This review describes recent progresses in the development and applications of smart polymeric gels, especially in the context of biomedical devices. The review has been organized into three separate sections: defining the basis of smart properties in polymeric gels; describing representative stimuli to which these gels respond; and illustrating a sample application area, namely, microfluidics. One of the major limitations in the use of hydrogels in stimuli-responsive applications is the diffusion rate limited transduction of signals. This can be obviated by engineering interconnected pores in the polymer structure to form capillary networks in the matrix and by downscaling the size of hydrogels to significantly decrease diffusion paths. Reducing the lag time in the induction of smart responses can be highly useful in biomedical devices, such as sensors and actuators. This review also describes molecular imprinting techniques to fabricate hydrogels for specific molecular recognition of target analytes. Additionally, it describes the significant advances in bottom-up nanofabrication strategies, involving supramolecular chemistry. Learning to assemble supramolecular structures from nature has led to the rapid prototyping of functional supramolecular devices. In essence, the barriers in the current performance potential of biomedical devices can be lowered or removed by the rapid convergence of interdisciplinary technologies.

MG-RAST (http://metagenomics.anl.gov) is an open-submission data portal for processing, analyzing, sharing and disseminating metagenomic datasets. The system currently hosts over 200 000 datasets and is continuously updated. The volume of submissions has increased 4-fold over the past 24 months, now averaging 4 terabasepairs per month. In addition to several new features, we report changes to the analysis workflow and the technologies used to scale the pipeline up to the required throughput levels. To show possible uses for the data from MG-RAST, we present several examples integrating data and analyses from MG-RAST into popular third-party analysis tools or sequence alignment tools.

Vascular smooth muscle cells (vSMCs) retain the ability to undergo modulation in their phenotypic continuum, ranging from a mature contractile state to a proliferative, secretory state. vSMC differentiation is modulated by a complex array of microenvironmental cues, which include the biochemical milieu of the cells and the architecture and stiffness of the extracellular matrix. In this study, we demonstrate that by using UV-assisted capillary force lithography (CFL) to engineer a polyurethane substratum of defined nanotopography and stiffness, we can facilitate the differentiation of cultured vSMCs, reduce their inflammatory signature, and potentially promote the optimal functioning of the vSMC contractile and cytoskeletal machinery. Specifically, we found that the combination of medial tissue-like stiffness (11 MPa) and anisotropic nanotopography (ridge width_groove width_ridge height of 800_800_600 nm) resulted in significant upregulation of calponin, desmin, and smoothelin, in addition to the downregulation of intercellular adhesion molecule-1, tissue factor, interleukin-6, and monocyte chemoattractant protein-1. Further, our results allude to the mechanistic role of the RhoA/ROCK pathway and caveolin-1 in altered cellular mechanotransduction pathways via differential matrix nanotopography and stiffness. Notably, the nanopatterning of the stiffer substrata (1.1 GPa) resulted in the significant upregulation of RhoA, ROCK1, and ROCK2. This indicates that nanopatterning an 800_800_600 nm pattern on a stiff substratum may trigger the mechanical plasticity of vSMCs resulting in a hypercontractile vSMC phenotype, as observed in diabetes or hypertension. Given that matrix stiffness is an independent risk factor for cardiovascular disease and that CFL can create different matrix nanotopographic patterns with high pattern fidelity, we are poised to create a combinatorial library of arterial test beds, whether they are healthy, diseased, injured, or aged. Such high-throughput testing environments will pave the way for the evolution of the next generation of vascular scaffolds that can effectively crosstalk with the scaffold microenvironment and result in improved clinical outcomes.

As technologies change, MG-RAST is adapting. Newly available software is being included to improve accuracy and performance. As a computational service constantly running large volume scientific workflows, MG-RAST is the right location to perform benchmarking and implement algorithmic or platform improvements, in many cases involving trade-offs between specificity, sensitivity and run-time cost. The work in [Glass EM, Dribinsky Y, Yilmaz P, et al. ISME J 2014;8:1-3] is an example; we use existing well-studied data sets as gold standards representing different environments and different technologies to evaluate any changes to the pipeline. Currently, we use well-understood data sets in MG-RAST as platform for benchmarking. The use of artificial data sets for pipeline performance optimization has not added value, as these data sets are not presenting the same challenges as real-world data sets. In addition, the MG-RAST team welcomes suggestions for improvements of the workflow. We are currently working on versions 4.02 and 4.1, both of which contain significant input from the community and our partners that will enable double barcoding, stronger inferences supported by longer-read technologies, and will increase throughput while maintaining sensitivity by using Diamond and SortMeRNA. On the technical platform side, the MG-RAST team intends to support the Common Workflow Language as a standard to specify bioinformatics workflows, both to facilitate development and efficient high-performance implementation of the community's data analysis tasks.

Despite great progress in biomaterial design strategies for replacing damaged articular cartilage, prevention of stem cell-derived chondrocyte hypertrophy and resulting inferior tissue formation is still a critical challenge. Here, by using engineered biomaterials and a high-throughput system for screening of combinatorial cues in cartilage microenvironments, we demonstrate that biomaterial cross-linking density that regulates matrix degradation and stiffness—together with defined presentation of growth factors, mechanical stimulation, and arginine-glycine-aspartic acid (RGD) peptides—can guide human mesenchymal stem cell (hMSC) differentiation into articular or hypertrophic cartilage phenotypes. Faster-degrading, soft matrices promoted articular cartilage tissue formation of hMSCs by inducing their proliferation and maturation, while slower-degrading, stiff matrices promoted cells to differentiate into hypertrophic chondrocytes through Yes-associated protein (YAP)–dependent mechanotransduction. in vitro and in vivo chondrogenesis studies also suggest that down-regulation of the Wingless and INT-1 (WNT) signaling pathway is required for better quality articular cartilage-like tissue production.