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      Primary Human Osteoblasts Cultured in a 3D Microenvironment Create a Unique Representative Model of Their Differentiation Into Osteocytes

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          Abstract

          Microengineered systems provide an in vitro strategy to explore the variability of individual patient response to tissue engineering products, since they prefer the use of primary cell sources representing the phenotype variability. Traditional in vitro systems already showed that primary human osteoblasts embedded in a 3D fibrous collagen matrix differentiate into osteocytes under specific conditions. Here, we hypothesized that translating this environment to the organ-on-a-chip scale creates a minimal functional unit to recapitulate osteoblast maturation toward osteocytes and matrix mineralization. Primary human osteoblasts were seeded in a type I collagen hydrogel, to establish the role of lower (2.5 × 10 5 cells/ml) and higher (1 × 10 6 cells/ml) cell density on their differentiation into osteocytes. A custom semi-automatic image analysis software was used to extract quantitative data on cellular morphology from brightfield images. The results are showing that cells cultured at a high density increase dendrite length over time, stop proliferating, exhibit dendritic morphology, upregulate alkaline phosphatase (ALP) activity, and express the osteocyte marker dental matrix protein 1 (DMP1). On the contrary, cells cultured at lower density proliferate over time, do not upregulate ALP and express the osteoblast marker bone sialoprotein 2 (BSP2) at all timepoints. Our work reveals that microengineered systems create unique conditions to capture the major aspects of osteoblast differentiation into osteocytes with a limited number of cells. We propose that the microengineered approach is a functional strategy to create a patient-specific bone tissue model and investigate the individual osteogenic potential of the patient bone cells.

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          Most cited references39

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          Metadata matters: access to image data in the real world

          Data sharing is important in the biological sciences to prevent duplication of effort, to promote scientific integrity, and to facilitate and disseminate scientific discovery. Sharing requires centralized repositories, and submission to and utility of these resources require common data formats. This is particularly challenging for multidimensional microscopy image data, which are acquired from a variety of platforms with a myriad of proprietary file formats (PFFs). In this paper, we describe an open standard format that we have developed for microscopy image data. We call on the community to use open image data standards and to insist that all imaging platforms support these file formats. This will build the foundation for an open image data repository.
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            Microfluidic assay for simultaneous culture of multiple cell types on surfaces or within hydrogels.

            This protocol describes a simple but robust microfluidic assay combining three-dimensional (3D) and two-dimensional (2D) cell culture. The microfluidic platform comprises hydrogel-incorporating chambers between surface-accessible microchannels. By using this platform, well-defined biochemical and biophysical stimuli can be applied to multiple cell types interacting over distances of <1 mm, thereby replicating many aspects of the in vivo microenvironment. Capabilities exist for time-dependent manipulation of flow and concentration gradients as well as high-resolution real-time imaging for observing spatial-temporal single-cell behavior, cell-cell communication, cell-matrix interactions and cell population dynamics. These heterotypic cell type assays can be used to study cell survival, proliferation, migration, morphogenesis and differentiation under controlled conditions. Applications include the study of previously unexplored cellular interactions, and they have already provided new insights into how biochemical and biophysical factors regulate interactions between populations of different cell types. It takes 3 d to fabricate the system and experiments can run for up to several weeks.
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              Biological imaging software tools.

              Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost all these advances have required the development of software to enable the acquisition, management, analysis and visualization of the imaging data. We review each computational step that biologists encounter when dealing with digital images, the inherent challenges and the overall status of available software for bioimage informatics, focusing on open-source options.
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                Author and article information

                Contributors
                Journal
                Front Bioeng Biotechnol
                Front Bioeng Biotechnol
                Front. Bioeng. Biotechnol.
                Frontiers in Bioengineering and Biotechnology
                Frontiers Media S.A.
                2296-4185
                24 April 2020
                2020
                : 8
                : 336
                Affiliations
                [1] 1Multiscale in Mechanical and Biological Engineering (M2BE), University of Zaragoza , Zaragoza, Spain
                [2] 2Biomechanics Section, Department of Mechanical Engineering, KU Leuven , Leuven, Belgium
                [3] 3Mechanobiology and Medical Device Research Group (MMDRG), National University of Ireland Galway , Galway, Ireland
                Author notes

                Edited by: Maria Chatzinikolaidou, University of Crete, Greece

                Reviewed by: Anne Bernhardt, Dresden University of Technology, Germany; Lorenzo Fassina, University of Pavia, Italy

                *Correspondence: José Manuel García-Aznar jmgaraz@ 123456unizar.es

                This article was submitted to Tissue Engineering and Regenerative Medicine, a section of the journal Frontiers in Bioengineering and Biotechnology

                Article
                10.3389/fbioe.2020.00336
                7193048
                32391343
                a9d88b9a-02f5-4e17-8a07-6ada76c6eebd
                Copyright © 2020 Nasello, Alamán-Díez, Schiavi, Pérez, McNamara and García-Aznar.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 06 December 2019
                : 26 March 2020
                Page count
                Figures: 8, Tables: 0, Equations: 0, References: 64, Pages: 14, Words: 9210
                Funding
                Funded by: Horizon 2020 Framework Programme 10.13039/100010661
                Funded by: Ministerio de Ciencia, Tecnología 10.13039/501100006280
                Funded by: Science Foundation Ireland 10.13039/501100001602
                Categories
                Bioengineering and Biotechnology
                Original Research

                bone-on-a-chip,osteoblast differentiation,microfluidics,osteocyte,primary human cells,dendrite formation,in vitro bone model

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