M icroRNAs (miRNAs) are small noncoding RNAs with cell-type specific expression patterns that are released by cells into the circulation as part of membranous particles or protein complexes.1 Thus, miRNAs can be readily quantified by real-time polymerase chain reactions (qPCRs) in plasma and serum and have generated increasing interest as potential new biomarkers.2 Our group has previously identified plateletrelated miRNA signatures that are predictive of cardiovascular events. 3 In addition, we measured miRNAs in healthy volunteers and in patients with symptomatic atherosclerosis before and after initiation of dual antiplatelet therapy and demonstrated reduced plasma levels of platelet-related miRNAs on platelet inhibition. Kaudewitz et al Plasma MicroRNAs and Platelet Function 421Dual oral antiplatelet therapy (acetylsalicylic acid [ASA]+a P2Y 12 inhibitor) is commonly used for the management of non-ST-segment-elevation acute coronary syndromes (ACS) and ST-segment-elevation myocardial infarction.5 ASA irreversibly inhibits cyclooxygenase 1 in platelets, thereby repressing thromboxane A 2 (TxA 2 ) synthesis and, consequently, platelet activation. Clopidogrel, prasugrel, and ticagrelor target the P2Y 12 receptor for ADP. However, interindividual variability in the platelet response to clopidogrel has been reported. Prasugrel and ticagrelor exhibit a more consistent antiplatelet effect and have shown benefits over clopidogrel in patients with ACS but also increase the risk of bleeding. 6,7 It is currently unclear whether plasma levels of platelet-related miRNAs correlate with the residual platelet activity in patients with ACS and how different antiplatelet agents alter miRNAs.In this study, we used RNA sequencing to characterize small RNAs in plasma. Then, we compared the effect of different antiplatelet agents and explored the association of small RNAs (miRNAs and YRNAs) with platelet function tests in patients with ACS. Moreover, we correlated their plasma levels to platelet activation markers in the prospective, population-based Bruneck study 3 and investigated whether a single-nucleotide polymorphism (SNP) that facilitates miR-126 processing 8 alters circulating miR-126 levels and platelet reactivity. These epidemiological observations were complemented by preclinical studies, assessing platelet function in mice on treatment with antagomiRs directed against miR-126 and by mechanistic studies measuring miR-126 targets. MethodsAn expanded Methods section is available in the Online Data Supplement. Next-Generation SequencingSmall RNA libraries were generated from non-normalized RNA (ranging from 375 pg to 1 ng) extracted from equal volumes of platelet-poor plasma (PPP) and platelet-rich plasma (PRP) from healthy human volunteers. Before library preparation, RNA was spiked with equal amounts of C. elegans miR-39 star (cel-miR-39*) to assist in normalization. Libraries were prepared using the small RNA library preparation kit version 2.0 (Illumina Cambridge Ltd) according to manufacturer's protocol with limi...

Manual gating has been traditionally applied to cytometry data sets to identify cells based on protein expression. The advent of mass cytometry allows for a higher number of proteins to be simultaneously measured on cells, therefore providing a means to define cell clusters in a high dimensional expression space. This enhancement, whilst opening unprecedented opportunities for single cell-level analyses, makes the incremental replacement of manual gating with automated clustering a compelling need. To this aim many methods have been implemented and their successful applications demonstrated in different settings. However, the reproducibility of automatically generated clusters is proving challenging and an analytical framework to distinguish spurious clusters from more stable entities, and presumably more biologically relevant ones, is still missing. One way to estimate cell clusters' stability is the evaluation of their consistent re-occurrence within-and between-algorithms, a metric that is commonly used to evaluate results from gene expression. Herein we report the usage and importance of cluster stability evaluations, when applied to results generated from three popular clustering algorithms -SPADE, FLOCK and PhenoGraph -run on four different data sets. These algorithms were shown to generate clusters with various degrees of statistical stability, many of them being unstable. By comparing the results of automated clustering with manually gated populations, we illustrate how information on cluster stability can assist towards a more rigorous and informed interpretation of clustering results. We also explore the relationships between statistical stability and other properties such as clusters' compactness and isolation, demonstrating that whilst cluster stability is linked to other properties it cannot be reliably predicted by any of them. Our study proposes the introduction of cluster stability as a necessary checkpoint for cluster interpretation and contributes to the construction of a more systematic and standardized analytical framework for the assessment of cytometry clustering results. V C 2016 International Society for Advancement of Cytometry

In this study, a predictive control system based on type Takagi-Sugeno fuzzy models was developed for a polymerization process. Such processes typically have a highly nonlinear dynamic behavior causing the performance of controllers based on conventional internal models to be poor or to require considerable effort in controller tuning. The copolymerization of methyl methacrylate with vinyl acetate was considered for analysis of the performance of the proposed control system. A nonlinear mathematical model which describes the reaction plant was used for data generation and implementation of the controller. The modeling using the fuzzy approach showed an excellent capacity for output prediction as a function of dynamic data input. The performance of the projected control system and dynamic matrix control for regulatory and servo problems were compared and the obtained results showed that the control system design is robust, of simple implementation and provides a better response than conventional predictive control. V V C 2009 American Institute of Chemical Engineers AIChE J, 56: 965-978, 2010

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