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Stem cells respond to the physicochemical parameters of the substrate on which they grow. Quantitative material activity relationships - the relationships between substrate parameters and the phenotypes they induce - have so far poorly predicted the success of bioactive implant surfaces. In this report, we screened a library of randomly selected designed surface topographies for those inducing osteogenic differentiation of bone marrow-derived mesenchymal stem cells. Cell shape features, surface design parameters, and osteogenic marker expression were strongly correlated in vitro. Furthermore, the surfaces with the highest osteogenic potential in vitro also demonstrated their osteogenic effect in vivo: these indeed strongly enhanced bone bonding in a rabbit femur model. Our work shows that by giving stem cells specific physicochemical parameters through designed surface topographies, differentiation of these cells can be dictated. (C) 2017 Elsevier Ltd. All rights reserved.

Liver disease is a leading cause of morbidity worldwide and treatment options are limited, with organ transplantation being the only form of definitive management. Cell-based therapies have long held promise as alternatives to whole-organ transplantation but have been hindered by the rapid loss of liver-specific functions over a period of days in cultured hepatocytes. Hypothesis-driven studies have identified a handful of factors that modulate hepatocyte functions in vitro, but our understanding of the mechanisms involved remains incomplete. We thus report here the development of a high-throughput platform to enable systematic interrogation of liver biology in vitro. The platform is currently configured to enable genetic knockdown screens and includes an enzyme-linked immunosorbent assay-based functional assay to quantify albumin output as a surrogate marker for hepatocyte synthetic functions as well as an image-based viability assay that counts hepatocyte nuclei. Using this platform, we identified 12 gene products that may be important for hepatocyte viability and/or liver identity in vitro. These results represent important first steps in the elucidation of mechanisms instrumental to the phenotypic maintenance of hepatocytes in vitro, and we hope that the tools reported here will empower additional studies in various fields of liver research.

Cell-based therapies hold the potential to alleviate the growing burden of liver diseases. Such therapies require human hepatocytes, which, within the stromal context of the liver, are capable of many rounds of replication. However, this ability is lost ex vivo, and human hepatocyte sourcing has limited many fields of research for decades. Here we developed a high-throughput screening platform for primary human hepatocytes to identify small molecules in two different classes that can be used to generate renewable sources of functional human hepatocytes. The first class induced functional proliferation of primary human hepatocytes in vitro. The second class enhanced hepatocyte functions and promoted the differentiation of induced pluripotent stem cell-derived hepatocytes toward a more mature phenotype than what was previously obtainable. The identification of these small molecules can help address a major challenge affecting many facets of liver research and may lead to the development of new therapeutics for liver diseases.

The typical “design” approach to image-based assay development involves choosing measurements that are likely to correlate with the phenotype of interest, based on the researcher’s intuition and knowledge of image analysis. An alternate “screening” approach is to measure a large number of cellular features and systematically test each feature to identify those that are best able to distinguish positive and negative controls while taking precautions to avoid overfitting the available data. The cell measurement software the authors previously developed, CellProfiler, makes both approaches straightforward, easing the process of assay development. Here, they demonstrate the use of the screening approach to image assay development to select the best measures for scoring publicly available image sets of 2 cytoplasm-to-nucleus translocation assays and 2 Transfluor assays. The authors present the resulting assay quality measures as a baseline for future algorithm comparisons, and all software, methods, and images they present are freely available.

The perception and control of self-movement relies on visual cues derived from the radial patterns of optic flow and from the relative motion of objects within view. Optic flow and object motion processing impairments might limit independent self-movement in a manner like that seen in ageing and in Alzheimer's disease. We used optic flow and object motion stimuli to simulate aspects of the self-movement scene. Stimulus salience was individualized to present comparable stimuli to young [n = 18; mean age = 25.6, standard error of measurement (SEM) = 1.4], middle-aged (n = 17; mean age = 53.9, SEM = 0.9), older adult (n = 30; mean age = 72.4, SEM = 1.4) and Alzheimer's disease (n = 15; mean age 75.2, SEM = 1.6) subjects. All groups were tested in two tasks: pointing towards the simulated direction of self-movement and steering the simulated self-movement towards a straight-ahead direction. We found that young and middle-aged subjects show similar pointing accuracy using either optic flow or object motion, but steer better with object motion than with optic flow. Older adult subjects show better performance with optic flow than object cues for pointing (P < 0.001), but their performance improves when both cues are combined in the pointing (P = 0.012) and steering (P = 0.02) tasks. Alzheimer's disease patients show poorer performance with optic flow and object motion than all other groups and do not benefit from the combined presentation of cues for either pointing or steering. We conclude that ageing and Alzheimer's disease are associated with distinct profiles of visual processing deficits that limit the ability to use optic flow and object motion to perceive and control self-movement.

The cellular content of mitochondria changes dynamically during development and in response to external stimuli, but the underlying mechanisms remain obscure. To systematically identify molecular probes and pathways that control mitochondrial abundance, we developed a high-throughput imaging assay that tracks both the per cell mitochondrial content and the cell size in confluent human umbilical vein endothelial cells. We screened 28,786 small molecules and observed that hundreds of small molecules are capable of increasing or decreasing the cellular content of mitochondria in a manner proportionate to cell size, revealing stereotyped control of these parameters. However, only a handful of compounds dissociate this relationship. We focus on one such compound, BRD6897, and demonstrate through secondary assays that it increases the cellular content of mitochondria as evidenced by fluorescence microscopy, mitochondrial protein content, and respiration, even after rigorous correction for cell size, cell volume, or total protein content. BRD6897 increases uncoupled respiration 1.6-fold in two different, non-dividing cell types. Based on electron microscopy, BRD6897 does not alter the percent of cytoplasmic area occupied by mitochondria, but instead, induces a striking increase in the electron density of existing mitochondria. The mechanism is independent of known transcriptional programs and is likely to be related to a blockade in the turnover of mitochondrial proteins. At present the molecular target of BRD6897 remains to be elucidated, but if identified, could reveal an important additional mechanism that governs mitochondrial biogenesis and turnover.

Summary: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline. Availability and Implementation: CellProfiler 2.0 is free and open source, available at http://www.cellprofiler.org under the GPL v. 2 license. It is available as a packaged application for Macintosh OS X and Microsoft Windows and can be compiled for Linux. Contact: anne@broadinstitute.org Supplementary information:Supplementary data are available at Bioinformatics online.