Surgical strategies to treat articular cartilage injury such as microfracture, expose human bone marrow stem cells (hMSCs) to synovial fluid and its components. High molecular weight hyaluronan (hMwt HA) is one of the most abundant bioactive macromolecules of healthy synovial fluid (hSF) and it plays an important role in the protection of opposing articular cartilage surfaces within the synovial joint. Although hMwt HA has been extensively used to attempt the engineering of the cartilage tissue, its effect as media supplement has not been established. Indeed, current media are often simple in their composition and doesn't recapitulate the rheological and biological features of hSF. In addition, critical in vivo molecules that can potentially change the chondrogenic behavior of hBMSCs to make the in vitro results more predictive of the real in vivo outcome, are lacking. In order to be one step closer to the in vivo physiology of hSF, a new culture media supplemented with physiological level of hMwt HA was deveium component in a more reliable in vitro/ex vivo system to reduce in vitro artifacts, enable more accurate pre-screening of potential cartilage repair therapies and reduce the need for animal studies. Copyright © 2020 Monaco, El Haj, Alini and Stoddart.Mesenchymal stem cells are a promising source for externally grown tissue replacements and patient-specific immunomodulatory treatments. https://www.selleckchem.com/products/perhexiline-maleate.html This promise has not yet been fulfilled in part due to production scaling issues and the need to maintain the correct phenotype after re-implantation. One aspect of extracorporeal growth that may be manipulated to optimize cell growth and differentiation is metabolism. The metabolism of MSCs changes during and in response to differentiation and immunomodulatory changes. MSC metabolism may be linked to functional differences but how this occurs and influences MSC function remains unclear. Understanding how MSC metabolism relates to cell function is however important as metabolite availability and environmental circumstances in the body may affect the success of implantation. Genome-scale constraint based metabolic modeling can be used as a tool to fill gaps in knowledge of MSC metabolism, acting as a framework to integrate and understand various data types (e.g., genomic, transcriptomic and metabolomic). These approaches have long been used to optimize the growth and productivity of bacterial production systems and are being increasingly used to provide insights into human health research. Production of tissue for implantation using MSCs requires both optimized production of cell mass and the understanding of the patient and phenotype specific metabolic situation. This review considers the current knowledge of MSC metabolism and how it may be optimized along with the current and future uses of genome scale constraint based metabolic modeling to further this aim. Copyright © 2020 Sigmarsdóttir, McGarrity, Rolfsson, Yurkovich and Sigurjónsson.There is a distinct clinical need for new therapies that provide an effective treatment for large bone defect repair. Herein we describe a developmental approach, whereby constructs are primed to mimic certain aspects of bone formation that occur during embryogenesis. Specifically, we directly compared the bone healing potential of unprimed, intramembranous, and endochondral primed MSC-laden polycaprolactone (PCL) scaffolds. To generate intramembranous constructs, MSC-seeded PCL scaffolds were exposed to osteogenic growth factors, while endochondral constructs were exposed to chondrogenic growth factors to generate a cartilage template. Eight weeks after implantation into a cranial critical sized defect in mice, there were significantly more vessels present throughout defects treated with endochondral constructs compared to intramembranous constructs. Furthermore, 33 and 50% of the animals treated with the intramembranous and endochondral constructs respectively, had full bone union along the sagittal suture line, with significantly higher levels of bone healing than the unprimed group. Having demonstrated the potential of endochondral priming but recognizing that only 50% of animals completely healed after 8 weeks, we next sought to examine if we could further accelerate the bone healing capacity of the constructs by pre-vascularizing them in vitro prior to implantation. The addition of endothelial cells alone significantly reduced the healing capacity of the constructs. The addition of a co-culture of endothelial cells and MSCs had no benefit to either the vascularization or mineralization potential of the scaffolds. Together, these results demonstrate that endochondral priming alone is enough to induce vascularization and subsequent mineralization in a critical-size defect. Copyright © 2020 Freeman, Brennan, Browe, Renaud, De Lima, Kelly, McNamara and Layrolle.RNA 5-hydroxymethylcytosine (5hmC) modification plays an important role in a series of biological processes. Characterization of its distributions in transcriptome is fundamentally important to reveal the biological functions of 5hmC. Sequencing-based technologies allow the high-throughput identification of 5hmC; however, they are labor-intensive, time-consuming, as well as expensive. Thus, there is an urgent need to develop more effective and efficient computational methods, at least complementary to the high-throughput technologies. In this study, we developed iRNA5hmC, a computational predictive protocol to identify RNA 5hmC sites using machine learning. In this predictor, we introduced a sequence-based feature algorithm consisting of two feature representations, (1) k-mer spectrum and (2) positional nucleotide binary vector, to capture the sequential characteristics of 5hmC sites. Afterward, we utilized a two-stage feature space optimization strategy to improve the feature representation ability, and trained a predictive model using support vector machine (SVM). Our feature analysis results showed that feature optimization can help to capture the most discriminative features. As compared to well-known existing feature descriptors, our proposed representations can more accurately separate true 5hmC from non-5hmC sites. To the best of our knowledge, iRNA5hmC is the first RNA 5hmC predictor that enables to make predictions based on RNA primary sequences only, without any need of prior experimental knowledge. Importantly, we have established an easy-to-use webserver which is currently available at http//server.malab.cn/iRNA5hmC. We expect it has potential to be a useful tool for the prediction of 5hmC sites. Copyright © 2020 Liu, Chen, Su, Chen and Wei.