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Huang Z, Sun Y, Liu S, Chen X, Ping J, Fei P, Gong Z, Zheng N. A machine learning based method for tracking of simultaneously imaged neural activity and body posture of freely moving maggot. Biochem Biophys Res Commun 2024; 727:150290. [PMID: 38941792 DOI: 10.1016/j.bbrc.2024.150290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/16/2024] [Accepted: 06/19/2024] [Indexed: 06/30/2024]
Abstract
To understand neural basis of animal behavior, it is necessary to monitor neural activity and behavior in freely moving animal before building relationship between them. Here we use light sheet fluorescence microscope (LSFM) combined with microfluidic chip to simultaneously capture neural activity and body movement in small freely behaving Drosophila larva. We develop a transfer learning based method to simultaneously track the continuously changing body posture and activity of neurons that move together using a sub-region tracking network with a precise landmark estimation network for the inference of target landmark trajectory. Based on the tracking of each labelled neuron, the activity of the neuron indicated by fluorescent intensity is calculated. For each video, annotation of only 20 frames in a video is sufficient to yield human-level accuracy for all other frames. The validity of this method is further confirmed by reproducing the activity pattern of PMSIs (period-positive median segmental interneurons) and larval movement as previously reported. Using this method, we disclosed the correlation between larval movement and left-right asymmetry in activity of a group of unidentified neurons labelled by R52H01-Gal4 and further confirmed the roles of these neurons in bilateral balance of body contraction during larval crawling by genetic inhibition of these neurons. Our method provides a new tool for accurate extraction of neural activities and movement of freely behaving small-size transparent animals.
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Affiliation(s)
- Zenan Huang
- Zhejiang Lab, Hangzhou, 311121, China; Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310007, China
| | - Yixuan Sun
- Zhejiang Lab, Hangzhou, 311121, China; Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Affiliated Mental Health Center, Zhejiang University School of Medicine, Hangzhou, 310058, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | | | - Xiaopeng Chen
- Zhejiang Lab, Hangzhou, 311121, China; School of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics, Huazhong, University of Science and Technology, Wuhan, 430074, China
| | - Junyu Ping
- School of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics, Huazhong, University of Science and Technology, Wuhan, 430074, China
| | - Peng Fei
- School of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics, Huazhong, University of Science and Technology, Wuhan, 430074, China
| | - Zhefeng Gong
- Zhejiang Lab, Hangzhou, 311121, China; Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Affiliated Mental Health Center, Zhejiang University School of Medicine, Hangzhou, 310058, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China.
| | - Nenggan Zheng
- Zhejiang Lab, Hangzhou, 311121, China; Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310007, China
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Ding P, Wahn H, Chen FD, Li J, Mu X, Stalmashonak A, Luo X, Lo GQ, Poon JKS, Sacher WD. Photonic neural probe enabled microendoscopes for light-sheet light-field computational fluorescence brain imaging. NEUROPHOTONICS 2024; 11:S11503. [PMID: 38322247 PMCID: PMC10846542 DOI: 10.1117/1.nph.11.s1.s11503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 12/14/2023] [Accepted: 12/20/2023] [Indexed: 02/08/2024]
Abstract
Significance Light-sheet fluorescence microscopy is widely used for high-speed, high-contrast, volumetric imaging. Application of this technique to in vivo brain imaging in non-transparent organisms has been limited by the geometric constraints of conventional light-sheet microscopes, which require orthogonal fluorescence excitation and collection objectives. We have recently demonstrated implantable photonic neural probes that emit addressable light sheets at depth in brain tissue, miniaturizing the excitation optics. Here, we propose a microendoscope consisting of a light-sheet neural probe packaged together with miniaturized fluorescence collection optics based on an image fiber bundle for lensless, light-field, computational fluorescence imaging. Aim Foundry-fabricated, silicon-based, light-sheet neural probes can be packaged together with commercially available image fiber bundles to form microendoscopes for light-sheet light-field fluorescence imaging at depth in brain tissue. Approach Prototype microendoscopes were developed using light-sheet neural probes with five addressable sheets and image fiber bundles. Fluorescence imaging with the microendoscopes was tested with fluorescent beads suspended in agarose and fixed mouse brain tissue. Results Volumetric light-sheet light-field fluorescence imaging was demonstrated using the microendoscopes. Increased imaging depth and enhanced reconstruction accuracy were observed relative to epi-illumination light-field imaging using only a fiber bundle. Conclusions Our work offers a solution toward volumetric fluorescence imaging of brain tissue with a compact size and high contrast. The proof-of-concept demonstrations herein illustrate the operating principles and methods of the imaging approach, providing a foundation for future investigations of photonic neural probe enabled microendoscopes for deep-brain fluorescence imaging in vivo.
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Affiliation(s)
- Peisheng Ding
- Max Planck Institute of Microstructure Physics, Halle, Germany
- University of Toronto, Department of Electrical and Computer Engineering, Toronto, Ontario, Canada
| | - Hannes Wahn
- Max Planck Institute of Microstructure Physics, Halle, Germany
| | - Fu-Der Chen
- Max Planck Institute of Microstructure Physics, Halle, Germany
- University of Toronto, Department of Electrical and Computer Engineering, Toronto, Ontario, Canada
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, Ontario, Canada
| | - Jianfeng Li
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, Ontario, Canada
| | - Xin Mu
- Max Planck Institute of Microstructure Physics, Halle, Germany
- University of Toronto, Department of Electrical and Computer Engineering, Toronto, Ontario, Canada
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, Ontario, Canada
| | | | | | | | - Joyce K. S. Poon
- Max Planck Institute of Microstructure Physics, Halle, Germany
- University of Toronto, Department of Electrical and Computer Engineering, Toronto, Ontario, Canada
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, Ontario, Canada
| | - Wesley D. Sacher
- Max Planck Institute of Microstructure Physics, Halle, Germany
- Max Planck-University of Toronto Centre for Neural Science and Technology, Toronto, Ontario, Canada
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Li C, Rai MR, Cai Y, Ghashghaei HT, Greenbaum A. Intelligent Beam Optimization for Light-Sheet Fluorescence Microscopy through Deep Learning. INTELLIGENT COMPUTING (WASHINGTON, D.C.) 2024; 3:0095. [PMID: 39099879 PMCID: PMC11298055 DOI: 10.34133/icomputing.0095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 04/22/2024] [Indexed: 08/06/2024]
Abstract
Light-sheet fluorescence microscopy (LSFM) provides the benefit of optical sectioning coupled with rapid acquisition times, enabling high-resolution 3-dimensional imaging of large tissue-cleared samples. Inherent to LSFM, the quality of the imaging heavily relies on the characteristics of the illumination beam, which only illuminates a thin section of the sample. Therefore, substantial efforts are dedicated to identifying slender, nondiffracting beam profiles that yield uniform and high-contrast images. An ongoing debate concerns the identification of optimal illumination beams for different samples: Gaussian, Bessel, Airy patterns, and/or others. However, comparisons among different beam profiles are challenging as their optimization objectives are often different. Given that our large imaging datasets (approximately 0.5 TB of images per sample) are already analyzed using deep learning models, we envisioned a different approach to the problem by designing an illumination beam tailored to boost the performance of the deep learning model. We hypothesized that integrating the physical LSFM illumination model (after passing it through a variable phase mask) into the training of a cell detection network would achieve this goal. Here, we report that joint optimization continuously updates the phase mask and results in improved image quality for better cell detection. The efficacy of our method is demonstrated through both simulations and experiments that reveal substantial enhancements in imaging quality compared to the traditional Gaussian light sheet. We discuss how designing microscopy systems through a computational approach provides novel insights for advancing optical design that relies on deep learning models for the analysis of imaging datasets.
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Affiliation(s)
- Chen Li
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - Mani Ratnam Rai
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - Yuheng Cai
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - H. Troy Ghashghaei
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
- Department of Molecular Biomedical Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Alon Greenbaum
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
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4
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Feng R, Xie J, Gao L. EDTP enhances and protects the fluorescent signal of GFP in cleared and expanded tissues. Sci Rep 2024; 14:15279. [PMID: 38961181 PMCID: PMC11222453 DOI: 10.1038/s41598-024-66398-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 07/01/2024] [Indexed: 07/05/2024] Open
Abstract
Advanced 3D high-resolution imaging techniques are essential for investigating biological challenges, such as neural circuit analysis and tumor microenvironment in intact tissues. However, the fluorescence signal emitted by endogenous fluorescent proteins in cleared or expanded biological samples gradually diminishes with repeated irradiation and prolonged imaging, compromising its ability to accurately depict the underlying scientific problem. We have developed a strategy to preserve fluorescence in cleared and expanded tissue samples during prolonged high-resolution three-dimensional imaging. We evaluated various compounds at different concentrations to determine their ability to enhance fluorescence intensity and resistance to photobleaching while maintaining the structural integrity of the tissue. Specifically, we investigated the impact of EDTP utilization on GFP, as it has been observed to significantly improve fluorescence intensity, resistance to photobleaching, and maintain fluorescence during extended room temperature storage. This breakthrough will facilitate extended hydrophilic and hydrogel-based clearing and expansion methods for achieving long-term high-resolution 3D imaging of cleared biological tissues by effectively safeguarding fluorescent proteins within the tissue.
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Affiliation(s)
- Ruili Feng
- Fudan University, Shanghai, 200433, China.
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China.
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China.
| | - Jiongfang Xie
- Fudan University, Shanghai, 200433, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China
| | - Liang Gao
- Fudan University, Shanghai, 200433, China
- Key Laboratory of Structural Biology of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, 310024, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, 310024, Zhejiang, China
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5
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Zheng J, Wu YC, Cai X, Phan P, Er EE, Zhao Z, Lee SSY. Correlative multiscale 3D imaging of mouse primary and metastatic tumors by sequential light sheet and confocal fluorescence microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.14.594162. [PMID: 38798657 PMCID: PMC11118317 DOI: 10.1101/2024.05.14.594162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Three-dimensional (3D) optical microscopy, combined with advanced tissue clearing, permits in situ interrogation of the tumor microenvironment (TME) in large volumetric tumors for preclinical cancer research. Light sheet (also known as ultramicroscopy) and confocal fluorescence microscopy are often used to achieve macroscopic and microscopic 3D images of optically cleared tumor tissues, respectively. Although each technique offers distinct fields of view (FOVs) and spatial resolution, the combination of these two optical microscopy techniques to obtain correlative multiscale 3D images from the same tumor tissues has not yet been explored. To establish correlative multiscale 3D optical microscopy, we developed a method for optically marking defined regions of interest (ROIs) within a cleared mouse tumor by employing a UV light-activated visible dye and Z-axis position-selective UV irradiation in a light sheet microscope system. By integrating this method with subsequent tissue processing, including physical ROI marking, reversal of tissue clearing, tissue macrosectioning, and multiplex immunofluorescence, we established a workflow that enables the tracking and 3D imaging of ROIs within tumor tissues through sequential light sheet and confocal fluorescence microscopy. This approach allowed for quantitative 3D spatial analysis of the immune response in the TME of a mouse mammary tumor following cancer immunotherapy at multiple spatial scales. The workflow also facilitated the direct localization of a metastatic lesion within a whole mouse brain. These results demonstrate that our ROI tracking method and its associated workflow offer a novel approach for correlative multiscale 3D optical microscopy, with the potential to provide new insights into tumor heterogeneity, metastasis, and response to therapy at various spatial levels.
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Chen FD, Sharma A, Roszko DA, Xue T, Mu X, Luo X, Chua H, Lo PGQ, Sacher WD, Poon JKS. Development of wafer-scale multifunctional nanophotonic neural probes for brain activity mapping. LAB ON A CHIP 2024; 24:2397-2417. [PMID: 38623840 DOI: 10.1039/d3lc00931a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
Optical techniques, such as optogenetic stimulation and functional fluorescence imaging, have been revolutionary for neuroscience by enabling neural circuit analysis with cell-type specificity. To probe deep brain regions, implantable light sources are crucial. Silicon photonics, commonly used for data communications, shows great promise in creating implantable devices with complex optical systems in a compact form factor compatible with high volume manufacturing practices. This article reviews recent developments of wafer-scale multifunctional nanophotonic neural probes. The probes can be realized on 200 or 300 mm wafers in commercial foundries and integrate light emitters for photostimulation, microelectrodes for electrophysiological recording, and microfluidic channels for chemical delivery and sampling. By integrating active optical devices to the probes, denser emitter arrays, enhanced on-chip biosensing, and increased ease of use may be realized. Silicon photonics technology makes possible highly versatile implantable neural probes that can transform neuroscience experiments.
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Affiliation(s)
- Fu Der Chen
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
| | - Ankita Sharma
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
| | - David A Roszko
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
| | - Tianyuan Xue
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
| | - Xin Mu
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
| | - Xianshu Luo
- Advanced Micro Foundry Pte Ltd, 11 Science Park Road, Singapore Science Park II, 117685, Singapore
| | - Hongyao Chua
- Advanced Micro Foundry Pte Ltd, 11 Science Park Road, Singapore Science Park II, 117685, Singapore
| | - Patrick Guo-Qiang Lo
- Advanced Micro Foundry Pte Ltd, 11 Science Park Road, Singapore Science Park II, 117685, Singapore
| | - Wesley D Sacher
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
| | - Joyce K S Poon
- Max Planck Institute of Microstructure Physics, Weinberg 2, 06120 Halle, Germany.
- Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ontario M5S 3G4, Canada
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7
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Bishop KW, Erion Barner LA, Han Q, Baraznenok E, Lan L, Poudel C, Gao G, Serafin RB, Chow SSL, Glaser AK, Janowczyk A, Brenes D, Huang H, Miyasato D, True LD, Kang S, Vaughan JC, Liu JTC. An end-to-end workflow for nondestructive 3D pathology. Nat Protoc 2024; 19:1122-1148. [PMID: 38263522 DOI: 10.1038/s41596-023-00934-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/23/2023] [Indexed: 01/25/2024]
Abstract
Recent advances in 3D pathology offer the ability to image orders of magnitude more tissue than conventional pathology methods while also providing a volumetric context that is not achievable with 2D tissue sections, and all without requiring destructive tissue sectioning. Generating high-quality 3D pathology datasets on a consistent basis, however, is not trivial and requires careful attention to a series of details during tissue preparation, imaging and initial data processing, as well as iterative optimization of the entire process. Here, we provide an end-to-end procedure covering all aspects of a 3D pathology workflow (using light-sheet microscopy as an illustrative imaging platform) with sufficient detail to perform well-controlled preclinical and clinical studies. Although 3D pathology is compatible with diverse staining protocols and computationally generated color palettes for visual analysis, this protocol focuses on the use of a fluorescent analog of hematoxylin and eosin, which remains the most common stain used for gold-standard pathological reports. We present our guidelines for a broad range of end users (e.g., biologists, clinical researchers and engineers) in a simple format. The end-to-end workflow requires 3-6 d to complete, bearing in mind that data analysis may take longer.
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Affiliation(s)
- Kevin W Bishop
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | | | - Qinghua Han
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Elena Baraznenok
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
| | - Lydia Lan
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
- Department of Biology, University of Washington, Seattle, WA, USA
| | - Chetan Poudel
- Department of Chemistry, University of Washington, Seattle, WA, USA
| | - Gan Gao
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Robert B Serafin
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Sarah S L Chow
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Adam K Glaser
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Andrew Janowczyk
- Department of Biomedical Engineering, Emory University, Atlanta, GA, USA
- Department of Oncology, Division of Precision Oncology, University Hospital of Geneva, Geneva, Switzerland
- Department of Diagnostics, Division of Clinical Pathology, University Hospital of Geneva, Geneva, Switzerland
| | - David Brenes
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Hongyi Huang
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Dominie Miyasato
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Lawrence D True
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Soyoung Kang
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA
| | - Joshua C Vaughan
- Department of Chemistry, University of Washington, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Jonathan T C Liu
- Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
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Wang J, Xu X, Ye H, Zhang X, Shi G. Interferometric modulation for generating extended light sheet: improving field of view. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:046501. [PMID: 38629030 PMCID: PMC11020319 DOI: 10.1117/1.jbo.29.4.046501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/20/2024] [Accepted: 03/27/2024] [Indexed: 04/19/2024]
Abstract
Significance Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful and versatile imaging technique renowned for its remarkable features, including high-speed 3D tomography, minimal photobleaching, and low phototoxicity. The interference light-sheet fluorescence microscope, with its larger field of view (FOV) and more uniform axial resolution, possesses significant potential for a wide range of applications in biology and medicine. Aim The aim of this study is to investigate the interference behavior among multiple light sheets (LSs) in LSFM and optimize the FOV and resolution of the light-sheet fluorescence microscope. Approach We conducted a detailed investigation of the interference effects among LSs through theoretical derivation and numerical simulations, aiming to find optimal parameters. Subsequently, we constructed a customized system of multi-LSFM that incorporates both interference light sheets (ILS) and noninterference light-sheet configurations. We performed beam imaging and microsphere imaging tests to evaluate the FOV and axial resolution of these systems. Results Using our custom-designed light-sheet fluorescence microscope, we captured the intensity distribution profiles of both interference and noninterference light sheets (NILS). Additionally, we conducted imaging tests on microspheres to assess their imaging outcomes. The ILS not only exhibits a larger FOV compared to the NILS but also demonstrates a more uniform axial resolution. Conclusions By effectively modulating the interference among multiple LSs, it is possible to optimize the intensity distribution of the LSs, expand the FOV, and achieve a more uniform axial resolution.
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Affiliation(s)
- Jixiang Wang
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Xu
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Hong Ye
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Xin Zhang
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
| | - Guohua Shi
- University of Science and Technology of China, School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, Hefei, China
- Chinese Academy of Science, Suzhou Institute of Biomedical Engineering and Technology, Jiangsu Key Laboratory of Medical Optics, Suzhou, China
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9
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Ko J, Hyung S, Cheong S, Chung Y, Li Jeon N. Revealing the clinical potential of high-resolution organoids. Adv Drug Deliv Rev 2024; 207:115202. [PMID: 38336091 DOI: 10.1016/j.addr.2024.115202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 01/01/2024] [Accepted: 02/02/2024] [Indexed: 02/12/2024]
Abstract
The symbiotic interplay of organoid technology and advanced imaging strategies yields innovative breakthroughs in research and clinical applications. Organoids, intricate three-dimensional cell cultures derived from pluripotent or adult stem/progenitor cells, have emerged as potent tools for in vitro modeling, reflecting in vivo organs and advancing our grasp of tissue physiology and disease. Concurrently, advanced imaging technologies such as confocal, light-sheet, and two-photon microscopy ignite fresh explorations, uncovering rich organoid information. Combined with advanced imaging technologies and the power of artificial intelligence, organoids provide new insights that bridge experimental models and real-world clinical scenarios. This review explores exemplary research that embodies this technological synergy and how organoids reshape personalized medicine and therapeutics.
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Affiliation(s)
- Jihoon Ko
- Department of BioNano Technology, Gachon University, Gyeonggi 13120, Republic of Korea
| | - Sujin Hyung
- Precision Medicine Research Institute, Samsung Medical Center, Seoul 08826, Republic of Korea; Division of Hematology-Oncology, Department of Medicine, Sungkyunkwan University, Samsung Medical Center, Seoul 08826, Republic of Korea
| | - Sunghun Cheong
- Interdisciplinary Program in Bioengineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
| | - Yoojin Chung
- Division of Computer Engineering, Hankuk University of Foreign Studies, Yongin 17035, Republic of Korea
| | - Noo Li Jeon
- Interdisciplinary Program in Bioengineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Department of Mechanical Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Institute of Advanced Machines and Design, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea; Qureator, Inc., San Diego, CA, USA.
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10
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Julia A, Iguernaissi R, Michel FJ, Matarazzo V, Merad D. Distortion Correction and Denoising of Light Sheet Fluorescence Images. SENSORS (BASEL, SWITZERLAND) 2024; 24:2053. [PMID: 38610265 PMCID: PMC11014158 DOI: 10.3390/s24072053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/14/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024]
Abstract
Light Sheet Fluorescence Microscopy (LSFM) has emerged as a valuable tool for neurobiologists, enabling the rapid and high-quality volumetric imaging of mice brains. However, inherent artifacts and distortions introduced during the imaging process necessitate careful enhancement of LSFM images for optimal 3D reconstructions. This work aims to correct images slice by slice before reconstructing 3D volumes. Our approach involves a three-step process: firstly, the implementation of a deblurring algorithm using the work of K. Becker; secondly, an automatic contrast enhancement; and thirdly, the development of a convolutional denoising auto-encoder featuring skip connections to effectively address noise introduced by contrast enhancement, particularly excelling in handling mixed Poisson-Gaussian noise. Additionally, we tackle the challenge of axial distortion in LSFM by introducing an approach based on an auto-encoder trained on bead calibration images. The proposed pipeline demonstrates a complete solution, presenting promising results that surpass existing methods in denoising LSFM images. These advancements hold potential to significantly improve the interpretation of biological data.
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Affiliation(s)
- Adrien Julia
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Rabah Iguernaissi
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
| | - François J. Michel
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Valéry Matarazzo
- INMED, INSERM, Institut de Neurobiologie de la Méditerranée, Institut National de la Santé et de la Recherche Médicale, Aix Marseille University, 13284 Marseille, France; (F.J.M.)
| | - Djamal Merad
- LIS, CNRS, Laboratoire d’Informatique et des Systèmes, Centre National de la Recherche Scientifique, Aix Marseille University, 13284 Marseille, France
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11
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Pesce L, Ricci P, Sportelli G, Belcari N, Sancataldo G. Expansion and Light-Sheet Microscopy for Nanoscale 3D Imaging. SMALL METHODS 2024:e2301715. [PMID: 38461540 DOI: 10.1002/smtd.202301715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 02/10/2024] [Indexed: 03/12/2024]
Abstract
Expansion Microscopy (ExM) and Light-Sheet Fluorescence Microscopy (LSFM) are forefront imaging techniques that enable high-resolution visualization of biological specimens. ExM enhances nanoscale investigation using conventional fluorescence microscopes, while LSFM offers rapid, minimally invasive imaging over large volumes. This review explores the joint advancements of ExM and LSFM, focusing on the excellent performance of the integrated modality obtained from the combination of the two, which is refer to as ExLSFM. In doing so, the chemical processes required for ExM, the tailored optical setup of LSFM for examining expanded samples, and the adjustments in sample preparation for accurate data collection are emphasized. It is delve into various specimen types studied using this integrated method and assess its potential for future applications. The goal of this literature review is to enrich the comprehension of ExM and LSFM, encouraging their wider use and ongoing development, looking forward to the upcoming challenges, and anticipating innovations in these imaging techniques.
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Affiliation(s)
- Luca Pesce
- Department of Physics - Enrico Fermi, University of Pisa, Largo Pontecorvo, 3, Pisa, 56127, Italy
| | - Pietro Ricci
- Department of Applied Physics, University of Barcelona, C/Martí i Franquès, 1, Barcelona, 08028, Spain
| | - Giancarlo Sportelli
- Department of Physics - Enrico Fermi, University of Pisa, Largo Pontecorvo, 3, Pisa, 56127, Italy
| | - Nicola Belcari
- Department of Physics - Enrico Fermi, University of Pisa, Largo Pontecorvo, 3, Pisa, 56127, Italy
| | - Giuseppe Sancataldo
- Department of Physics - Emilio Segrè, University of Palermo, Viale delle Scienze, 18, Palermo, 90128, Italy
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12
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Xiao W, Li P, Kong F, Kong J, Pan A, Long L, Yan X, Xiao B, Gong J, Wan L. Unraveling the Neural Circuits: Techniques, Opportunities and Challenges in Epilepsy Research. Cell Mol Neurobiol 2024; 44:27. [PMID: 38443733 PMCID: PMC10914928 DOI: 10.1007/s10571-024-01458-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Accepted: 01/24/2024] [Indexed: 03/07/2024]
Abstract
Epilepsy, a prevalent neurological disorder characterized by high morbidity, frequent recurrence, and potential drug resistance, profoundly affects millions of people globally. Understanding the microscopic mechanisms underlying seizures is crucial for effective epilepsy treatment, and a thorough understanding of the intricate neural circuits underlying epilepsy is vital for the development of targeted therapies and the enhancement of clinical outcomes. This review begins with an exploration of the historical evolution of techniques used in studying neural circuits related to epilepsy. It then provides an extensive overview of diverse techniques employed in this domain, discussing their fundamental principles, strengths, limitations, as well as their application. Additionally, the synthesis of multiple techniques to unveil the complexity of neural circuits is summarized. Finally, this review also presents targeted drug therapies associated with epileptic neural circuits. By providing a critical assessment of methodologies used in the study of epileptic neural circuits, this review seeks to enhance the understanding of these techniques, stimulate innovative approaches for unraveling epilepsy's complexities, and ultimately facilitate improved treatment and clinical translation for epilepsy.
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Affiliation(s)
- Wenjie Xiao
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China
| | - Peile Li
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China
| | - Fujiao Kong
- Department of Anesthesiology, Xiangya Hospital, Central South University, Changsha, Hunan Province, China
| | - Jingyi Kong
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China
| | - Aihua Pan
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China
| | - Lili Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaoxin Yan
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Jiaoe Gong
- Department of Neurology, Hunan Children's Hospital, Changsha, Hunan Province, China.
| | - Lily Wan
- Department of Anatomy and Neurobiology, Central South University Xiangya Medical School, Changsha, Hunan Province, China.
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13
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Nozdriukhin D, Kalva SK, Özsoy C, Reiss M, Li W, Razansky D, Deán‐Ben XL. Multi-Scale Volumetric Dynamic Optoacoustic and Laser Ultrasound (OPLUS) Imaging Enabled by Semi-Transparent Optical Guidance. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306087. [PMID: 38115760 PMCID: PMC10953719 DOI: 10.1002/advs.202306087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 11/05/2023] [Indexed: 12/21/2023]
Abstract
Major biological discoveries are made by interrogating living organisms with light. However, the limited penetration of un-scattered photons within biological tissues limits the depth range covered by optical methods. Deep-tissue imaging is achieved by combining light and ultrasound. Optoacoustic imaging exploits the optical generation of ultrasound to render high-resolution images at depths unattainable with optical microscopy. Recently, laser ultrasound has been suggested as a means of generating broadband acoustic waves for high-resolution pulse-echo ultrasound imaging. Herein, an approach is proposed to simultaneously interrogate biological tissues with light and ultrasound based on layer-by-layer coating of silica optical fibers with a controlled degree of transparency. The time separation between optoacoustic and ultrasound signals collected with a custom-made spherical array transducer is exploited for simultaneous 3D optoacoustic and laser ultrasound (OPLUS) imaging with a single laser pulse. OPLUS is shown to enable large-scale anatomical characterization of tissues along with functional multi-spectral imaging of chromophores and assessment of cardiac dynamics at ultrafast rates only limited by the pulse repetition frequency of the laser. The suggested approach provides a flexible and scalable means for developing a new generation of systems synergistically combining the powerful capabilities of optoacoustics and ultrasound imaging in biology and medicine.
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Affiliation(s)
- Daniil Nozdriukhin
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Sandeep Kumar Kalva
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Cagla Özsoy
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Michael Reiss
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Weiye Li
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Daniel Razansky
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
| | - Xosé Luís Deán‐Ben
- Institute of Pharmacology and Toxicology and Institute for Biomedical EngineeringFaculty of MedicineUniversity of ZürichWinterthurerstrasse 190Zürich8057Switzerland
- Institute for Biomedical Engineering, Department of Information Technology and Electrical EngineeringETH ZürichWolfgang‐Pauli‐Strasse 27Zürich8093Switzerland
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14
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Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, Yuste R. Automatic monitoring of neural activity with single-cell resolution in behaving Hydra. Sci Rep 2024; 14:5083. [PMID: 38429381 PMCID: PMC10907378 DOI: 10.1038/s41598-024-55608-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 02/26/2024] [Indexed: 03/03/2024] Open
Abstract
The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.
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Affiliation(s)
- Alison Hanson
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA.
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY, USA.
| | - Raphael Reme
- UMR3691, BioImage Analysis Unit, Institut Pasteur, Université Paris Cité, CNRS, Paris, France
| | - Noah Telerman
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
| | - Wataru Yamamoto
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
| | | | - Thibault Lagache
- UMR3691, BioImage Analysis Unit, Institut Pasteur, Université Paris Cité, CNRS, Paris, France
| | - Rafael Yuste
- Department of Biological Sciences, Neurotechnology Center, Columbia University, New York, NY, USA
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15
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Caznok Silveira AC, Antunes ASLM, Athié MCP, da Silva BF, Ribeiro dos Santos JV, Canateli C, Fontoura MA, Pinto A, Pimentel-Silva LR, Avansini SH, de Carvalho M. Between neurons and networks: investigating mesoscale brain connectivity in neurological and psychiatric disorders. Front Neurosci 2024; 18:1340345. [PMID: 38445254 PMCID: PMC10912403 DOI: 10.3389/fnins.2024.1340345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 01/29/2024] [Indexed: 03/07/2024] Open
Abstract
The study of brain connectivity has been a cornerstone in understanding the complexities of neurological and psychiatric disorders. It has provided invaluable insights into the functional architecture of the brain and how it is perturbed in disorders. However, a persistent challenge has been achieving the proper spatial resolution, and developing computational algorithms to address biological questions at the multi-cellular level, a scale often referred to as the mesoscale. Historically, neuroimaging studies of brain connectivity have predominantly focused on the macroscale, providing insights into inter-regional brain connections but often falling short of resolving the intricacies of neural circuitry at the cellular or mesoscale level. This limitation has hindered our ability to fully comprehend the underlying mechanisms of neurological and psychiatric disorders and to develop targeted interventions. In light of this issue, our review manuscript seeks to bridge this critical gap by delving into the domain of mesoscale neuroimaging. We aim to provide a comprehensive overview of conditions affected by aberrant neural connections, image acquisition techniques, feature extraction, and data analysis methods that are specifically tailored to the mesoscale. We further delineate the potential of brain connectivity research to elucidate complex biological questions, with a particular focus on schizophrenia and epilepsy. This review encompasses topics such as dendritic spine quantification, single neuron morphology, and brain region connectivity. We aim to showcase the applicability and significance of mesoscale neuroimaging techniques in the field of neuroscience, highlighting their potential for gaining insights into the complexities of neurological and psychiatric disorders.
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Affiliation(s)
- Ana Clara Caznok Silveira
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
- School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil
| | | | - Maria Carolina Pedro Athié
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | - Bárbara Filomena da Silva
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | | | - Camila Canateli
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | - Marina Alves Fontoura
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | - Allan Pinto
- Brazilian Synchrotron Light Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | | | - Simoni Helena Avansini
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
| | - Murilo de Carvalho
- National Laboratory of Biosciences, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
- Brazilian Synchrotron Light Laboratory, Brazilian Center for Research in Energy and Materials, Campinas, Brazil
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16
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Page Vizcaíno J, Symvoulidis P, Wang Z, Jelten J, Favaro P, Boyden ES, Lasser T. Fast light-field 3D microscopy with out-of-distribution detection and adaptation through conditional normalizing flows. BIOMEDICAL OPTICS EXPRESS 2024; 15:1219-1232. [PMID: 38404325 PMCID: PMC10890860 DOI: 10.1364/boe.504039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/09/2023] [Accepted: 11/20/2023] [Indexed: 02/27/2024]
Abstract
Real-time 3D fluorescence microscopy is crucial for the spatiotemporal analysis of live organisms, such as neural activity monitoring. The eXtended field-of-view light field microscope (XLFM), also known as Fourier light field microscope, is a straightforward, single snapshot solution to achieve this. The XLFM acquires spatial-angular information in a single camera exposure. In a subsequent step, a 3D volume can be algorithmically reconstructed, making it exceptionally well-suited for real-time 3D acquisition and potential analysis. Unfortunately, traditional reconstruction methods (like deconvolution) require lengthy processing times (0.0220 Hz), hampering the speed advantages of the XLFM. Neural network architectures can overcome the speed constraints but do not automatically provide a way to certify the realism of their reconstructions, which is essential in the biomedical realm. To address these shortcomings, this work proposes a novel architecture to perform fast 3D reconstructions of live immobilized zebrafish neural activity based on a conditional normalizing flow. It reconstructs volumes at 8 Hz spanning 512x512x96 voxels, and it can be trained in under two hours due to the small dataset requirements (50 image-volume pairs). Furthermore, normalizing flows provides a way to compute the exact likelihood of a sample. This allows us to certify whether the predicted output is in- or ood, and retrain the system when a novel sample is detected. We evaluate the proposed method on a cross-validation approach involving multiple in-distribution samples (genetically identical zebrafish) and various out-of-distribution ones.
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Affiliation(s)
- Josué Page Vizcaíno
- Computational Imaging and Inverse Problems, Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, Germany
- Munich Institute of Biomedical Engineering, Technical University of Munich, Germany
| | | | - Zeguan Wang
- Synthetic Neurobiology Group, Massachusetts Institute of Technology, USA
| | - Jonas Jelten
- Computational Imaging and Inverse Problems, Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, Germany
- Munich Institute of Biomedical Engineering, Technical University of Munich, Germany
| | - Paolo Favaro
- Computer Vision Group, University of Bern, Switzerland
| | - Edward S. Boyden
- Synthetic Neurobiology Group, Massachusetts Institute of Technology, USA
| | - Tobias Lasser
- Computational Imaging and Inverse Problems, Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, Germany
- Munich Institute of Biomedical Engineering, Technical University of Munich, Germany
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17
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Cooney PC, Huang Y, Li W, Perera DM, Hormigo R, Tabachnik T, Godage IS, Hillman EMC, Grueber WB, Zarin AA. Neuromuscular basis of Drosophila larval rolling escape behavior. Proc Natl Acad Sci U S A 2023; 120:e2303641120. [PMID: 38096410 PMCID: PMC10743538 DOI: 10.1073/pnas.2303641120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 10/06/2023] [Indexed: 12/18/2023] Open
Abstract
When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larva's circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression leads to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.
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Affiliation(s)
- Patricia C. Cooney
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Neuroscience, Columbia University, New York, NY10027
| | - Yuhan Huang
- Department of Biology, Texas A&M University, College Station, TX77843
- Zarin Laboratory, Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX77843
| | - Wenze Li
- Laboratory for Functional Optical Imaging, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Electrical Engineering, Columbia University, New York, NY10027
| | - Dulanjana M. Perera
- Department of Multidisciplinary Engineering, Texas A&M University, College Station, TX77843
| | - Richard Hormigo
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
| | - Tanya Tabachnik
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
| | - Isuru S. Godage
- Department of Multidisciplinary Engineering, Texas A&M University, College Station, TX77843
- Department of Engineering Technology and Industrial Distribution, Texas A&M University, College Station, TX77843
- J. Mike Walker ‘66 Department of Mechanical Engineering, Texas A&M University, College Station, TX77843
| | - Elizabeth M. C. Hillman
- Laboratory for Functional Optical Imaging, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Biomedical Engineering, Columbia University, New York, NY10027
- Laboratory for Functional Optical Imaging, Kavli Institute for Brain Science, Columbia University, New York, NY10032
| | - Wesley B. Grueber
- Grueber Laboratory, Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY10027
- Department of Neuroscience, Columbia University, New York, NY10027
- Department of Physiology and Cellular Biophysics, Jerome L. Greene Science Center, New York, NY10027
| | - Aref A. Zarin
- Department of Biology, Texas A&M University, College Station, TX77843
- Zarin Laboratory, Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX77843
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18
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Wang Z, Zhang J, Symvoulidis P, Guo W, Zhang L, Wilson MA, Boyden ES. Imaging the voltage of neurons distributed across entire brains of larval zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.15.571964. [PMID: 38168290 PMCID: PMC10760087 DOI: 10.1101/2023.12.15.571964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Neurons interact in networks distributed throughout the brain. Although much effort has focused on whole-brain calcium imaging, recent advances in genetically encoded voltage indicators (GEVIs) raise the possibility of imaging voltage of neurons distributed across brains. To achieve this, a microscope must image at high volumetric rate and signal-to-noise ratio. We present a remote scanning light-sheet microscope capable of imaging GEVI-expressing neurons distributed throughout entire brains of larval zebrafish at a volumetric rate of 200.8 Hz. We measured voltage of ∼1/3 of the neurons of the brain, distributed throughout. We observed that neurons firing at different times during a sequence were located at different brain locations, for sequences elicited by a visual stimulus, which mapped onto locations throughout the optic tectum, as well as during stimulus-independent bursts, which mapped onto locations in the cerebellum and medulla. Whole-brain voltage imaging may open up frontiers in the fundamental operation of neural systems.
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19
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Jiang T, Gong H, Yuan J. Whole-brain Optical Imaging: A Powerful Tool for Precise Brain Mapping at the Mesoscopic Level. Neurosci Bull 2023; 39:1840-1858. [PMID: 37715920 PMCID: PMC10661546 DOI: 10.1007/s12264-023-01112-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 05/08/2023] [Indexed: 09/18/2023] Open
Abstract
The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons. Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain. Optical approaches can achieve submicron lateral resolution and achieve "optical sectioning" by a variety of means, which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level. Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues. Combined with various fluorescent labeling techniques, whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells, circuits, and blood vessels. In this review, we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.
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Affiliation(s)
- Tao Jiang
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
| | - Hui Gong
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Jing Yuan
- Huazhong University of Science and Technology-Suzhou Institute for Brainsmatics, Jiangsu Industrial Technology Research Institute, Suzhou, 215123, China.
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China.
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20
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Li C, Rai MR, Cai Y, Ghashghaei HT, Greenbaum A. Enhancing Light-Sheet Fluorescence Microscopy Illumination Beams through Deep Design Optimization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.569329. [PMID: 38077074 PMCID: PMC10705487 DOI: 10.1101/2023.11.29.569329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2023]
Abstract
Light sheet fluorescence microscopy (LSFM) provides the benefit of optical sectioning coupled with rapid acquisition times for imaging of tissue-cleared specimen. This allows for high-resolution 3D imaging of large tissue volumes. Inherently to LSFM, the quality of the imaging heavily relies on the characteristics of the illumination beam, with the notion that the illumination beam only illuminates a thin section that is being imaged. Therefore, substantial efforts are dedicated to identifying slender, non-diffracting beam profiles that can yield uniform and high-contrast images. An ongoing debate concerns the employment of the most optimal illumination beam; Gaussian, Bessel, Airy patterns and/or others. Comparisons among different beam profiles is challenging as their optimization objective is often different. Given that our large imaging datasets (~0.5TB images per sample) is already analyzed using deep learning models, we envisioned a different approach to this problem by hypothesizing that we can tailor the illumination beam to boost the deep learning models performance. We achieve this by integrating the physical LSFM illumination model after passing through a variable phase mask into the training of a cell detection network. Here we report that the joint optimization continuously updates the phase mask, improving the image quality for better cell detection. Our method's efficacy is demonstrated through both simulations and experiments, revealing substantial enhancements in imaging quality compared to traditional Gaussian light sheet. We offer valuable insights for designing microscopy systems through a computational approach that exhibits significant potential for advancing optics design that relies on deep learning models for analysis of imaging datasets.
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Affiliation(s)
- Chen Li
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - Mani Ratnam Rai
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - Yuheng Cai
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
| | - H. Troy Ghashghaei
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
- Department of Molecular Biomedical Sciences, North Carolina State University, Raleigh, NC 27695, USA
| | - Alon Greenbaum
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, NC 27695, USA
- Comparative Medicine Institute, North Carolina State University, Raleigh, NC 27695, USA
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27695, USA
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21
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Ryu Y, Kim Y, Park SJ, Kim SR, Kim HJ, Ha CM. Comparison of Light-Sheet Fluorescence Microscopy and Fast-Confocal Microscopy for Three-Dimensional Imaging of Cleared Mouse Brain. Methods Protoc 2023; 6:108. [PMID: 37987355 PMCID: PMC10660704 DOI: 10.3390/mps6060108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 11/05/2023] [Accepted: 11/06/2023] [Indexed: 11/22/2023] Open
Abstract
Whole-brain imaging is important for understanding brain functions through deciphering tissue structures, neuronal circuits, and single-neuron tracing. Thus, many clearing methods have been developed to acquire whole-brain images or images of three-dimensional thick tissues. However, there are several limitations to imaging whole-brain volumes, including long image acquisition times, large volumes of data, and a long post-image process. Based on these limitations, many researchers are unsure about which light microscopy is most suitable for imaging thick tissues. Here, we compared fast-confocal microscopy with light-sheet fluorescence microscopy for whole-brain three-dimensional imaging, which can acquire images the fastest. To compare the two types of microscopies for large-volume imaging, we performed tissue clearing of a whole mouse brain, and changed the sample chamber and low- magnification objective lens and modified the sample holder of a light-sheet fluorescence microscope. We found out that light-sheet fluorescence microscopy using a 2.5× objective lens possesses several advantages, including saving time, large-volume image acquisitions, and high Z-resolution, over fast-confocal microscopy, which uses a 4× objective lens. Therefore, we suggest that light-sheet fluorescence microscopy is suitable for whole mouse brain imaging and for obtaining high-resolution three-dimensional images.
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Affiliation(s)
- Youngjae Ryu
- Research Strategy Office and Brain Research Core Facilities of Korea Brain Research Institute, Daegu 41062, Republic of Korea; (Y.R.); (Y.K.)
- Department of Histology, College of Veterinary Medicine, Kyungpook University, Daegu 41566, Republic of Korea;
| | - Yoonju Kim
- Research Strategy Office and Brain Research Core Facilities of Korea Brain Research Institute, Daegu 41062, Republic of Korea; (Y.R.); (Y.K.)
| | - Sang-Joon Park
- Department of Histology, College of Veterinary Medicine, Kyungpook University, Daegu 41566, Republic of Korea;
| | - Sung Rae Kim
- Dementia Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea; (S.R.K.); (H.-J.K.)
| | - Hyung-Jun Kim
- Dementia Research Group, Korea Brain Research Institute, Daegu 41062, Republic of Korea; (S.R.K.); (H.-J.K.)
| | - Chang Man Ha
- Research Strategy Office and Brain Research Core Facilities of Korea Brain Research Institute, Daegu 41062, Republic of Korea; (Y.R.); (Y.K.)
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22
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Park S, Na M, Chang S, Kim KH. High-resolution open-top axially swept light sheet microscopy. BMC Biol 2023; 21:248. [PMID: 37940973 PMCID: PMC10634022 DOI: 10.1186/s12915-023-01747-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 10/24/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND Open-top light-sheet microscopy (OT-LSM) is a specialized microscopic technique for the high-throughput cellular imaging of optically cleared, large-sized specimens, such as the brain. Despite the development of various OT-LSM techniques, achieving submicron resolution in all dimensions remains. RESULTS We developed a high-resolution open-top axially swept LSM (HR-OTAS-LSM) for high-throughput and high-resolution imaging in all dimensions. High axial and lateral resolutions were achieved by using an aberration-corrected axially swept excitation light sheet in the illumination arm and a high numerical aperture (NA) immersion objective lens in the imaging arm, respectively. The high-resolution, high-throughput visualization of neuronal networks in mouse brain and retina specimens validated the performance of HR-OTAS-LSM. CONCLUSIONS The proposed HR-OTAS-LSM method represents a significant advancement in the high-resolution mapping of cellular networks in biological systems such as the brain and retina.
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Affiliation(s)
- Soohyun Park
- Department of Mechanical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-gu, Pohang, Gyeongbuk, 37673, Republic of Korea
| | - Myeongsu Na
- Department of Research and Development Center, Crayon Technologies, 19 Sanmaru-ro, Guri, Gyeonggi-do, 11901, Republic of Korea
| | - Sunghoe Chang
- Department of Physiology and Biomedical Sciences, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
- Neuroscience Research Institute, Seoul National University College of Medicine, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Ki Hean Kim
- Department of Mechanical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-gu, Pohang, Gyeongbuk, 37673, Republic of Korea.
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23
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Balaram P, Takasaki K, Hellevik A, Tandukar J, Turschak E, MacLennan B, Ouellette N, Torres R, Laughland C, Gliko O, Seshamani S, Perlman E, Taormina M, Peterson E, Juneau Z, Potekhina L, Glaser A, Chandrashekar J, Logsdon M, Cao K, Dylla C, Hatanaka G, Chatterjee S, Ting J, Vumbaco D, Waters J, Bair W, Tsao D, Gao R, Reid C. Microscale visualization of cellular features in adult macaque visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.02.565381. [PMID: 37961179 PMCID: PMC10635096 DOI: 10.1101/2023.11.02.565381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Expansion microscopy and light sheet imaging enable fine-scale resolution of intracellular features that comprise neural circuits. Most current techniques visualize sparsely distributed features across whole brains or densely distributed features within individual brain regions. Here, we visualize dense distributions of immunolabeled proteins across early visual cortical areas in adult macaque monkeys. This process may be combined with multiphoton or magnetic resonance imaging to produce multimodal atlases in large, gyrencephalic brains.
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24
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Dennis EJ, Bibawi P, Dhanerawala ZM, Lynch LA, Wang SSH, Brody CD. Princeton RAtlas: A Common Coordinate Framework for Fully cleared, Whole Rattus norvegicus Brains. Bio Protoc 2023; 13:e4854. [PMID: 37900100 PMCID: PMC10603261 DOI: 10.21769/bioprotoc.4854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 08/11/2023] [Accepted: 08/16/2023] [Indexed: 10/31/2023] Open
Abstract
Whole-brain clearing and imaging methods are becoming more common in mice but have yet to become standard in rats, at least partially due to inadequate clearing from most available protocols. Here, we build on recent mouse-tissue clearing and light-sheet imaging methods and develop and adapt them to rats. We first used cleared rat brains to create an open-source, 3D rat atlas at 25 μm resolution. We then registered and imported other existing labeled volumes and made all of the code and data available for the community (https://github.com/emilyjanedennis/PRA) to further enable modern, whole-brain neuroscience in the rat. Key features • This protocol adapts iDISCO (Renier et al., 2014) and uDISCO (Pan et al., 2016) tissue-clearing techniques to consistently clear rat brains. • This protocol also decreases the number of working hours per day to fit in an 8 h workday. Graphical overview.
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Affiliation(s)
- Emily Jane Dennis
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, USA
| | - Peter Bibawi
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
- Neurology Department, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Zahra M. Dhanerawala
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Laura A. Lynch
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
| | - Samuel S.-H. Wang
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
| | - Carlos D. Brody
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, USA
- Howard Hughes Medical Institute, Princeton University, Princeton, USA
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25
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Tian Y, Johnson GA, Williams RW, White LE. A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology. Front Neurosci 2023; 17:1223226. [PMID: 37841684 PMCID: PMC10569694 DOI: 10.3389/fnins.2023.1223226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/04/2023] [Indexed: 10/17/2023] Open
Abstract
Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues in a mouse model by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and both global and regional deformations. 4. Implement stereological protocols for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cell densities of one brain region in less than 1 min and is highly replicable in cortical and subcortical gray matter regions and structures throughout the brain. This method demonstrates the advantage of not requiring an extensive amount of training data, achieving a F1 score of approximately 0.9 with just 20 training nuclei. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57BL/6J cases and 2 BXD strains. The data represent the variability among specimens for the same brain region and across regions within the specimen. Neuronal densities estimated with our workflow are within the range of values in previous classical stereological studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications for studies of how genetics, environment, and development across the lifespan impact cell numbers in the CNS.
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Affiliation(s)
- Yuqi Tian
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, United States
| | - G. Allan Johnson
- Duke Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, United States
| | - Robert W. Williams
- Department of Genetics, Genomics and Informatics, The University of Tennessee Health Science Center, Memphis, TN, United States
| | - Leonard E. White
- Department of Neurology, Duke University, Durham, NC, United States
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26
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Hanson A, Reme R, Telerman N, Yamamoto W, Olivo-Marin JC, Lagache T, Yuste R. Automatic monitoring of whole-body neural activity in behaving Hydra. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.22.559063. [PMID: 37790332 PMCID: PMC10542483 DOI: 10.1101/2023.09.22.559063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/05/2023]
Abstract
The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neuron's calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.
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Affiliation(s)
- Alison Hanson
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University, New York, NY, USA
| | - Raphael Reme
- Institut Pasteur, Université Paris Cité, CNRS UMR3691, BioImage Analysis Unit, Paris, France
| | - Noah Telerman
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Wataru Yamamoto
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
| | | | - Thibault Lagache
- Institut Pasteur, Université Paris Cité, CNRS UMR3691, BioImage Analysis Unit, Paris, France
| | - Rafael Yuste
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA
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27
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Cooney PC, Huang Y, Li W, Perera DM, Hormigo R, Tabachnik T, Godage I, Hillman EMC, Grueber WB, Zarin AA. Neuromuscular Basis of Drosophila larval rolling escape behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.01.526733. [PMID: 36778508 PMCID: PMC9915593 DOI: 10.1101/2023.02.01.526733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
When threatened by dangerous or harmful stimuli, animals engage in diverse forms of rapid escape behaviors. In Drosophila larvae, one type of escape response involves C-shaped bending and lateral rolling followed by rapid forward crawling. The sensory circuitry that promotes larval escape has been extensively characterized; however, the motor programs underlying rolling are unknown. Here, we characterize the neuromuscular basis of rolling escape behavior. We used high-speed, volumetric, Swept Confocally-Aligned Planar Excitation (SCAPE) microscopy to image muscle activity during larval rolling. Unlike sequential peristaltic muscle contractions that progress from segment to segment during forward and backward crawling, the muscle activity progresses circumferentially during bending and rolling escape behavior. We propose that progression of muscular contraction around the larval circumference results in a transient misalignment between weight and the ground support forces, which generates a torque that induces stabilizing body rotation. Therefore, successive cycles of slight misalignment followed by reactive aligning rotation lead to continuous rolling motion. Supporting our biomechanical model, we found that disrupting the activity of muscle groups undergoing circumferential contraction progression lead to rolling defects. We use EM connectome data to identify premotor to motor connectivity patterns that could drive rolling behavior, and perform neural silencing approaches to demonstrate the crucial role of a group of glutamatergic premotor neurons in rolling. Our data reveal body-wide muscle activity patterns and putative premotor circuit organization for execution of the rolling escape response.
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28
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Bishop KW, Barner LAE, Han Q, Baraznenok E, Lan L, Poudel C, Gao G, Serafin RB, Chow SS, Glaser AK, Janowczyk A, Brenes D, Huang H, Miyasato D, True LD, Kang S, Vaughan JC, Liu JT. An end-to-end workflow for non-destructive 3D pathology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.03.551845. [PMID: 37577615 PMCID: PMC10418226 DOI: 10.1101/2023.08.03.551845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Recent advances in 3D pathology offer the ability to image orders-of-magnitude more tissue than conventional pathology while providing a volumetric context that is lacking with 2D tissue sections, all without requiring destructive tissue sectioning. Generating high-quality 3D pathology datasets on a consistent basis is non-trivial, requiring careful attention to many details regarding tissue preparation, imaging, and data/image processing in an iterative process. Here we provide an end-to-end protocol covering all aspects of a 3D pathology workflow (using light-sheet microscopy as an illustrative imaging platform) with sufficient detail to perform well-controlled preclinical and clinical studies. While 3D pathology is compatible with diverse staining protocols and computationally generated color palettes for visual analysis, this protocol will focus on a fluorescent analog of hematoxylin and eosin (H&E), which remains the most common stain for gold-standard diagnostic determinations. We present our guidelines for a broad range of end-users (e.g., biologists, clinical researchers, and engineers) in a simple tutorial format.
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Affiliation(s)
- Kevin W. Bishop
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | | | - Qinghua Han
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Elena Baraznenok
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
| | - Lydia Lan
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
- Department of Biology, University of Washington, Seattle, Washington, USA
| | - Chetan Poudel
- Department of Chemistry, University of Washington, Seattle, Washington, USA
| | - Gan Gao
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Robert B. Serafin
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Sarah S.L. Chow
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Adam K. Glaser
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Andrew Janowczyk
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA
- Department of Oncology, Division of Precision Oncology, University Hospital of Geneva, Geneva, Switzerland
- Department of Clinical Pathology, Division of Clinical Pathology, University Hospital of Geneva, Geneva, Switzerland
| | - David Brenes
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Hongyi Huang
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Dominie Miyasato
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Lawrence D. True
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
| | - Soyoung Kang
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
| | - Joshua C. Vaughan
- Department of Chemistry, University of Washington, Seattle, Washington, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, Washington, USA
| | - Jonathan T.C. Liu
- Department of Mechanical Engineering, University of Washington, Seattle, Washington, USA
- Department of Bioengineering, University of Washington, Seattle, Washington, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, Washington, USA
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29
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Jacobs EAK, Ryu S. Larval zebrafish as a model for studying individual variability in translational neuroscience research. Front Behav Neurosci 2023; 17:1143391. [PMID: 37424749 PMCID: PMC10328419 DOI: 10.3389/fnbeh.2023.1143391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/22/2023] [Indexed: 07/11/2023] Open
Abstract
The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.
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Affiliation(s)
- Elina A. K. Jacobs
- Institute of Human Genetics, University Medical Center of Johannes Gutenberg University Mainz, Mainz, Germany
| | - Soojin Ryu
- Institute of Human Genetics, University Medical Center of Johannes Gutenberg University Mainz, Mainz, Germany
- Living Systems Institute, Faculty of Health and Life Sciences, University of Exeter, Exeter, United Kingdom
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30
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Samimi K, Desa DE, Lin W, Weiss K, Li J, Huisken J, Miskolci V, Huttenlocher A, Chacko JV, Velten A, Rogers JD, Eliceiri KW, Skala MC. Light-sheet autofluorescence lifetime imaging with a single-photon avalanche diode array. JOURNAL OF BIOMEDICAL OPTICS 2023; 28:066502. [PMID: 37351197 PMCID: PMC10284079 DOI: 10.1117/1.jbo.28.6.066502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 05/02/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023]
Abstract
Significance Fluorescence lifetime imaging microscopy (FLIM) of the metabolic co-enzyme nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] is a popular method to monitor single-cell metabolism within unperturbed, living 3D systems. However, FLIM of NAD(P)H has not been performed in a light-sheet geometry, which is advantageous for rapid imaging of cells within live 3D samples. Aim We aim to design, validate, and demonstrate a proof-of-concept light-sheet system for NAD(P)H FLIM. Approach A single-photon avalanche diode camera was integrated into a light-sheet microscope to achieve optical sectioning and limit out-of-focus contributions for NAD(P)H FLIM of single cells. Results An NAD(P)H light-sheet FLIM system was built and validated with fluorescence lifetime standards and with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times. NAD(P)H light-sheet FLIM in vivo was demonstrated with live neutrophil imaging in a larval zebrafish tail wound also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light-sheet geometries, indicating a 30 × to 6 × acquisition speed advantage for the light sheet compared to the laser scanning geometry. Conclusions FLIM of NAD(P)H is feasible in a light-sheet geometry and is attractive for 3D live cell imaging applications, such as monitoring immune cell metabolism and migration within an organism.
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Affiliation(s)
- Kayvan Samimi
- Morgridge Institute for Research, Madison, Wisconsin, United States
| | - Danielle E. Desa
- Morgridge Institute for Research, Madison, Wisconsin, United States
| | - Wei Lin
- University of Wisconsin, Department of Electrical and Computer Engineering, Madison, Wisconsin, United States
| | - Kurt Weiss
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin, Department of Biochemistry, Madison, Wisconsin, United States
| | - Joe Li
- Morgridge Institute for Research, Madison, Wisconsin, United States
| | - Jan Huisken
- Morgridge Institute for Research, Madison, Wisconsin, United States
- Georg-August-University Göttingen, Department of Biology and Psychology, Göttingen, Germany
| | - Veronika Miskolci
- University of Wisconsin, Department of Medical Microbiology and Immunology, Madison, Wisconsin, United States
- Rutgers New Jersey Medical School, Center for Cell Signaling, Newark, New Jersey, United States
- Rutgers New Jersey Medical School, Department of Microbiology, Biochemistry and Molecular Genetics, Newark, New Jersey, United States
| | - Anna Huttenlocher
- University of Wisconsin, Department of Medical Microbiology and Immunology, Madison, Wisconsin, United States
- University of Wisconsin, Department of Pediatrics, Madison, Wisconsin, United States
| | - Jenu V. Chacko
- University of Wisconsin, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
| | - Andreas Velten
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin, Department of Electrical and Computer Engineering, Madison, Wisconsin, United States
- University of Wisconsin, Department of Biostatistics and Medical Informatics, Madison, Wisconsin, United States
- University of Wisconsin, McPherson Eye Research Institute, Madison, Wisconsin, United States
| | - Jeremy D. Rogers
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin, McPherson Eye Research Institute, Madison, Wisconsin, United States
- University of Wisconsin, Department of Ophthalmology and Visual Sciences, Madison, Wisconsin, United States
| | - Kevin W. Eliceiri
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin, Laboratory for Optical and Computational Instrumentation, Madison, Wisconsin, United States
- University of Wisconsin, Department of Biostatistics and Medical Informatics, Madison, Wisconsin, United States
- University of Wisconsin, McPherson Eye Research Institute, Madison, Wisconsin, United States
- University of Wisconsin, Department of Biomedical Engineering, Madison, Wisconsin, United States
| | - Melissa C. Skala
- Morgridge Institute for Research, Madison, Wisconsin, United States
- University of Wisconsin, McPherson Eye Research Institute, Madison, Wisconsin, United States
- University of Wisconsin, Department of Biomedical Engineering, Madison, Wisconsin, United States
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31
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Zhang X, Li H, Ma Y, Zhong D, Hou S. Study liquid-liquid phase separation with optical microscopy: A methodology review. APL Bioeng 2023; 7:021502. [PMID: 37180732 PMCID: PMC10171890 DOI: 10.1063/5.0137008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 04/28/2023] [Indexed: 05/16/2023] Open
Abstract
Intracellular liquid-liquid phase separation (LLPS) is a critical process involving the dynamic association of biomolecules and the formation of non-membrane compartments, playing a vital role in regulating biomolecular interactions and organelle functions. A comprehensive understanding of cellular LLPS mechanisms at the molecular level is crucial, as many diseases are linked to LLPS, and insights gained can inform drug/gene delivery processes and aid in the diagnosis and treatment of associated diseases. Over the past few decades, numerous techniques have been employed to investigate the LLPS process. In this review, we concentrate on optical imaging methods applied to LLPS studies. We begin by introducing LLPS and its molecular mechanism, followed by a review of the optical imaging methods and fluorescent probes employed in LLPS research. Furthermore, we discuss potential future imaging tools applicable to the LLPS studies. This review aims to provide a reference for selecting appropriate optical imaging methods for LLPS investigations.
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Affiliation(s)
| | | | - Yue Ma
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | | | - Shangguo Hou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
- Authors to whom correspondence should be addressed: and
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32
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Wen C, Matsumoto M, Sawada M, Sawamoto K, Kimura KD. Seg2Link: an efficient and versatile solution for semi-automatic cell segmentation in 3D image stacks. Sci Rep 2023; 13:7109. [PMID: 37217545 DOI: 10.1038/s41598-023-34232-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 04/26/2023] [Indexed: 05/24/2023] Open
Abstract
Recent advances in microscopy techniques, especially in electron microscopy, are transforming biomedical studies by acquiring large quantities of high-precision 3D cell image stacks. To examine cell morphology and connectivity in organs such as the brain, scientists need to conduct cell segmentation, which extracts individual cell regions of different shapes and sizes from a 3D image. This is challenging due to the indistinct images often encountered in real biomedical research: in many cases, automatic segmentation methods inevitably contain numerous mistakes in the segmentation results, even when using advanced deep learning methods. To analyze 3D cell images effectively, a semi-automated software solution is needed that combines powerful deep learning techniques with the ability to perform post-processing, generate accurate segmentations, and incorporate manual corrections. To address this gap, we developed Seg2Link, which takes deep learning predictions as inputs and use watershed 2D + cross-slice linking to generate more accurate automatic segmentations than previous methods. Additionally, it provides various manual correction tools essential for correcting mistakes in 3D segmentation results. Moreover, our software has been optimized for efficiently processing large 3D images in diverse organisms. Thus, Seg2Link offers an practical solution for scientists to study cell morphology and connectivity in 3D image stacks.
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Affiliation(s)
- Chentao Wen
- Graduate School of Science, Nagoya City University, Nagoya, Japan.
- RIKEN Center for Biosystems Dynamics Research, Kobe, Japan.
| | - Mami Matsumoto
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Masato Sawada
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
| | - Kazunobu Sawamoto
- Department of Developmental and Regenerative Neurobiology, Institute of Brain Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
- Division of Neural Development and Regeneration, National Institute for Physiological Sciences, Okazaki, Japan
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33
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Tian Y, Johnson GA, Williams RW, White L. A rapid workflow for neuron counting in combined light sheet microscopy and magnetic resonance histology. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.17.540884. [PMID: 37292796 PMCID: PMC10245654 DOI: 10.1101/2023.05.17.540884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Information on regional variation in cell numbers and densities in the CNS provides critical insight into structure, function, and the progression of CNS diseases. However, variability can be real or can be a consequence of methods that do not account for technical biases, including morphologic deformations, errors in the application of cell type labels and boundaries of regions, errors of counting rules and sampling sites. We address these issues of by introducing a workflow that consists of the following steps: 1. Magnetic resonance histology (MRH) to establish the size, shape, and regional morphology of the mouse brain in situ. 2. Light-sheet microscopy (LSM) to selectively label all neurons or other cells in the entire brain without sectioning artifacts. 3. Register LSM volumes to MRH volumes to correct for dissection errors and morphological deformations. 4. Implement novel protocol for automated sampling and counting of cells in 3D LSM volumes. This workflow can analyze the cells density of one brain region in less than 1 min and is highly replicable to cortical and subcortical gray matter regions and structures throughout the brain. We report deformation-corrected neuron (NeuN) counts and neuronal density in 13 representative regions in 5 C57B6/6J and 2 BXD strains. The data represent the variability among cases for the same brain region and across regions within case. Our data are consistent with previous studies. We demonstrate the application of our workflow to a mouse model of aging. This workflow improves the accuracy of neuron counting and the assessment of neuronal density on a region-by-region basis, with broad applications in how genetics, environment, and development across the lifespan impact brain structure.
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Zhang G, Ma X, Qin W, Jia M, Chen M. Editorial: Optical imaging in neuroscience and brain disease. Front Neurosci 2023; 17:1192863. [PMID: 37081938 PMCID: PMC10111033 DOI: 10.3389/fnins.2023.1192863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 04/07/2023] Open
Affiliation(s)
- Guanglei Zhang
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- *Correspondence: Guanglei Zhang
| | - Xibo Ma
- State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China
| | - Wenjian Qin
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (CAS), Shenzhen, China
| | - Mengyu Jia
- School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
| | - Maomao Chen
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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35
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Liu Y, Liu B, Green J, Duffy C, Song M, Lauderdale JD, Kner P. Volumetric light sheet imaging with adaptive optics correction. BIOMEDICAL OPTICS EXPRESS 2023; 14:1757-1771. [PMID: 37078033 PMCID: PMC10110302 DOI: 10.1364/boe.473237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 03/09/2023] [Accepted: 03/10/2023] [Indexed: 05/02/2023]
Abstract
Light sheet microscopy has developed quickly over the past decades and become a popular method for imaging live model organisms and other thick biological tissues. For rapid volumetric imaging, an electrically tunable lens can be used to rapidly change the imaging plane in the sample. For larger fields of view and higher NA objectives, the electrically tunable lens introduces aberrations in the system, particularly away from the nominal focus and off-axis. Here, we describe a system that employs an electrically tunable lens and adaptive optics to image over a volume of 499 × 499 × 192 μm3 with close to diffraction-limited resolution. Compared to the system without adaptive optics, the performance shows an increase in signal to background ratio by a factor of 3.5. While the system currently requires 7s/volume, it should be straightforward to increase the imaging speed to under 1s per volume.
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Affiliation(s)
- Yang Liu
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - Bingxi Liu
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - John Green
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - Carly Duffy
- Dept. of Cellular Biology, University of Georgia, Athens, GA 30602, USA
| | - Ming Song
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
| | - James D. Lauderdale
- Dept. of Cellular Biology, University of Georgia, Athens, GA 30602, USA
- Neuroscience Division of the Biomedical Health Sciences Institute, University of Georgia, Athens, GA 30602, USA
| | - Peter Kner
- School of Electrical and Computer Engineering, University of Georgia, Athens, GA 30602, USA
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36
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Samimi K, Desa DE, Lin W, Weiss K, Li J, Huisken J, Miskolci V, Huttenlocher A, Chacko JV, Velten A, Rogers JD, Eliceiri KW, Skala1 MC. Light sheet autofluorescence lifetime imaging with a single photon avalanche diode array. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.01.526695. [PMID: 36778488 PMCID: PMC9915663 DOI: 10.1101/2023.02.01.526695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Single photon avalanche diode (SPAD) array sensors can increase the imaging speed for fluorescence lifetime imaging microscopy (FLIM) by transitioning from laser scanning to widefield geometries. While a SPAD camera in epi-fluorescence geometry enables widefield FLIM of fluorescently labeled samples, label-free imaging of single-cell autofluorescence is not feasible in an epi-fluorescence geometry because background fluorescence from out-of-focus features masks weak cell autofluorescence and biases lifetime measurements. Here, we address this problem by integrating the SPAD camera in a light sheet illumination geometry to achieve optical sectioning and limit out-of-focus contributions, enabling fast label-free FLIM of single-cell NAD(P)H autofluorescence. The feasibility of this NAD(P)H light sheet FLIM system was confirmed with time-course imaging of metabolic perturbations in pancreas cancer cells with 10 s integration times, and in vivo NAD(P)H light sheet FLIM was demonstrated with live neutrophil imaging in a zebrafish tail wound, also with 10 s integration times. Finally, the theoretical and practical imaging speeds for NAD(P)H FLIM were compared across laser scanning and light sheet geometries, indicating a 30X to 6X frame rate advantage for the light sheet compared to the laser scanning geometry. This light sheet system provides faster frame rates for 3D NAD(P)H FLIM for live cell imaging applications such as monitoring single cell metabolism and immune cell migration throughout an entire living organism.
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Affiliation(s)
| | | | - Wei Lin
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI, USA
| | - Kurt Weiss
- Morgridge Institute for Research, Madison, WI, USA
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA
| | - Joe Li
- Morgridge Institute for Research, Madison, WI, USA
| | - Jan Huisken
- Morgridge Institute for Research, Madison, WI, USA
- Department of Biology and Psychology, Georg-August-University Göttingen, Göttingen, Germany
| | - Veronika Miskolci
- Department of Medical Microbiology and Immunology, University of Wisconsin, Madison, WI, USA
| | - Anna Huttenlocher
- Department of Medical Microbiology and Immunology, University of Wisconsin, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin, Madison, WI, USA
| | - Jenu V. Chacko
- Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA
| | - Andreas Velten
- Morgridge Institute for Research, Madison, WI, USA
- Department of Electrical and Computer Engineering, University of Wisconsin, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
- McPherson Eye Research Institute, University of Wisconsin, Madison, WI, USA
| | - Jeremy D. Rogers
- Morgridge Institute for Research, Madison, WI, USA
- McPherson Eye Research Institute, University of Wisconsin, Madison, WI, USA
- Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison, WI, USA
| | - Kevin W. Eliceiri
- Morgridge Institute for Research, Madison, WI, USA
- Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, WI, USA
- McPherson Eye Research Institute, University of Wisconsin, Madison, WI, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA
| | - Melissa C. Skala1
- McPherson Eye Research Institute, University of Wisconsin, Madison, WI, USA
- Department of Biomedical Engineering, University of Wisconsin, Madison, WI, USA
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37
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Durand S, Heller GR, Ramirez TK, Luviano JA, Williford A, Sullivan DT, Cahoon AJ, Farrell C, Groblewski PA, Bennett C, Siegle JH, Olsen SR. Acute head-fixed recordings in awake mice with multiple Neuropixels probes. Nat Protoc 2023; 18:424-457. [PMID: 36477710 DOI: 10.1038/s41596-022-00768-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 08/09/2022] [Indexed: 12/12/2022]
Abstract
Multi-electrode arrays such as Neuropixels probes enable electrophysiological recordings from large populations of single neurons with high temporal resolution. By using such probes, the activity from functionally interacting, yet distinct, brain regions can be measured simultaneously by inserting multiple probes into the same subject. However, the use of multiple probes in small animals such as mice requires the removal of a sizable fraction of the skull, while also minimizing tissue damage and keeping the brain stable during the recordings. Here, we describe a step-by-step process designed to facilitate reliable recordings from up to six Neuropixels probes simultaneously in awake, head-fixed mice. The procedure involves four stages: the implantation of a headframe and a removable glass coverslip, the precise positioning of the Neuropixels probes at targeted points on the brain surface, the placement of a perforated plastic imaging window and the insertion of the probes into the brain of an awake mouse. The approach provides access to multiple brain regions and has been successfully applied across hundreds of mice. The procedure has been optimized for dense recordings from the mouse visual system, but it can be adapted for alternative recording configurations to target multiple probes in other brain areas. The protocol is suitable for users with experience in stereotaxic surgery in mice.
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Affiliation(s)
| | - Greggory R Heller
- Allen Institute, Seattle, WA, USA.,Department of Brain and Cognitive Sciences, Massachussetts Institute of Technology, Cambridge, MA, USA
| | - Tamina K Ramirez
- Allen Institute, Seattle, WA, USA.,Department of Neurobiology and Behavior, Columbia University, New York, NY, USA
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Zhan YJ, Zhang SW, Zhu S, Jiang N. Tissue Clearing and Its Application in the Musculoskeletal System. ACS OMEGA 2023; 8:1739-1758. [PMID: 36687066 PMCID: PMC9850472 DOI: 10.1021/acsomega.2c05180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
The musculoskeletal system is an integral part of the human body. Currently, most skeletal muscle research is conducted through conventional histological sections due to technological limitations and the structure of skeletal muscles. For studying and observing bones and muscles, there is an urgent need for three-dimensional, objective imaging technologies. Optical tissue-clearing technologies seem to offer a novel and accessible approach to research of the musculoskeletal system. Using this approach, the components which cause refraction or prevent light from penetrating into the tissue are physically and chemically eliminated; then the liquid in the tissue is replaced with high-refractive-index chemicals. This innovative method, which allows three-dimensional reconstruction at the cellular and subcellular scale, significantly improves imaging depth and resolution. Nonetheless, this technology was not originally developed to image bones or muscles. When compared with brain and nerve organs which have attracted considerable attention in this field, the musculoskeletal system contains fewer lipids and has high levels of hemoglobin, collagen fibers, and inorganic hydroxyapatite crystals. Currently, three-dimensional imaging methods are widely used in the diagnosis and treatment of skeletal and muscular illnesses. In this regard, it is vitally important to review and evaluate the optical tissue-clearing technologies currently employed in the musculoskeletal system, so that researchers may make an informed decision. In the meantime, this study offers guidelines and recommendations for expanding the use of this technology in the musculoskeletal system.
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Affiliation(s)
- Yan-Jing Zhan
- State
Key Laboratory of Oral Diseases & National Clinical Research Center
for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Shi-Wen Zhang
- State
Key Laboratory of Oral Diseases & National Clinical Research Center
for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
- West
China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - SongSong Zhu
- State
Key Laboratory of Oral Diseases & National Clinical Research Center
for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
- West
China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
| | - Nan Jiang
- State
Key Laboratory of Oral Diseases & National Clinical Research Center
for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
- West
China Hospital of Stomatology, Sichuan University, Chengdu 610041, China
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Balcaen T, Piens C, Mwema A, Chourrout M, Vandebroek L, Des Rieux A, Chauveau F, De Borggraeve WM, Hoffmann D, Kerckhofs G. Revealing the three-dimensional murine brain microstructure by contrast-enhanced computed tomography. Front Neurosci 2023; 17:1141615. [PMID: 37034159 PMCID: PMC10076597 DOI: 10.3389/fnins.2023.1141615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 03/08/2023] [Indexed: 04/11/2023] Open
Abstract
To improve our understanding of the brain microstructure, high-resolution 3D imaging is used to complement classical 2D histological assessment techniques. X-ray computed tomography allows high-resolution 3D imaging, but requires methods for enhancing contrast of soft tissues. Applying contrast-enhancing staining agents (CESAs) ameliorates the X-ray attenuating properties of soft tissue constituents and is referred to as contrast-enhanced computed tomography (CECT). Despite the large number of chemical compounds that have successfully been applied as CESAs for imaging brain, they are often toxic for the researcher, destructive for the tissue and without proper characterization of affinity mechanisms. We evaluated two sets of chemically related CESAs (organic, iodinated: Hexabrix and CA4+ and inorganic polyoxometalates: 1:2 hafnium-substituted Wells-Dawson phosphotungstate and Preyssler anion), for CECT imaging of healthy murine hemispheres. We then selected the CESA (Hexabrix) that provided the highest contrast between gray and white matter and applied it to a cuprizone-induced demyelination model. Differences in the penetration rate, effect on tissue integrity and affinity for tissue constituents have been observed for the evaluated CESAs. Cuprizone-induced demyelination could be visualized and quantified after Hexabrix staining. Four new non-toxic and non-destructive CESAs to the field of brain CECT imaging were introduced. The added value of CECT was shown by successfully applying it to a cuprizone-induced demyelination model. This research will prove to be crucial for further development of CESAs for ex vivo brain CECT and 3D histopathology.
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Affiliation(s)
- Tim Balcaen
- MolDesignS, Sustainable Chemistry for Metals and Molecules, Department of Chemistry, KU Leuven, Leuven, Belgium
- ContrasT Team, Institute of Mechanics, Materials and Civil Engineering, Mechatronic, Electrical Energy and Dynamic Systems, UCLouvain, Louvain-la-Neuve, Belgium
- Pole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Catherine Piens
- ContrasT Team, Institute of Mechanics, Materials and Civil Engineering, Mechatronic, Electrical Energy and Dynamic Systems, UCLouvain, Louvain-la-Neuve, Belgium
| | - Ariane Mwema
- Advanced Drug Delivery and Biomaterials, UCLouvain, Brussels, Belgium
- Bioanalysis and Pharmacology of Bioactive Lipids, UCLouvain, Brussels, Belgium
| | - Matthieu Chourrout
- Université Claude Bernard Lyon 1, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Centre de Recherche en Neurosciences de Lyon U1028 UMR 5292, Bron, France
| | - Laurens Vandebroek
- Laboratory of Biomolecular Modelling and Design (LBMD), Biochemistry, Molecular and Structural Biology, Department of Chemistry, KU Leuven, Leuven, Belgium
| | - Anne Des Rieux
- Advanced Drug Delivery and Biomaterials, UCLouvain, Brussels, Belgium
| | - Fabien Chauveau
- Université Claude Bernard Lyon 1, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Centre de Recherche en Neurosciences de Lyon U1028 UMR 5292, Bron, France
| | - Wim M. De Borggraeve
- MolDesignS, Sustainable Chemistry for Metals and Molecules, Department of Chemistry, KU Leuven, Leuven, Belgium
| | - Delia Hoffmann
- Pole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
- Prometheus, Division of Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium
- Skeletal Biology and Engineering Research Center, KU Leuven, Leuven, Belgium
| | - Greet Kerckhofs
- ContrasT Team, Institute of Mechanics, Materials and Civil Engineering, Mechatronic, Electrical Energy and Dynamic Systems, UCLouvain, Louvain-la-Neuve, Belgium
- Pole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
- Department Materials Engineering, KU Leuven, Leuven, Belgium
- *Correspondence: Greet Kerckhofs,
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40
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Cao Y, Lee S, Kim K, Kang SH. Minimizing the Optical Illusion of Nanoparticles in Single Cells Using Four-Dimensional Cuboid Multiangle Illumination-Based Light-Sheet Super-Resolution Imaging. Anal Chem 2022; 94:17877-17884. [PMID: 36509731 DOI: 10.1021/acs.analchem.2c03729] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Although light-sheet-based super-resolution microscopy is an excellent detection technique for biological samples because of minimal photodamage, uneven light paths due to solid-angle illumination limits it, resulting in an optical illusion. Furthermore, the optical illusion limits the observations of individual molecules in diffraction. In this study, a four-dimensional cuboid multiangle illumination-based light-sheet super-resolution (4D CMLS) imaging system was developed to minimize optical illusions in cells. The lab-built 4D CMLS imaging system was integrated with total internal reflection fluorescence and a differential interference contrast microscope. A specially designed rotatable cuboid prism simply overcame the optical illusion by rotating a specimen on the prism to change the direction of light coming from an illumination lens. 4D CMLS reconstructed images of nanoparticles of different sizes were acquired in multi-illumination angles of 0°, 90°, 180°, and 270°. Additionally, a 4D multiangle illumination-based algorithm was created to select the optimal illumination angle by combining three-dimensional super-resolution imaging with multiangle observation, even in the presence of obstacles. The 4D CMLS imaging method demonstrates the in-depth 4D observation of samples at an optimum angle that can be used in various applications, such as single-molecule and subcellular organelle observations in single cells at subdiffraction limit resolutions that describe the scenario of nature.
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Affiliation(s)
- Yingying Cao
- Department of Chemistry, Graduate School, Kyung Hee University, Yongin-si, Gyeonggi-do17104, Republic of Korea
| | - Seungah Lee
- Department of Applied Chemistry and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Gyeonggi-do17104, Republic of Korea
| | - Kyungsoo Kim
- Department of Applied Mathematics, Kyung Hee University, Yongin-si, Gyeonggi-do17104, Republic of Korea
| | - Seong Ho Kang
- Department of Chemistry, Graduate School, Kyung Hee University, Yongin-si, Gyeonggi-do17104, Republic of Korea.,Department of Applied Chemistry and Institute of Natural Sciences, Kyung Hee University, Yongin-si, Gyeonggi-do17104, Republic of Korea
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Stouffer KM, Witter MP, Tward DJ, Miller MI. Projective Diffeomorphic Mapping of Molecular Digital Pathology with Tissue MRI. COMMUNICATIONS ENGINEERING 2022; 1:44. [PMID: 37284027 PMCID: PMC10243734 DOI: 10.1038/s44172-022-00044-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 11/28/2022] [Indexed: 06/08/2023]
Abstract
Reconstructing dense 3D anatomical coordinates from 2D projective measurements has become a central problem in digital pathology for both animal models and human studies. Here we describe Projective Large Deformation Diffeomorphic Metric Mapping (LDDMM), a technique which projects diffeomorphic mappings of dense human magnetic resonance imaging (MRI) atlases at tissue scales onto sparse measurements at micrometre scales associated with histological and more general optical imaging modalities. We solve the problem of dense mapping surjectively onto histological sections by incorporating technologies for crossing modalities that use nonlinear scattering transforms to represent multiple radiomic-like textures at micron scales, together with a Gaussian mixture-model framework for modelling tears and distortions associated to each section. We highlight the significance of our method through incorporation of neuropathological measures and MRI, of relevance to the development of biomarkers for Alzheimer's disease and one instance of the integration of imaging data across the scales of clinical imaging and digital pathology.
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Affiliation(s)
- Kaitlin M. Stouffer
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
| | - Menno P. Witter
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Torgarden Norway
| | - Daniel J. Tward
- Departments of Computational Medicine and Neurology, University of California, Los Angeles, CA USA
| | - Michael I. Miller
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD USA
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42
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Liu Z, Zhu Y, Zhang L, Jiang W, Liu Y, Tang Q, Cai X, Li J, Wang L, Tao C, Yin X, Li X, Hou S, Jiang D, Liu K, Zhou X, Zhang H, Liu M, Fan C, Tian Y. Structural and functional imaging of brains. Sci China Chem 2022; 66:324-366. [PMID: 36536633 PMCID: PMC9753096 DOI: 10.1007/s11426-022-1408-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 09/28/2022] [Indexed: 12/23/2022]
Abstract
Analyzing the complex structures and functions of brain is the key issue to understanding the physiological and pathological processes. Although neuronal morphology and local distribution of neurons/blood vessels in the brain have been known, the subcellular structures of cells remain challenging, especially in the live brain. In addition, the complicated brain functions involve numerous functional molecules, but the concentrations, distributions and interactions of these molecules in the brain are still poorly understood. In this review, frontier techniques available for multiscale structure imaging from organelles to the whole brain are first overviewed, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), serial-section electron microscopy (ssEM), light microscopy (LM) and synchrotron-based X-ray microscopy (XRM). Specially, XRM for three-dimensional (3D) imaging of large-scale brain tissue with high resolution and fast imaging speed is highlighted. Additionally, the development of elegant methods for acquisition of brain functions from electrical/chemical signals in the brain is outlined. In particular, the new electrophysiology technologies for neural recordings at the single-neuron level and in the brain are also summarized. We also focus on the construction of electrochemical probes based on dual-recognition strategy and surface/interface chemistry for determination of chemical species in the brain with high selectivity and long-term stability, as well as electrochemophysiological microarray for simultaneously recording of electrochemical and electrophysiological signals in the brain. Moreover, the recent development of brain MRI probes with high contrast-to-noise ratio (CNR) and sensitivity based on hyperpolarized techniques and multi-nuclear chemistry is introduced. Furthermore, multiple optical probes and instruments, especially the optophysiological Raman probes and fiber Raman photometry, for imaging and biosensing in live brain are emphasized. Finally, a brief perspective on existing challenges and further research development is provided.
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Affiliation(s)
- Zhichao Liu
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
| | - Ying Zhu
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Liming Zhang
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
| | - Weiping Jiang
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Yawei Liu
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022 China
| | - Qiaowei Tang
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Xiaoqing Cai
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Jiang Li
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Lihua Wang
- Interdisciplinary Research Center, Shanghai Synchrotron Radiation Facility, Zhangjiang Laboratory, Shanghai Advanced Research Institute, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Shanghai, 201210 China
| | - Changlu Tao
- Interdisciplinary Center for Brain Information, Brain Cognition and Brain Disease Institute, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055 China
| | | | - Xiaowei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Shangguo Hou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055 China
| | - Dawei Jiang
- Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022 China
| | - Kai Liu
- Department of Chemistry, Tsinghua University, Beijing, 100084 China
| | - Xin Zhou
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Hongjie Zhang
- State Key Laboratory of Rare Earth Resource Utilization, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, 130022 China
- Department of Chemistry, Tsinghua University, Beijing, 100084 China
| | - Maili Liu
- State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Chinese Academy of Sciences, Wuhan National Laboratory for Optoelectronics, Wuhan, 430071 China
| | - Chunhai Fan
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules, Institute of Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Yang Tian
- Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, 200241 China
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43
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Ye H, Xu X, Wang J, Wang J, He Y, Mu Y, Shi G. Polarization effects on the fluorescence emission of zebrafish neurons using light-sheet microscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:6733-6744. [PMID: 36589590 PMCID: PMC9774877 DOI: 10.1364/boe.474588] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 11/21/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
Light-sheet fluorescence microscopy (LSFM) makes use of a thin plane of light to optically section and image transparent tissues or organisms in vivo, which has the advantages of fast imaging speed and low phototoxicity. In this paper, we have employed light-sheet microscopy to investigate the polarization effects on fluorescence emission of zebrafish neurons via modifying the electric oscillation orientation of the excitation light. The intensity of the fluorescence emission from the excited zebrafish larvae follows a cosine square function with respect to the polarization state of the excitation light and reveals a 40% higher fluorescence emission when the polarization orientation is orthogonal to the illumination and detection axes. Through registration and subtraction of fluorescence images under different polarization states, we have demonstrated that most of the enhanced fluorescence signals are from the neuronal cells rather than the extracellular substance. This provides us a way to distinguish the cell boundaries and observe the organism structures with improved contrast and resolution.
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Affiliation(s)
- Hong Ye
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
| | - Xin Xu
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
- School of Biomedical Engineering (Suzhou),
Division of Life Sciences and Medicine, University of
Science and Technology of China, Hefei, China
| | - Jixiang Wang
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
- School of Biomedical Engineering (Suzhou),
Division of Life Sciences and Medicine, University of
Science and Technology of China, Hefei, China
| | - Jing Wang
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
- School of Biomedical Engineering (Suzhou),
Division of Life Sciences and Medicine, University of
Science and Technology of China, Hefei, China
| | - Yi He
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
| | - Yu Mu
- Institute of Neuroscience, State Key
Laboratory of Neuroscience, Center for Excellence in Brain Science and
Intelligence Technology, Chinese Academy of
Sciences, Shanghai, China
| | - Guohua Shi
- Jiangsu Key Laboratory of Medical Optics,
Suzhou Institute of Biomedical Engineering and Technology,
Chinese Academy of Sciences, Suzhou,
China
- School of Biomedical Engineering (Suzhou),
Division of Life Sciences and Medicine, University of
Science and Technology of China, Hefei, China
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44
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Costantini I, Axer M, Magnain C, Hof PR. Editorial: The human brain multiscale imaging challenge. Front Neuroanat 2022; 16:1060405. [DOI: 10.3389/fnana.2022.1060405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 10/14/2022] [Indexed: 11/13/2022] Open
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45
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Liu X, Jiang Y, Cui Y, Yuan J, Fang X. Deep learning in single-molecule imaging and analysis: recent advances and prospects. Chem Sci 2022; 13:11964-11980. [PMID: 36349113 PMCID: PMC9600384 DOI: 10.1039/d2sc02443h] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 09/19/2022] [Indexed: 09/19/2023] Open
Abstract
Single-molecule microscopy is advantageous in characterizing heterogeneous dynamics at the molecular level. However, there are several challenges that currently hinder the wide application of single molecule imaging in bio-chemical studies, including how to perform single-molecule measurements efficiently with minimal run-to-run variations, how to analyze weak single-molecule signals efficiently and accurately without the influence of human bias, and how to extract complete information about dynamics of interest from single-molecule data. As a new class of computer algorithms that simulate the human brain to extract data features, deep learning networks excel in task parallelism and model generalization, and are well-suited for handling nonlinear functions and extracting weak features, which provide a promising approach for single-molecule experiment automation and data processing. In this perspective, we will highlight recent advances in the application of deep learning to single-molecule studies, discuss how deep learning has been used to address the challenges in the field as well as the pitfalls of existing applications, and outline the directions for future development.
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Affiliation(s)
- Xiaolong Liu
- Key Laboratory of Molecular Nanostructure and Nanotechnology, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences Beijing 100190 China
- University of Chinese Academy of Sciences Beijing 100049 P. R. China
| | - Yifei Jiang
- Institute of Basic Medicine and Cancer, Chinese Academy of Sciences Hangzhou 310022 Zhejiang China
| | - Yutong Cui
- Key Laboratory of Molecular Nanostructure and Nanotechnology, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences Beijing 100190 China
- University of Chinese Academy of Sciences Beijing 100049 P. R. China
| | - Jinghe Yuan
- Key Laboratory of Molecular Nanostructure and Nanotechnology, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences Beijing 100190 China
| | - Xiaohong Fang
- Key Laboratory of Molecular Nanostructure and Nanotechnology, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences Beijing 100190 China
- University of Chinese Academy of Sciences Beijing 100049 P. R. China
- Institute of Basic Medicine and Cancer, Chinese Academy of Sciences Hangzhou 310022 Zhejiang China
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46
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Maes A, Pestiaux C, Marino A, Balcaen T, Leyssens L, Vangrunderbeeck S, Pyka G, De Borggraeve WM, Bertrand L, Beauloye C, Horman S, Wevers M, Kerckhofs G. Cryogenic contrast-enhanced microCT enables nondestructive 3D quantitative histopathology of soft biological tissues. Nat Commun 2022; 13:6207. [PMID: 36266273 PMCID: PMC9584947 DOI: 10.1038/s41467-022-34048-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 10/12/2022] [Indexed: 12/24/2022] Open
Abstract
Biological tissues comprise a spatially complex structure, composition and organization at the microscale, named the microstructure. Given the close structure-function relationships in tissues, structural characterization is essential to fully understand the functioning of healthy and pathological tissues, as well as the impact of possible treatments. Here, we present a nondestructive imaging approach to perform quantitative 3D histo(patho)logy of biological tissues, termed Cryogenic Contrast-Enhanced MicroCT (cryo-CECT). By combining sample staining, using an X-ray contrast-enhancing staining agent, with freezing the sample at the optimal freezing rate, cryo-CECT enables 3D visualization and structural analysis of individual tissue constituents, such as muscle and collagen fibers. We applied cryo-CECT on murine hearts subjected to pressure overload following transverse aortic constriction surgery. Cryo-CECT allowed to analyze, in an unprecedented manner, the orientation and diameter of the individual muscle fibers in the entire heart, as well as the 3D localization of fibrotic regions within the myocardial layers. We foresee further applications of cryo-CECT in the optimization of tissue/food preservation and donor banking, showing that cryo-CECT also has clinical and industrial potential.
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Affiliation(s)
- Arne Maes
- grid.5596.f0000 0001 0668 7884Department of Materials Engineering, KU Leuven, Heverlee, Belgium ,grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Camille Pestiaux
- grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Alice Marino
- grid.7942.80000 0001 2294 713XPole of Cardiovascular Research, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Tim Balcaen
- grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium ,grid.5596.f0000 0001 0668 7884Molecular Design and Synthesis, Department of Chemistry, KU Leuven, Leuven, Belgium
| | - Lisa Leyssens
- grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Sarah Vangrunderbeeck
- grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium ,grid.5596.f0000 0001 0668 7884Molecular Design and Synthesis, Department of Chemistry, KU Leuven, Leuven, Belgium
| | - Grzegorz Pyka
- grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Wim M. De Borggraeve
- grid.5596.f0000 0001 0668 7884Molecular Design and Synthesis, Department of Chemistry, KU Leuven, Leuven, Belgium
| | - Luc Bertrand
- grid.7942.80000 0001 2294 713XPole of Cardiovascular Research, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Christophe Beauloye
- grid.48769.340000 0004 0461 6320Division of Cardiology, University Hospital Saint-Luc, Brussels, Belgium
| | - Sandrine Horman
- grid.7942.80000 0001 2294 713XPole of Cardiovascular Research, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium
| | - Martine Wevers
- grid.5596.f0000 0001 0668 7884Department of Materials Engineering, KU Leuven, Heverlee, Belgium
| | - Greet Kerckhofs
- grid.5596.f0000 0001 0668 7884Department of Materials Engineering, KU Leuven, Heverlee, Belgium ,grid.7942.80000 0001 2294 713XBiomechanics lab, Institute of Mechanics, Materials and Civil Engineering, UCLouvain, Louvain-la-Neuve, Belgium ,grid.7942.80000 0001 2294 713XPole of Morphology, Institute of Experimental and Clinical Research, UCLouvain, Brussels, Belgium ,grid.5596.f0000 0001 0668 7884Prometheus, Division for Skeletal Tissue Engineering, KU Leuven, Leuven, Belgium
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47
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Obesity-Related Neuroinflammation: Magnetic Resonance and Microscopy Imaging of the Brain. Int J Mol Sci 2022; 23:ijms23158790. [PMID: 35955925 PMCID: PMC9368789 DOI: 10.3390/ijms23158790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Revised: 08/03/2022] [Accepted: 08/06/2022] [Indexed: 12/01/2022] Open
Abstract
Obesity is a major risk factor of Alzheimer’s disease and related dementias. The principal feature of dementia is a loss of neurons and brain atrophy. The mechanistic links between obesity and the neurodegenerative processes of dementias are not fully understood, but recent research suggests that obesity-related systemic inflammation and subsequent neuroinflammation may be involved. Adipose tissues release multiple proinflammatory molecules (fatty acids and cytokines) that impact blood and vessel cells, inducing low-grade systemic inflammation that can transition to tissues, including the brain. Inflammation in the brain—neuroinflammation—is one of key elements of the pathobiology of neurodegenerative disorders; it is characterized by the activation of microglia, the resident immune cells in the brain, and by the structural and functional changes of other cells forming the brain parenchyma, including neurons. Such cellular changes have been shown in animal models with direct methods, such as confocal microscopy. In humans, cellular changes are less tangible, as only indirect methods such as magnetic resonance (MR) imaging are usually used. In these studies, obesity and low-grade systemic inflammation have been associated with lower volumes of the cerebral gray matter, cortex, and hippocampus, as well as altered tissue MR properties (suggesting microstructural variations in cellular and molecular composition). How these structural variations in the human brain observed using MR imaging relate to the cellular variations in the animal brain seen with microscopy is not well understood. This review describes the current understanding of neuroinflammation in the context of obesity-induced systemic inflammation, and it highlights need for the bridge between animal microscopy and human MR imaging studies.
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48
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Kim K. Single-Shot Light-Field Microscopy: An Emerging Tool for 3D Biomedical Imaging. BIOCHIP JOURNAL 2022. [DOI: 10.1007/s13206-022-00077-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Abstract3D microscopy is a useful tool to visualize the detailed structures and mechanisms of biomedical specimens. In particular, biophysical phenomena such as neural activity require fast 3D volumetric imaging because fluorescence signals degrade quickly. A light-field microscope (LFM) has recently attracted attention as a high-speed volumetric imaging technique by recording 3D information in a single-snapshot. This review highlighted recent progress in LFM techniques for 3D biomedical applications. In detail, various image reconstruction algorithms according to LFM configurations are explained, and several biomedical applications such as neuron activity localization, live-cell imaging, locomotion analysis, and single-molecule visualization are introduced. We also discuss deep learning-based LFMs to enhance image resolution and reduce reconstruction artifacts.
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Seo Y, Bang S, Son J, Kim D, Jeong Y, Kim P, Yang J, Eom JH, Choi N, Kim HN. Brain physiome: A concept bridging in vitro 3D brain models and in silico models for predicting drug toxicity in the brain. Bioact Mater 2022; 13:135-148. [PMID: 35224297 PMCID: PMC8843968 DOI: 10.1016/j.bioactmat.2021.11.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 11/01/2021] [Accepted: 11/06/2021] [Indexed: 12/12/2022] Open
Abstract
In the last few decades, adverse reactions to pharmaceuticals have been evaluated using 2D in vitro models and animal models. However, with increasing computational power, and as the key drivers of cellular behavior have been identified, in silico models have emerged. These models are time-efficient and cost-effective, but the prediction of adverse reactions to unknown drugs using these models requires relevant experimental input. Accordingly, the physiome concept has emerged to bridge experimental datasets with in silico models. The brain physiome describes the systemic interactions of its components, which are organized into a multilevel hierarchy. Because of the limitations in obtaining experimental data corresponding to each physiome component from 2D in vitro models and animal models, 3D in vitro brain models, including brain organoids and brain-on-a-chip, have been developed. In this review, we present the concept of the brain physiome and its hierarchical organization, including cell- and tissue-level organizations. We also summarize recently developed 3D in vitro brain models and link them with the elements of the brain physiome as a guideline for dataset collection. The connection between in vitro 3D brain models and in silico modeling will lead to the establishment of cost-effective and time-efficient in silico models for the prediction of the safety of unknown drugs.
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Affiliation(s)
- Yoojin Seo
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Seokyoung Bang
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
| | - Jeongtae Son
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Dongsup Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Yong Jeong
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Pilnam Kim
- Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, 34141, Republic of Korea
| | - Jihun Yang
- Next&Bio Inc., Seoul, 02841, Republic of Korea
| | - Joon-Ho Eom
- Medical Device Research Division, National Institute of Food and Drug Safety Evaluation, Cheongju, 28159, Republic of Korea
| | - Nakwon Choi
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
- Division of Bio-Medical Science & Technology, KIST School, Korea University of Science and Technology (UST), Seoul, 02792, Republic of Korea
- KU-KIST Graduate School of Converging Science and Technology, Korea University, Seoul, 02841, Republic of Korea
| | - Hong Nam Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, Republic of Korea
- Division of Bio-Medical Science & Technology, KIST School, Korea University of Science and Technology (UST), Seoul, 02792, Republic of Korea
- School of Mechanical Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, 03722, Republic of Korea
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50
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Wu Z, Lin D, Li Y. Pushing the frontiers: tools for monitoring neurotransmitters and neuromodulators. Nat Rev Neurosci 2022; 23:257-274. [PMID: 35361961 PMCID: PMC11163306 DOI: 10.1038/s41583-022-00577-6] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2022] [Indexed: 12/26/2022]
Abstract
Neurotransmitters and neuromodulators have a wide range of key roles throughout the nervous system. However, their dynamics in both health and disease have been challenging to assess, owing to the lack of in vivo tools to track them with high spatiotemporal resolution. Thus, developing a platform that enables minimally invasive, large-scale and long-term monitoring of neurotransmitters and neuromodulators with high sensitivity, high molecular specificity and high spatiotemporal resolution has been essential. Here, we review the methods available for monitoring the dynamics of neurotransmitters and neuromodulators. Following a brief summary of non-genetically encoded methods, we focus on recent developments in genetically encoded fluorescent indicators, highlighting how these novel indicators have facilitated advances in our understanding of the functional roles of neurotransmitters and neuromodulators in the nervous system. These studies present a promising outlook for the future development and use of tools to monitor neurotransmitters and neuromodulators.
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Affiliation(s)
- Zhaofa Wu
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
| | - Dayu Lin
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China.
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China.
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- Chinese Institute for Brain Research, Beijing, China.
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, China.
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