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      High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells

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          Abstract

          Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, time-resolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.

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          Most cited references32

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          Continuous inertial focusing, ordering, and separation of particles in microchannels.

          Under laminar flow conditions, when no external forces are applied, particles are generally thought to follow fluid streamlines. Contrary to this perspective, we observe that flowing particles migrate across streamlines in a continuous, predictable, and accurate manner in microchannels experiencing laminar flows. The migration is attributed to lift forces on particles that are observed when inertial aspects of the flow become significant. We identified symmetric and asymmetric channel geometries that provide additional inertial forces that bias particular equilibrium positions to create continuous streams of ordered particles precisely positioned in three spatial dimensions. We were able to order particles laterally, within the transverse plane of the channel, with >80-nm accuracy, and longitudinally, in regular chains along the direction of flow. A fourth dimension of rotational alignment was observed for discoidal red blood cells. Unexpectedly, ordering appears to be independent of particle buoyant direction, suggesting only minor centrifugal contributions. Theoretical analysis indicates the physical principles are operational over a range of channel and particle length scales. The ability to differentially order particles of different sizes, continuously, at high rates, and without external forces in microchannels is expected to have a broad range of applications in continuous bioparticle separation, high-throughput cytometry, and large-scale filtration systems.
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            Inertial microfluidic physics.

            Microfluidics has experienced massive growth in the past two decades, and especially with advances in rapid prototyping researchers have explored a multitude of channel structures, fluid and particle mixtures, and integration with electrical and optical systems towards solving problems in healthcare, biological and chemical analysis, materials synthesis, and other emerging areas that can benefit from the scale, automation, or the unique physics of these systems. Inertial microfluidics, which relies on the unconventional use of fluid inertia in microfluidic platforms, is one of the emerging fields that make use of unique physical phenomena that are accessible in microscale patterned channels. Channel shapes that focus, concentrate, order, separate, transfer, and mix particles and fluids have been demonstrated, however physical underpinnings guiding these channel designs have been limited and much of the development has been based on experimentally-derived intuition. Here we aim to provide a deeper understanding of mechanisms and underlying physics in these systems which can lead to more effective and reliable designs with less iteration. To place the inertial effects into context we also discuss related fluid-induced forces present in particulate flows including forces due to non-Newtonian fluids, particle asymmetry, and particle deformability. We then highlight the inverse situation and describe the effect of the suspended particles acting on the fluid in a channel flow. Finally, we discuss the importance of structured channels, i.e. channels with boundary conditions that vary in the streamwise direction, and their potential as a means to achieve unprecedented three-dimensional control over fluid and particles in microchannels. Ultimately, we hope that an improved fundamental and quantitative understanding of inertial fluid dynamic effects can lead to unprecedented capabilities to program fluid and particle flow towards automation of biomedicine, materials synthesis, and chemical process control.
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              Gleason grading and prognostic factors in carcinoma of the prostate.

              Gleason grade of adenocarcinoma of the prostate is an established prognostic indicator that has stood the test of time. The Gleason grading method was devised in the 1960s and 1970s by Dr Donald F Gleason and members of the Veterans Administration Cooperative Urological Research Group. This grading system is based entirely on the histologic pattern of arrangement of carcinoma cells in H&E-stained sections. Five basic grade patterns are used to generate a histologic score, which can range from 2 to 10. These patterns are illustrated in a standard drawing that can be employed as a guide for recognition of the specific Gleason grades. Increasing Gleason grade is directly related to a number of histopathologic end points, including tumor size, margin status, and pathologic stage. Indeed, models have been developed that allow for pretreatment prediction of pathologic stage based upon needle biopsy Gleason grade, total serum prostate-specific antigen level, and clinical stage. Gleason grade has been linked to a number of clinical end points, including clinical stage, progression to metastatic disease, and survival. Gleason grade is often incorporated into nomograms used to predict response to a specific therapy, such as radiotherapy or surgery. Needle biopsy Gleason grade is routinely used to plan patient management and is also often one of the criteria for eligibility for clinical trials testing new therapies. Gleason grade should be routinely reported for adenocarcinoma of the prostate in all types of tissue samples. Experimental approaches that could be of importance in the future include determination of percentage of high-grade Gleason pattern 4 or 5, and utilization of markers discovered by gene expression profiling or by genetic testing for DNA abnormalities. Such markers would be of prognostic usefulness if they provided added value beyond the established indicators of Gleason grade, serum prostate-specific antigen, and stage. Currently, established prognostic factors for prostatic carcinoma recommended for routine reporting are TNM stage, surgical margin status, serum prostate-specific antigen, and Gleason grade.
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                Author and article information

                Contributors
                y.z.belotti@dundee.ac.uk
                david.mcgloin@uts.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 April 2019
                5 April 2019
                2019
                : 9
                : 5742
                Affiliations
                [1 ]ISNI 0000 0004 0397 2876, GRID grid.8241.f, University of Dundee, SUPA, School of Science and Engineering, ; Dundee, Scotland UK
                [2 ]ISNI 0000 0004 0397 2876, GRID grid.8241.f, University of Dundee, School of Life Sciences, ; Dundee, Scotland UK
                [3 ]ISNI 0000 0004 0397 2876, GRID grid.8241.f, University of Dundee, School of Medicine, ; Dundee, Scotland UK
                [4 ]ISNI 0000 0004 1936 7611, GRID grid.117476.2, University of Technology Sydney, School of Electrical and Data Engineering, ; Sydney, Australia
                Author information
                http://orcid.org/0000-0003-0530-2035
                http://orcid.org/0000-0002-0075-4481
                Article
                42008
                10.1038/s41598-019-42008-0
                6450875
                30952895
                d9470cf0-f4a3-406c-87a5-a312c5ad8eab
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 May 2017
                : 8 March 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000266, RCUK | Engineering and Physical Sciences Research Council (EPSRC);
                Award ID: EP/K503010/1
                Award ID: EP/K503010/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000708, Scottish Universities Physics Alliance (SUPA);
                Funded by: FundRef https://doi.org/10.13039/501100000723, Tenovus;
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