Tissue clearing combined with deep imaging has emerged as a powerful alternative to classical histological techniques. Whereas current techniques have been optimized for imaging selected nonpigmented organs such as the mammalian brain, natural pigmentation remains challenging for most other biological specimens of larger volume. We have developed a fast DEpigmEntation-Plus-Clearing method (DEEP-Clear) that is easily incorporated in existing workflows and combines whole system labeling with a spectrum of detection techniques, ranging from immunohistochemistry to RNA in situ hybridization, labeling of proliferative cells (EdU labeling) and visualization of transgenic markers. With light-sheet imaging of whole animals and detailed confocal studies on pigmented organs, we provide unprecedented insight into eyes, whole nervous systems, and subcellular structures in animal models ranging from worms and squids to axolotls and zebrafish. DEEP-Clear thus paves the way for the exploration of species-rich clades and developmental stages that are largely inaccessible by regular imaging approaches.
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http://dx.doi.org/10.1126/sciadv.aba0365 | DOI Listing |
Cell Metab
January 2025
Optogenetics & Synthetic Biology Interdisciplinary Research Center, Shanghai Frontiers Science Center of Optogenetic Techniques for Cell Metabolism, State Key Laboratory of Bioreactor Engineering, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China; Research Unit of New Techniques for Live-cell Metabolic Imaging, Chinese Academy of Medical Sciences, Beijing 100730, China. Electronic address:
Ophthalmol Retina
February 2022
Department of Ophthalmology & Vision Science, University of California, Davis, Sacramento, California. Electronic address:
Objective: Diseases such as age-related macular degeneration (AMD) are classified based on human rubrics that are prone to bias. Supervised neural networks trained using human-generated labels require labor-intensive annotations and are restricted to specific trained tasks. Here, we trained a self-supervised deep learning network using unlabeled fundus images, enabling data-driven feature classification of AMD severity and discovery of ocular phenotypes.
View Article and Find Full Text PDFMethods Enzymol
June 2021
Department of Molecular Pharmacology, Physiology, and Biotechnology, Brown University, Providence, RI, United States. Electronic address:
Melanocytes are specialized cells that produce melanin pigments responsible for skin, hair, and eye pigmentation. The synthesis and storage of melanin occurs in unique lysosome-related organelles called melanosomes, which regulate melanin production via complex regulatory mechanisms. Maintenance of the melanosome luminal ionic environment and pH is crucial for proper function of the main melanogenic enzymes.
View Article and Find Full Text PDFJ Indian Soc Periodontol
January 2021
Department of Periodontics, Panineeya Institute of Dental Sciences and Research Center, Hyderabad, Telangana, India.
Radiosurgery (RS) has evolved from electrosurgery and uses ultra-high-frequency radio waves at a frequency ranging from 3 to 4 MHz. It is used to address numerous soft-tissue concerns in dentistry and as well as medicine with excellent and predictable results. A review of the indexed literature disclosed that RS has been employed for various periodontal procedures such as gingivectomy, gingivoplasty, crown lengthening, minimally invasive closed osteotomy, frenectomies, operculectomies, depigmentation, gingival curettage, periodontal flap procedures, mucogingival surgeries, harvesting soft-tissue grafts, and also in implantology.
View Article and Find Full Text PDFSci Adv
May 2020
Department for Bioelectronics, FKE, Vienna University of Technology, Gußhausstraße 25-25A, building CH, 1040 Vienna, Austria.
Tissue clearing combined with deep imaging has emerged as a powerful alternative to classical histological techniques. Whereas current techniques have been optimized for imaging selected nonpigmented organs such as the mammalian brain, natural pigmentation remains challenging for most other biological specimens of larger volume. We have developed a fast DEpigmEntation-Plus-Clearing method (DEEP-Clear) that is easily incorporated in existing workflows and combines whole system labeling with a spectrum of detection techniques, ranging from immunohistochemistry to RNA in situ hybridization, labeling of proliferative cells (EdU labeling) and visualization of transgenic markers.
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