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Goswami N, Anastasio MA, Popescu G. Quantitative phase imaging techniques for measuring scattering properties of cells and tissues: a review-part I. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:S22713. [PMID: 39026612 PMCID: PMC11257415 DOI: 10.1117/1.jbo.29.s2.s22713] [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: 02/29/2024] [Revised: 04/30/2024] [Accepted: 05/20/2024] [Indexed: 07/20/2024]
Abstract
Significance Quantitative phase imaging (QPI) techniques offer intrinsic information about the sample of interest in a label-free, noninvasive manner and have an enormous potential for wide biomedical applications with negligible perturbations to the natural state of the sample in vitro. Aim We aim to present an in-depth review of the scattering formulation of light-matter interactions as applied to biological samples such as cells and tissues, discuss the relevant quantitative phase measurement techniques, and present a summary of various reported applications. Approach We start with scattering theory and scattering properties of biological samples followed by an exploration of various microscopy configurations for 2D QPI for measurement of structure and dynamics. Results We reviewed 157 publications and presented a range of QPI techniques and discussed suitable applications for each. We also presented the theoretical frameworks for phase reconstruction associated with the discussed techniques and highlighted their domains of validity. Conclusions We provide detailed theoretical as well as system-level information for a wide range of QPI techniques. Our study can serve as a guideline for new researchers looking for an exhaustive literature review of QPI methods and relevant applications.
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Affiliation(s)
- Neha Goswami
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
| | - Mark A. Anastasio
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
- University of Illinois Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
| | - Gabriel Popescu
- University of Illinois Urbana-Champaign, Department of Bioengineering, Urbana, Illinois, United States
- University of Illinois Urbana-Champaign, Department of Electrical and Computer Engineering, Urbana, Illinois, United States
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Lee AJ, Yoon D, Han S, Hugonnet H, Park W, Park JK, Nam Y, Park Y. Label-free monitoring of 3D cortical neuronal growth in vitro using optical diffraction tomography. BIOMEDICAL OPTICS EXPRESS 2021; 12:6928-6939. [PMID: 34858689 PMCID: PMC8606138 DOI: 10.1364/boe.439404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 09/17/2021] [Accepted: 09/18/2021] [Indexed: 05/10/2023]
Abstract
The highly complex central nervous systems of mammals are often studied using three-dimensional (3D) in vitro primary neuronal cultures. A coupled confocal microscopy and immunofluorescence labeling are widely utilized for visualizing the 3D structures of neurons. However, this requires fixation of the neurons and is not suitable for monitoring an identical sample at multiple time points. Thus, we propose a label-free monitoring method for 3D neuronal growth based on refractive index tomograms obtained by optical diffraction tomography. The 3D morphology of the neurons was clearly visualized, and the developmental processes of neurite outgrowth in 3D spaces were analyzed for individual neurons.
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Affiliation(s)
- Ariel J Lee
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Current Affiliation: Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Contributed equally
| | - DongJo Yoon
- Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea
- Contributed equally
| | - SeungYun Han
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Current Affiliation: Department of Applied Physics, Yale University, New Haven, CT 06520, USA
- Contributed equally
| | - Herve Hugonnet
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - WeiSun Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
| | - Je-Kyun Park
- Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - YoonKey Nam
- Department of Bio and Brain Engineering, KAIST, Daejeon 34141, Republic of Korea
| | - YongKeun Park
- Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Republic of Korea
- KAIST Institute for Health Science and Technology, KAIST, Daejeon 34141, Republic of Korea
- Tomocube Inc., Daejeon, Republic of Korea
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Gryshkov O, AL Halabi F, Kuhn AI, Leal-Marin S, Freund LJ, Förthmann M, Meier N, Barker SA, Haastert-Talini K, Glasmacher B. PVDF and P(VDF-TrFE) Electrospun Scaffolds for Nerve Graft Engineering: A Comparative Study on Piezoelectric and Structural Properties, and In Vitro Biocompatibility. Int J Mol Sci 2021; 22:11373. [PMID: 34768804 PMCID: PMC8583857 DOI: 10.3390/ijms222111373] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/14/2021] [Accepted: 10/16/2021] [Indexed: 12/19/2022] Open
Abstract
Polyvinylidene fluoride (PVDF) and its copolymer with trifluoroethylene (P(VDF-TrFE)) are considered as promising biomaterials for supporting nerve regeneration because of their proven biocompatibility and piezoelectric properties that could stimulate cell ingrowth due to their electrical activity upon mechanical deformation. For the first time, this study reports on the comparative analysis of PVDF and P(VDF-TrFE) electrospun scaffolds in terms of structural and piezoelectric properties as well as their in vitro performance. A dynamic impact test machine was developed, validated, and utilised, to evaluate the generation of an electrical voltage upon the application of an impact load (varying load magnitude and frequency) onto the electrospun PVDF (15-20 wt%) and P(VDF-TrFE) (10-20 wt%) scaffolds. The cytotoxicity and in vitro performance of the scaffolds was evaluated with neonatal rat (nrSCs) and adult human Schwann cells (ahSCs). The neurite outgrowth behaviour from sensory rat dorsal root ganglion neurons cultured on the scaffolds was analysed qualitatively. The results showed (i) a significant increase of the β-phase content in the PVDF after electrospinning as well as a zeta potential similar to P(VDF-TrFE), (ii) a non-constant behaviour of the longitudinal piezoelectric strain constant d33, depending on the load and the load frequency, and (iii) biocompatibility with cultured Schwann cells and guiding properties for sensory neurite outgrowth. In summary, the electrospun PVDF-based scaffolds, representing piezoelectric activity, can be considered as promising materials for the development of artificial nerve conduits for the peripheral nerve injury repair.
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Affiliation(s)
- Oleksandr Gryshkov
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
- Lower Saxony Centre for Biomedical Engineering, Implant Research and Development, Stadtfelddamm 34, 30625 Hannover, Germany
| | - Fedaa AL Halabi
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
| | - Antonia Isabel Kuhn
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
| | - Sara Leal-Marin
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
- Lower Saxony Centre for Biomedical Engineering, Implant Research and Development, Stadtfelddamm 34, 30625 Hannover, Germany
| | - Lena Julie Freund
- Institute of Neuroanatomy and Cell Biology, Hannover Medical School, Centre for Systems Neuroscience (ZSN) Hannover, 30559 Hannover, Germany; (L.J.F.); (M.F.); (K.H.-T.)
| | - Maria Förthmann
- Institute of Neuroanatomy and Cell Biology, Hannover Medical School, Centre for Systems Neuroscience (ZSN) Hannover, 30559 Hannover, Germany; (L.J.F.); (M.F.); (K.H.-T.)
| | - Nils Meier
- Institute for Technical Chemistry, Braunschweig University of Technology, Hagenring 30, 38106 Braunschweig, Germany;
| | - Sven-Alexander Barker
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
- Lower Saxony Centre for Biomedical Engineering, Implant Research and Development, Stadtfelddamm 34, 30625 Hannover, Germany
| | - Kirsten Haastert-Talini
- Institute of Neuroanatomy and Cell Biology, Hannover Medical School, Centre for Systems Neuroscience (ZSN) Hannover, 30559 Hannover, Germany; (L.J.F.); (M.F.); (K.H.-T.)
| | - Birgit Glasmacher
- Institute for Multiphase Processes, Leibniz University Hannover, An der Universität 1, Building 8143, 30823 Garbsen, Germany; (A.I.K.); (S.L.-M.); (S.-A.B.); (B.G.)
- Lower Saxony Centre for Biomedical Engineering, Implant Research and Development, Stadtfelddamm 34, 30625 Hannover, Germany
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Monitoring reactivation of latent HIV by label-free gradient light interference microscopy. iScience 2021; 24:102940. [PMID: 34430819 PMCID: PMC8367845 DOI: 10.1016/j.isci.2021.102940] [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: 01/12/2021] [Revised: 05/24/2021] [Accepted: 07/30/2021] [Indexed: 11/23/2022] Open
Abstract
Human immunodeficiency virus (HIV) can infect cells and take a quiescent and nonexpressive state called latency. In this study, we report insights provided by label-free, gradient light interference microscopy (GLIM) about the changes in dry mass, diameter, and dry mass density associated with infected cells that occur upon reactivation. We discovered that the mean cell dry mass and mean diameter of latently infected cells treated with reactivating drug, TNF-α, are higher for latent cells that reactivate than those of the cells that did not reactivate. Cells with mean dry mass and diameter less than approximately 10 pg and 8 μm, respectively, remain exclusively in the latent state. Also, cells with mean dry mass greater than approximately 28-30 pg and mean diameter greater than 11–12 μm have a higher probability of reactivating. This study is significant as it presents a new label-free approach to quantify latent reactivation of a virus in single cells. GLIM imaging reveals differences between latent and reactivated HIV in JLat cells Cells with reactivated HIV have higher dry mass and diameter
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Chen X, Kandel ME, Popescu G. Spatial light interference microscopy: principle and applications to biomedicine. ADVANCES IN OPTICS AND PHOTONICS 2021; 13:353-425. [PMID: 35494404 PMCID: PMC9048520 DOI: 10.1364/aop.417837] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, and full-field methods. Then, we outline SLIM imaging from theory and instrumentation to diffraction tomography. Zernike's phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next, we discuss the requirements for operation, with a focus on software developed in-house for SLIM that enables high-throughput acquisition, whole slide scanning, mosaic tile registration, and imaging with a color camera. We introduce two methods for solving the inverse problem using SLIM, white-light tomography, and Wolf phase tomography. Lastly, we review the applications of SLIM in basic science and clinical studies. SLIM can study cell dynamics, cell growth and proliferation, cell migration, mass transport, etc. In clinical settings, SLIM can assist with cancer studies, reproductive technology, blood testing, etc. Finally, we review an emerging trend, where SLIM imaging in conjunction with artificial intelligence brings computational specificity and, in turn, offers new solutions to outstanding challenges in cell biology and pathology.
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Jiao Y, He YR, Kandel ME, Liu X, Lu W, Popescu G. Computational interference microscopy enabled by deep learning. APL PHOTONICS 2021; 6:046103. [PMID: 35308602 PMCID: PMC8931864 DOI: 10.1063/5.0041901] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Quantitative phase imaging (QPI) has been widely applied in characterizing cells and tissues. Spatial light interference microscopy (SLIM) is a highly sensitive QPI method due to its partially coherent illumination and common path interferometry geometry. However, SLIM's acquisition rate is limited because of the four-frame phase-shifting scheme. On the other hand, off-axis methods such as diffraction phase microscopy (DPM) allow for single-shot QPI. However, the laser-based DPM system is plagued by spatial noise due to speckles and multiple reflections. In a parallel development, deep learning was proven valuable in the field of bioimaging, especially due to its ability to translate one form of contrast into another. Here, we propose using deep learning to produce synthetic, SLIM-quality, and high-sensitivity phase maps from DPM using single-shot images as the input. We used an inverted microscope with its two ports connected to the DPM and SLIM modules such that we have access to the two types of images on the same field of view. We constructed a deep learning model based on U-net and trained on over 1000 pairs of DPM and SLIM images. The model learned to remove the speckles in laser DPM and overcame the background phase noise in both the test set and new data. The average peak signal-to-noise ratio, Pearson correlation coefficient, and structural similarity index measure were 29.97, 0.79, and 0.82 for the test dataset. Furthermore, we implemented the neural network inference into the live acquisition software, which now allows a DPM user to observe in real-time an extremely low-noise phase image. We demonstrated this principle of computational interference microscopy imaging using blood smears, as they contain both erythrocytes and leukocytes, under static and dynamic conditions.
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Affiliation(s)
- Yuheng Jiao
- Quantitative Light Imaging Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yuchen R. He
- Quantitative Light Imaging Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Mikhail E. Kandel
- Quantitative Light Imaging Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Xiaojun Liu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wenlong Lu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Gabriel Popescu
- Quantitative Light Imaging Laboratory, Department of Electrical and Computer Engineering, Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Author to whom correspondence should be addressed:
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Pradeep S, Tasnim T, Zhang H, Zangle TA. Simultaneous measurement of neurite and neural body mass accumulation via quantitative phase imaging. Analyst 2021; 146:1361-1368. [PMID: 33393564 DOI: 10.1039/d0an01961e] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Measurement of neuron behavior is crucial for studying neural development and evaluating the impact of potential therapies on neural regeneration. Conventional approaches to imaging neuronal behavior require labeling and do not separately quantify the growth processes that underlie neural regeneration. In this paper we demonstrate the use of quantitative phase imaging (QPI) as a label-free, quantitative measurement of neuron behavior in vitro. By combining QPI with image processing, our method separately measures the mass accumulation rates of soma and neurites. Additionally, the data provided by QPI can be used to separately measure the processes of maturation and formation of neurites. Overall, our approach has the potential to greatly simplify conventional neurite outgrowth measurements, while providing key data on the resources used to produce neurites during neural development.
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Affiliation(s)
- Soorya Pradeep
- Department of Chemical Engineering, University of Utah, USA
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Kandel ME, He YR, Lee YJ, Chen THY, Sullivan KM, Aydin O, Saif MTA, Kong H, Sobh N, Popescu G. Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments. Nat Commun 2020; 11:6256. [PMID: 33288761 PMCID: PMC7721808 DOI: 10.1038/s41467-020-20062-x] [Citation(s) in RCA: 73] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 10/28/2020] [Indexed: 12/28/2022] Open
Abstract
Due to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy's utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.
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Affiliation(s)
- Mikhail E Kandel
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Yuchen R He
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Young Jae Lee
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Taylor Hsuan-Yu Chen
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | | | - Onur Aydin
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - M Taher A Saif
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Hyunjoon Kong
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Nahil Sobh
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
| | - Gabriel Popescu
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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Qin EC, Kandel ME, Liamas E, Shah TB, Kim C, Kaufman CD, Zhang ZJ, Popescu G, Gillette MU, Leckband DE, Kong H. Graphene oxide substrates with N-cadherin stimulates neuronal growth and intracellular transport. Acta Biomater 2019; 90:412-423. [PMID: 30951897 DOI: 10.1016/j.actbio.2019.04.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 03/12/2019] [Accepted: 04/01/2019] [Indexed: 12/23/2022]
Abstract
Intracellular transport is fundamental for neuronal function and development and is dependent on the formation of stable actin filaments. N-cadherin, a cell-cell adhesion protein, is actively involved in neuronal growth and actin cytoskeleton organization. Various groups have explored how neurons behaved on substrates engineered to present N-cadherin; however, few efforts have been made to examine how these surfaces modulate neuronal intracellular transport. To address this issue, we assembled a substrate to which recombinant N-cadherin molecules are physiosorbed using graphene oxide (GO) or reduced graphene oxide (rGO). N-cadherin physisorbed on GO and rGO led to a substantial enhancement of intracellular mass transport along neurites relative to N-cadherin on glass, due to increased neuronal adhesion, neurite extensions, dendritic arborization and glial cell adhesion. This study will be broadly useful for recreating active neural tissues in vitro and for improving our understanding of the development, homeostasis, and physiology of neurons. STATEMENT OF SIGNIFICANCE: Intracellular transport of proteins and chemical cues is extremely important for culturing neurons in vitro, as they replenish materials within and facilitate communication between neurons. Various studies have shown that intracellular transport is dependent on the formation of stable actin filaments. However, the extent to which cadherin-mediated cell-cell adhesion modulates intracellular transport is not heavily explored. In this study, N-cadherin was adsorbed onto graphene oxide-based substrates to understand the role of cadherin at a molecular level and the intracellular transport within cells was examined using spatial light interference microscopy. As such, the results of this study will serve to better understand and harness the role of cell-cell adhesion in neuron development and regeneration.
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Huang C, Gu Y, Chen J, Bahrani AA, Abu Jawdeh EG, Bada HS, Saatman K, Yu G, Chen L. A Wearable Fiberless Optical Sensor for Continuous Monitoring of Cerebral Blood Flow in Mice. IEEE JOURNAL OF SELECTED TOPICS IN QUANTUM ELECTRONICS : A PUBLICATION OF THE IEEE LASERS AND ELECTRO-OPTICS SOCIETY 2019; 25:1-9. [PMID: 31666792 DOI: 10.1109/jstqe.2018.2869613] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Continuous and longitudinal monitoring of cerebral blood flow (CBF) in animal models provides information for studying the mechanisms and interventions of various cerebral diseases. Since anesthesia may affect brain hemodynamics, researchers have been seeking wearable devices for use in conscious animals. We present a wearable diffuse speckle contrast flowmeter (DSCF) probe for monitoring CBF variations in mice. The DSCF probe consists of a small low-power near-infrared laser diode as a point source and an ultra-small low-power CMOS camera as a 2D detector array, which can be affixed on a mouse head. The movement of red blood cells in brain cortex (i.e., CBF) produces spatial fluctuations of laser speckles, which are captured by the camera. The DSCF system was calibrated using tissue phantoms and validated in a human forearm and mouse brains for continuous monitoring of blood flow increases and decreases against the established technologies. Significant correlations were observed among these measurements (R2 ≥ 0.80, p < 10-5). This small fiberless probe has the potential to be worn by a freely moving conscious mouse. Moreover, the flexible source-detector configuration allows for varied probing depths up to ~8 mm, which is sufficient for transcranially detecting CBF in the cortices of rodents and newborn infants.
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Affiliation(s)
- Chong Huang
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506 USA
| | - Yutong Gu
- Department of Electrical Engineering, University of Southern California, Los Angeles, CA, 90089 USA
| | - Jing Chen
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506 USA
| | - Ahmed A Bahrani
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506 USA
| | - Elie G Abu Jawdeh
- Department of Pediatrics, College of Medicine, University of Kentucky, Lexington, KY 40536 USA
| | - Henrietta S Bada
- Department of Pediatrics, College of Medicine, University of Kentucky, Lexington, KY 40536 USA
| | - Kathryn Saatman
- Department of Physiology, Spinal Cord and Brain Injury Research Center, University of Kentucky, Lexington, KY 40536 USA
| | - Guoqiang Yu
- Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506 USA
| | - Lei Chen
- Department of Physiology, Spinal Cord and Brain Injury Research Center, University of Kentucky, Lexington, KY 40536 USA
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