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Three-color single-molecule localization microscopy in chromatin

光：科学与应用（英文版） 2025年第5期14卷 1265-1277页

作者： Nicolas Acosta Ruyi Gong Yuanzhe Su Jane Frederick Karla I.Medina Wing Shun Li Kiana Mohammadian Luay Almassalha Geng Wang Vadim Backman Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Center for Physical Genomics and Engineering Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Center for Physical Genomics and Engineering Northwestern UniversityEvanstonIL 60208USA IBIS Interdisciplinary Biological Sciences Graduate Program Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Center for Physical Genomics and Engineering Northwestern UniversityEvanstonIL 60208USA Applied Physics Program Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Department of Biomedical Engineering Northwestern UniversityEvanstonIL 60208USA Center for Physical Genomics and Engineering Northwestern UniversityEvanstonIL 60208USA Department of Gastroenterology and Hepatology Northwestern Memorial HospitalChicagoIL 60611USA

Super-resolution microscopy has revolutionized our ability to visualize structures below the diffraction limit of conventional optical microscopy and is particularly useful for investigating complex biological targets like *** exhibits a hierarchical organization with structural compartments and domains at different length scales,from nanometers to *** molecule localization microscopy(SMLM)methods,such as STORM,are essential for studying chromatin at the supra-nucleosome level due to their ability to target epigenetic marks that determine chromatin ***-label imaging of chromatin is necessary to unpack its structural ***,these efforts are challenged by the high-density nuclear environment,which can affect antibody binding affinities,diffusivity and non-specific *** buffer conditions,fluorophore stability,and antibody specificity is crucial for achieving effective antibody ***,we demonstrate a sequential immunolabeling protocol that reliably enables three-color studies within the dense nuclear *** protocol couples multiplexed localization datasets with a robust analysis algorithm,which utilizes localizations from one target as seed points for distance,density and multi-label joint affinity measurements to explore complex organization of all three *** this multiplexed algorithm to analyze distance and joint density reveals that heterochromatin and euchromatin are not-distinct territories,but that localization of transcription and euchromatin couple with the periphery of heterochromatic *** work is a crucial step in molecular imaging of the dense nuclear environment as multi-label capacity enables for investigation of complex multi-component systems like chromatin with enhanced accuracy.

关键词： localization chromatin microscopy single-molecule three-color

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scNanoCOOL-seq:a long-read single-cell sequencing method for multi-omics profiling within individual cells

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细胞研究（英文版） 2023年第11期33卷 879-882页

作者： Jianli Lin Xiaohui Xue Yan Wang Yuan Zhou Jian Wu Haoling Xie Mengya Liu Lu Wen Fuchou Tang Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina Biomedical Pioneering Innovation Center School of Life SciencesPeking UniversityBeijingChina Beijing Advanced Innovation Center for Genomics(ICG) Ministry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina Biomedical Pioneering Innovation Center School of Life SciencesPeking UniversityBeijingChina Beijing Advanced Innovation Center for Genomics(ICG) Ministry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina PKU-Tsinghua-NIBS Graduate Program Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina Biomedical Pioneering Innovation Center School of Life SciencesPeking UniversityBeijingChina Beijing Advanced Innovation Center for Genomics(ICG) Ministry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina Biomedical Pioneering Innovation Center School of Life SciencesPeking UniversityBeijingChina Beijing Tongren Eye Center Beijing Tongren HospitalCapital Medical UniversityBeijing Ophthalmology & Visual Science Key LabBeijingChina Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina Biomedical Pioneering Innovation Center School of Life SciencesPeking UniversityBeijingChina Beijing Advanced Innovation Center for Genomics(ICG) Ministry of Education Key Laboratory of Cell Proliferation and DifferentiationBeijingChina PKU-Tsinghua-NIBS Graduate Program Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijingChina

Dear Editor, Single-cell multi-omics sequencing technologies provide a first step towards a more comprehensive understanding of cell type-specific gene regulation,expanding our ability to systematically explore cellular diversity and heterogeneity.1 Based on nucleo-some occupancy and methylome sequencing(NOMe-seq)and bisulfite sequencing(BS-seq),we and others previously developed single-cell NOMe-seq(scNOMe-seq)and single-cell chromatin overall omic-scale landscape sequencing(scCOOL-seq).1,2 Employ-ing a different strategy,scCOOL-seq/scNOMe-seq has several advantages over other existing single-cell muti-omics sequencing methods(Supplementary information,Note S1).

关键词： Chromatin analysis Gene expression profiling Methylation analysis

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A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

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National Science Review 2025年第5期12卷 362-381页

作者： Yurun Lu Dan Liu Zhongming Liang Rui Liu Pei Chen Yitong Liu Jiachen Li Zhanying Feng Lei M.Li Bin Sheng Weiping Jia Luonan Chen Huating Li Yong Wang Center for Excellence in Mathematical Sciences National Center for Mathematics and Interdisciplinary Sciences Hua Loo-Keng Center for Mathematical Sciences Key Laboratory of Management Decision and Information System Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematics University of Chinese Academy of SciencesChinese Academy of Sciences Department of Endocrinology and Metabolism Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai Diabetes InstituteShanghai Clinical Center for Diabetes Shanghai Key Laboratory of Diabetes Mellitus Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of Sciences BGI-Research School of Mathematics South China University of Technology Department of Statistics Department of Biomedical Data Science Bio-X ProgramStanford University Department of Computer Science and Engineering Shanghai Jiao Tong University State Key Laboratory of Cell Biology Center for Excellence in Molecular Cell Science Shanghai Institute of Biochemistry and Cell Biology Chinese Academy of Sciences Guangdong Institute of Intelligence Science and Technology Pazhou Laboratory (Huangpu)

Continuous glucose monitoring(CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states(MAE = 3.7 mg/d L). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task(AUROC = 0.914 for type 2 diabetes(T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics,CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling(Pearson correlation coefficient = 0.763)and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the ear

关键词： pretrained model diabetes continuous glucose monitoring glucose dynamics

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Cardiac Fibroblast-Mediated ECM Remodeling Regulates Maturation in an in vitro Cardiac Bundle Developmental Model

SSRN

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SSRN 2024年

作者： Jang, Yongjun Kang, Myeongjin Kang, Yong Guk Lee, Dongtak Jung, Hyo Gi Yoon, Dae Sung Kim, Jongseong Park, Yongdoo Department of Biomedical Sciences College of Medicine Korea University Seoul Korea Republic of School of Biomedical Engineering Korea University Seoul Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul Korea Republic of

Cardiac fibroblasts play an important role in heart homeostasis, regeneration, and disease by producing extracellular matrix (ECM) proteins and remodeling enzymes. Under normal conditions, fibroblasts exist in a quiescent state and maintain homeostasis, such as tissue structure and ECM turnover. However, if they become activated upon stimuli, such as injury, aging, or mechanical stress, which can lead to disease through excessive cell proliferation and ECM production. In addition to studying fibroblasts in disease progression, their role in cardiac maturation during development and whether the mechanism of cytokine and ECM production is similar to that observed during disease progression is unclear. In this study, we examined the functional and structural maturation of cardiac tissue by modulating fibroblast activity using an in vitro model of cardiac bundle formation. In this model, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and human cardiac fibroblasts (CFBs) were co-cultured in a fibrin gel and their morphology, beating characteristics, beating force, and mRNA expression profiles were analyzed. The results indicated that the cardiac bundle model matured structurally and functionally through tissue contraction and collagen deposition by fibroblasts, whereas inhibition of these ECM remodeling reduced maturation. In particular, the expression of second harmonic generation (SHG) and COL1A revealed that while activated fibroblasts induce structural maturation through sustained collagen deposition, excessive collagen accumulation can reduce functional maturation. Our data suggest that collagen type I expression by cardiac fibroblasts is essential for myocardial tissue maintenance and development through ECM remodeling. Furthermore, the regulation of collagen deposition by fibroblast activity is a crucial factor that influences cardiac development and disease progression. © 2024, The Authors. All rights reserved.

关键词： Stem cells

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The School of No Fun and No Play: Learning How to Create Supportive Environments from Children with Osteogenesis Imperfecta

Journal of Disability Studies in Education

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Journal of Disability Studies in Education 2024年第3期122卷 25-49页

作者： Cleary, Brenda Linds, Warren Carnevale, Franco A. Thorstad, Kelly Rauch, Frank Tsimicalis, Argerie the McGill University-based VOICE (Views On Interdisciplinary Childhood Ethics) research program the Shriners Hospitals for Children® Canada Montreal Canada Concordia University Director of Human Systems Intervention Graduate Program the Department of Applied Human Sciences Montreal Canada the Ingram School of Nursing McGill University based VOICE research program Montreal Canada PHCNP Director of Nursing and Patient Care Services/ Nurse Executive Shriners Hospitals for Children-Canada Montreal Canada the Department of Pediatrics McGill University the Biomedical Clinical Laboratory the Shriners Hospitals for Children®-Canada Montreal Canada

Children with medically complex dis/abilities hold sophisticated views on effective school leadership, adapted built environments, inspiring peer solidarity, catalyzing transformational solutions and a possible school-hospital liaison model to support student well-being. Using child-centric collaborative techniques, this ethnodramatic study engaged children with osteogenesis imperfecta (oi), a rare genetic disease, to create a children’s book describing their moral experiences to be disseminated to other children and families. Children living with oi experience ongoing medical interventions and dis/ability that broadly jeopardized the quality of their academic experience relative to their peers. As such, children living with oi offered trenchant insight into what supports and thwarts operationalization of their values and highlights the programs, leadership, services and paradigm shifts they feel that they need to flourish in the academic context. © Brenda Cleary et al., 2024.

关键词： Dis/abled Children Education Medicine in Literature Osteogenesis Imperfecta Return to School

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Equilibrative nucleoside transporter 3 supports microglial functions and protects against the progression of Huntington's disease in the mouse model

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Brain, Behavior, and Immunity 2024年 120卷 413-429页

作者： Lu, Ying-Sui Hung, Wei-Chien Hsieh, Yu-Ting Tsai, Pei-Yuan Tsai, Tsai-Hsien Fan, Hsiu-Han Chang, Ya-Gin Cheng, Hui-Kuei Huang, Shen-Yan Lin, Hsin-Chuan Lee, Yan-Hua Shen, Tzu-Hsiang Hung, Bing-Yu Tsai, Jin-Wu Dzhagalov, Ivan Cheng, Irene Han-Juo Lin, Chun-Jung Chern, Yijuang Hsu, Chia-Lin Institute of Microbiology and Immunology National Yang Ming Chiao Tung University Taipei Taiwan Taiwan International Graduate Program in Molecular Medicine National Yang Ming Chiao Tung University and Academia Sinica Taipei Taiwan Institute of Brain Science National Yang Ming Chiao Tung University Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Taiwan International Graduate Program in Interdisciplinary Neuroscience National Yang Ming Chiao Tung University and Academia Sinica Taipei Taiwan Biomedical Industry Ph.D. Program National Yang Ming Chiao Tung University Taipei Taiwan Brain Research Center National Yang Ming Chiao Tung University Taipei Taiwan School of Pharmacy College of Medicine National Taiwan University Taipei Taiwan

Huntington's disease (HD) is a hereditary neurodegenerative disorder characterized by involuntary movements, cognitive deficits, and psychiatric symptoms. Currently, there is no cure, and only limited treatments are available to manage the symptoms and to slow down the disease's progression. The molecular and cellular mechanisms of HD's pathogenesis are complex, involving immune cell activation, altered protein turnover, and disturbance in brain energy homeostasis. Microglia have been known to play a dual role in HD, contributing to neurodegeneration through inflammation but also enacting neuroprotective effects by clearing mHTT aggregates. However, little is known about the contribution of microglial metabolism to HD progression. This study explores the impact of a microglial metabolite transporter, equilibrative nucleoside transporter 3 (ENT3), in HD. Known as a lysosomal membrane transporter protein, ENT3 is highly enriched in microglia, with its expression correlated with HD severity. Using the R6/2 ENT3^−/− mouse model, we found that the deletion of ENT3 increases microglia numbers yet worsens HD progression, leading to mHTT accumulation, cell death, and disturbed energy metabolism. These results suggest that the delicate balance between microglial metabolism and function is crucial for maintaining brain homeostasis and that ENT3 has a protective role in ameliorating neurodegenerative processes. © 2024 The Authors

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Cartilage targeting cationic peptide carriers display deep cartilage penetration and retention in a rabbit model of post-traumatic osteoarthritis

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Osteoarthritis and Cartilage 2025年第6期33卷 721-734页

作者： Boyer, Timothy L. Chao, Olivia Hakim, Bill Childress, Luke Meslier, Quentin A. Iyengar, Suhasini M. Ondrechen, Mary Jo Porter, Ryan M. Bajpayee, Ambika G. Department of Bioengineering Northeastern University Boston MA United States Department of Biochemistry Northeastern University Boston MA United States Graduate Program for Interdisciplinary Biomedical Sciences UAMS Little Rock AR United States Department of Chemistry and Chemical Biology Northeastern University Boston MA United States Department of Internal Medicine UAMS Little Rock AR United States Department of Orthopaedic Surgery UAMS Little Rock AR United States

Objective: Drug delivery to cartilage is limited by its complex architecture and avascularity. Cationic peptide carriers (CPCs) have previously been optimized for improved cartilage transport and retention of drugs in vitro. In this study, we evaluated the kinetics, stability, and immunogenicity of CPCs after a single intra-articular injection using a rabbit knee injury model. Design: New Zealand White rabbits were administered a single dose of Cy5-labeled CPCs in knees receiving anterior cruciate ligament transection (ACLT) or Sham surgery. CPC biodistribution and retention within joint tissues and synovial fluid were evaluated 1 and 7 days after administration, and extra-articular kinetics were assessed in serum. Histology, immunohistochemistry, and reverse transcription quantitative polymerase chain reaction were performed to assess synovitis and protease activity. Proteolytic analysis of CPCs in the presence of arthritic enzymes was evaluated using synovial fluid size-exclusion filtration, Fluorescence Resonance Energy Transfer analysis, and computational molecular docking. Results: CPCs penetrated the full depth of sulfated glycosaminoglycan (sGAG)-rich tissues, notably cartilage, and were retained through the latest timepoint measured (one week) in both Sham and ACLT knees. Compared to ACLT, Sham knees had greater joint retention at Day 1 (1.6-fold) and Day 7 (1.8-fold). CPC intra-tissue concentration strongly correlated with tissue sGAG density, which did not considerably differ between surgical conditions at these timepoints. However, CPCs exhibited elevated vascular clearance and proteolytic fragmentation in inflammatory conditions. CPCs did not increase macrophage abundance, cytokine expression, or alter tissue morphology. Conclusion: CPCs target the deep layers of cartilage, even in inflamed joints, and can be utilized to substantially improve intra-joint bioavailability of therapeutics. © 2025 Osteoarthritis Research Society International

关键词： Cartilage penetration Cationic carriers Charge-based drug delivery Post-traumatic osteoarthritis Rabbit

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EDM: Enhancing Quality Diversity of Medical Image Augmentation Under the User-specified Complex and Various Conditions

EDM: Enhancing Quality Diversity of Medical Image Augmentati...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： S. Y. Kim H. B. Chung J. S. Lee M. J. Kang Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Republic of Korea Seoul National University Nuclear Medicine Bioengineering and Biomedical Sciences Seoul Republic of Korea Seoul National University Mathematical Sciences Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In the medical domain, the scarcity of data leads to class imbalances and fairness issues, significantly impairing deep learning performance and leading to the underrepresentation of minority patient groups. To address these challenges, data augmentation techniques employing Generative Adversarial Networks (GANs) and diffusion models have been extensively explored, with diffusion models particularly noted for their ability to enhance data diversity and quality. Despite their achievements, it remains a challenging task to generate a diverse range of samples from limited datasets and to achieve precise generation of images that align with user *** overcome these limitations, we propose a framework, EDM (Enhancing Quality Diversity of Medical image augmentation under the user-specified complex and various conditions), designed to generate diverse high-quality medical images under the various and complex multimodal conditions, representing age, sex, and diseases. Our framework comprises four steps. First, we propose a metric to quantize the necessity of data augmentation. Second, we prepare data augmentation. We generate medical sketch-image-text triplets using DiffSketcher from the real patients’ dataset. Then we employ these triplets to train ControlNet, enabling the generation of synthetic medical images from sketch data. Third, we generate synthetic medical images. We obtain multiple sketches for each image from a diversity-enhanced DiffSketcher, incorporating similarity loss. Using these sketches, we augment data from the fine-tuned ControlNet from the second step. Lastly, we introduce a metric to measure the diversity of the generated images, ensuring the effectiveness of our augmentation *** preliminary experimental results imply EDM can be the promising solution. Future experiments are planned to construct synthetic datasets of various modalities such as PET and CT for underrepresented patient groups.

关键词： Semiconductor device measurement Microwave integrated circuits Semiconductor detectors Data augmentation Diffusion models Generative adversarial networks Image augmentation

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COIN: Confidence Score-Guided Distillation for Annotation-Free Cell Segmentation

arXiv

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arXiv 2025年

作者： Jo, Sanghyun Lee, Seo Jin Lee, Seungwoo Hong, Seohyung Seo, Hyungseok Kim, Kyungsu OGQ Seoul Korea Republic of Laboratory of Cell & Gene Therapy Institute of Pharmaceutical Sciences College of Pharmacy Seoul National University Korea Republic of Department of Biomedical Science and Medical Research Center College of Pharmacy Seoul National University Korea Republic of School of Transdisciplinary Innovations Interdisciplinary Program in Bioengineering Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Cell instance segmentation (CIS) is crucial for identifying individual cell morphologies in histopathological images, providing valuable insights for biological and medical research. While unsupervised CIS (UCIS) models aim to reduce the heavy reliance on labor-intensive image annotations, they fail to accurately capture cell boundaries, causing missed detections and poor performance. Recognizing the absence of error-free instances as a key limitation, we present COIN (COnfidence score-guided INstance distillation), a novel annotation-free framework with three key steps: (1) Increasing the sensitivity for the presence of error-free instances via unsupervised semantic segmentation with optimal transport, leveraging its ability to discriminate spatially minor instances, (2) Instance-level confidence scoring to measure the consistency between model prediction and refined mask and identify highly confident instances, offering an alternative to ground truth annotations, and (3) Progressive expansion of confidence with recursive self-distillation. Extensive experiments across six datasets show COIN outperforming existing UCIS methods, even surpassing semi- and weakly-supervised approaches across all metrics on the MoNuSeg and TNBC datasets. The code is available at https://***/shjo-april/COIN. © 2025, CC BY.

关键词： Semantic Segmentation

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Deep imaging of LepR^(+)stromal cells in optically cleared murine bone hemisections

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Bone Research 2025年第1期13卷 104-120页

作者： Yuehan Ni Jiamiao Wu Fengqi Liu Yating Yi Xiangjiao Meng Xiang Gao Luyi Xiao Weiwei Zhou Zexi Chen Peng Chu Dan Xing Ye Yuan Donghui Ding Ge Shen Min Yang Ronjie Wu Ling Wang Luiza Martins Nascentes Melo Sien Lin Xiaoguang Cheng Gang Li Alpaslan Tasdogan Jessalyn M.Ubellacker Hu Zhao Shentong Fang Bo Shen College of Life Sciences Beijing Normal University100875BeijingChina National Institute of Biological Sciences Beijing(NIBS)102206BeijingChina Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua University100084BeijingChina School of Biopharmacy China Pharmaceutical University211198NanjingChina Chinese Institute for Brain Research Beijing(CIBR)102206BeijingChina Chinese Academy of Medical Sciences&Peking Union Medical College 100730BeijingChina Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University100871BeijingChina Arthritis Clinic and Research Center Peking University People’s HospitalPeking University100044BeijingChina Musculoskeletal Research Laboratory Department of Orthopaedics&Traumatology&Li Ka Shing Institute of Health SciencesFaculty of MedicineThe Chinese University of Hong Kong999077ShatinHong Kong SARPR China Department of Radiology Beijing Jishuitan HospitalCapital Medical UniversityNational Center for Orthopaedics100035BeijingChina Department of Dermatology University Hospital Essen&German Cancer ConsortiumPartner SiteEssen45147Germany Department of Molecular Metabolism Harvard T.H.Chan School of Public HealthBostonMA02115USA Tsinghua Institute of Multidisciplinary Biomedical Research Tsinghua University100084BeijingChina

Tissue clearing combined with high-resolution confocal imaging is a cutting-edge approach for dissecting the three-dimensional(3D)architecture of tissues and deciphering cellular spatial interactions under physiological and pathological *** the spatial interaction of leptin receptor-expressing(LepR^(+))stromal cells with other compartments in the bone marrow is crucial for a deeper understanding of the stem cell niche and the skeletal *** this study,we introduce an optimized protocol for the 3D analysis of skeletal tissues,enabling the visualization of hematopoietic and stromal cells,especially LepR+stromal cells,within optically cleared bone *** method preserves the 3D tissue architecture and is extendable to other hematopoietic sites such as calvaria and *** protocol entails tissue fixation,decalcification,and cryosectioning to reveal the marrow *** within approximately 12 days,this process yields highly transparent tissues that maintain genetically encoded or antibody-stained fluorescent *** bone hemisections are compatible with diverse antibody labeling *** microscopy of these transparent samples allows for qualitative and quantitative image analysis using Aivia or Bitplane Imaris software,assessing a spectrum of *** proper storage,the fluorescent signal in the stained and cleared bone hemisections remains intact for at least 2–3 *** protocol is robust,straightforward to implement,and highly reproducible,offering a valuable tool for tissue architecture and cellular interaction studies.

关键词： transparent sections straight

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