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      Structural analysis of melanosomes in living mammalian cells using scanning electron-assisted dielectric microscopy with deep neural network

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          Abstract

          Melanins are the main pigments found in mammals. Their synthesis and transfer to keratinocytes have been widely investigated for many years. However, analysis has been mainly carried out using fixed rather than live cells. In this study, we have analysed the melanosomes in living mammalian cells using newly developed scanning electron-assisted dielectric microscopy (SE-ADM). The melanosomes in human melanoma MNT-1 cells were observed as clear black particles in SE-ADM. The main structure of melanosomes was toroidal while that of normal melanocytes was ellipsoidal. In tyrosinase knockout MNT-1 cells, not only the black particles in the SE-ADM images but also the Raman shift of melanin peaks completely disappeared suggesting that the black particles were really melanosomes. We developed a deep neural network (DNN) system to automatically detect melanosomes in cells and analysed their diameter and roundness. In terms of melanosome morphology, the diameter of melanosomes in melanoma cells did not change while that in normal melanocytes increased during culture. The established DNN analysis system with SE-ADM can be used for other particles, e.g. exosomes, lysosomes, and other biological particles.

          Graphical Abstract

          Highlights

          • Direct observation of melanosomes in living cells by SE-ADM.

          • Melanosomes of MNT-1 cells have a toroidal structure.

          • Shape of melanosomes differs depending on cell type.

          • DNN enables highly accurate detection of melanosomes in SE-ADM images.

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          Deep learning.

          Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
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            ImageNet classification with deep convolutional neural networks

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              Going deeper with convolutions

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                Author and article information

                Contributors
                Journal
                Comput Struct Biotechnol J
                Comput Struct Biotechnol J
                Computational and Structural Biotechnology Journal
                Research Network of Computational and Structural Biotechnology
                2001-0370
                18 December 2022
                2023
                18 December 2022
                : 21
                : 506-518
                Affiliations
                [a ]Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Central 6, Higashi, Tsukuba, Ibaraki 305-8566, Japan
                [b ]Department of Periodontology, Osaka University Graduate School of Dentistry, 1-8 Yamada-oka, Suita, Osaka 565-0871, Japan
                [c ]Chemical Business Unit, Nikko Chemicals Co., Ltd., Itabashi-ku, Tokyo 174-0046, Japan
                Author notes
                [* ]Correspondence to: Health and Medical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Higashi 1-1-1, Tsukuba, Ibaraki 305-8566, Japan. t-ogura@ 123456aist.go.jp
                Article
                S2001-0370(22)00584-0
                10.1016/j.csbj.2022.12.027
                9807747
                36618988
                e85d30de-57a9-4bf2-abf8-f65cc3372c96
                © 2022 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 2 September 2022
                : 16 December 2022
                : 16 December 2022
                Categories
                Research Article

                scanning electron-assisted dielectric microscopy,raman microscopy,melanosome,melanocyte,mnt-1 cell,deep neural network

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