAE). As a result, we were able to successfully identify an epitope that matched the sequence of the peptide inducing the disease model without relying on existing antigen information. These results demonstrate that DECODE can provide high-quality epitope information, improve the reproducibility of antibody-dependent experiments, diagnostics and therapeutics, and contribute to discover pathogenic epitopes from antibodies in the blood.

Human sleep phenotypes can be defined and diversified by both genetic and environmental factors. However, some sleep phenotypes are difficult to evaluate without long-term, precise sleep monitoring, for which simple yet accurate sleep measurement is required. To solve this problem, we recently developed a state-of-the-art sleep/wake classification algorithm based on wristband-type accelerometers, termed ACCEL (acceleration-based classification and estimation of long-term sleep-wake cycles). In this study, we optimized and applied ACCEL to large-scale analysis of human sleep phenotypes. The clustering of an about 100,000-arm acceleration dataset in the UK Biobank using uniform manifold approximation and projection (UMAP) dimension reduction and density-based spatial clustering of applications with noise (DBSCAN) clustering methods identified 16 sleep phenotypes, including those related to social jet lag, chronotypes (“morning/night person”), and seven different insomnia-like phenotypes. Considering the complex relationship between sleep disorders and other psychiatric disorders, these unbiased and comprehensive analyses of sleep phenotypes in humans will not only contribute to the advancement of biomedical research on genetic and environmental factors underlying human sleep patterns but also, allow for the development of better digital biomarkers for psychiatric disorders.

The concept of chirality is of great relevance in nature, from chiral molecules such as sugar to parity transformations in particle physics. In condensed matter physics, recent studies have demonstrated chiral fermions and their relevance in emergent phenomena closely related to topology 1 – 3 . The experimental verification of chiral phonons (bosons) remains challenging, however, despite their expected strong impact on fundamental physical properties 4 – 6 . Here we show experimental proof of chiral phonons using resonant inelastic X-ray scattering with circularly polarized X-rays. Using the prototypical chiral material quartz, we demonstrate that circularly polarized X-rays, which are intrinsically chiral, couple to chiral phonons at specific positions in reciprocal space, allowing us to determine the chiral dispersion of the lattice modes. Our experimental proof of chiral phonons demonstrates a new degree of freedom in condensed matter that is both of fundamental importance and opens the door to exploration of new emergent phenomena based on chiral bosons. Our experimental proof of chiral phonons demonstrates a degree of freedom in condensed matter that is of fundamental importance and opens the door to exploration of emergent phenomena based on chiral bosons.

Hepatoblastoma (HB) is the most common pediatric liver malignancy; however, hereditary predisposition and acquired molecular aberrations related to HB clinicopathological diversity are not well understood. Here, we perform an integrative genomic profiling of 163 pediatric liver tumors (154 HBs and nine hepatocellular carcinomas) based on the data acquired from a cohort study (JPLT-2). The total number of somatic mutations is precious low (0.52/Mb on exonic regions) but correlated with age at diagnosis. Telomerase reverse transcriptase ( TERT) promoter mutations are prevalent in the tween HBs, selective in the transitional liver cell tumor (TLCT, > 8 years old). DNA methylation profiling reveals that classical HBs are characterized by the specific hypomethylated enhancers, which are enriched with binding sites for ASCL2, a regulatory transcription factor for definitive endoderm in Wnt-pathway. Prolonged upregulation of ASCL2, as well as fetal-liver-like methylation patterns of IGF2 promoters, suggests their “cell of origin” derived from the premature hepatoblast, similar to intestinal epithelial cells, which are highly proliferative. Systematic molecular profiling of HB is a promising approach for understanding the epigenetic drivers of hepatoblast carcinogenesis and deriving clues for risk stratification. While hepatoblastoma is the most common pediatric liver cancer, its molecular background has not been fully characterised. Here, the authors perform genomic and epigenomic profiling of 163 untreated pediatric liver tumours and suggest the upregulation of ASCL2 and methylation patterns of IGF2 promoters in driving hepatoblast carcinogenesis.

Tissue clearing, coupled with immunostaining, enables the transition from two-dimensional to three-dimensional pathology and has the potential to substantially improve data quality for biomedical diagnostics. Nevertheless, the workflows are limited by the complex sample processing protocols. Approaches for the parallel processing of samples, to include tissue clearing, immunostaining, imaging and analysis can increase three-dimensional pathology throughput. Here we detail a step-by-step approach that combines a tissue clearing device with a six-well multiwell plate to increase the throughput compared with methods using conventional clearing protocols. The six-well multiplate allows for parallel tissue clearing of multiple samples and is compatible with passive tissue clearing methods including Clear, Unobstructed Brain/Body Imaging Cocktails and Computational (CUBIC) analysis. In addition, gel embedding is performed without moving the samples from the wells, and a series of steps such as imaging with a high-speed light-sheet microscope and analysis in the cloud can be performed. Although this procedure slightly extends the overall time required for preparing and analyzing a single sample, it reduces the effort required at each step, such as reagent exchange and gel embedding, which results in an overall reduction in hands-on time due to the parallel sample processing. We describe a series of whole-organ analyses, including high-throughput tissue clearing, staining, gel embedding, imaging and data analysis in the cloud, as a useful platform for cellular biology and pathology. The total process varies depending on the presence or absence of immunostaining, but for some six-well plates, the tissue clearing process, imaging and data analysis can be completed within 10 d. Key points In this modified tissue clearing protocol, a multiwell plate is combined with a tissue clearing insert device to enable the parallelization of the tissue clearing process. This procedure streamlines the complex task of reagent exchange during the clearing process. In this protocol, the tissue clearing process is carried out using a multiwell plate and insert, which allows the clearing steps to be conducted in parallel across multiple samples.