Plasma exosomal microRNAs are non-invasive biomarkers of moyamoya disease: A pilot study

Background: As a progressive cerebrovascular disease, Moyamoya Disease (MMD) is a common cause of stroke in children and adults. However, the early biomarkers and pathogenesis of MMD remain poorly understood. Methods and material: This study was conducted using plasma exosome samples from MMD patients. Next-generation high-throughput sequencing, real-time quantitative PCR, gene ontology analysis, and Kyoto Encyclopaedia of Genes and Genomes pathway analysis of ideal exosomal miRNAs that could be used as potential biomarkers of MMD were performed. The area under the Receiver Operating Characteristic (ROC) curve was used to evaluate the sensitivity and specificity of biomarkers for predicting events. Results: Exosomes were successfully isolated and miRNA-sequence analysis yielded 1,002 differentially expressed miRNAs. Functional analysis revealed that they were mainly enriched in axon guidance, regulation of the actin cytoskeleton and the MAPK signaling pathway. Furthermore, 10 miRNAs (miR-1306-5p, miR-196b-5p, miR-19a-3p, miR-22-3p, miR-320b, miR-34a-5p, miR-485-3p, miR-489-3p, miR-501-3p, and miR-487-3p) were found to be associated with the most sensitive and specific pathways for MMD prediction. Conclusions: Several plasma secretory miRNAs closely related to the development of MMD have been identified, which can be used as biomarkers of MMD and contribute to differentiating MMD from non-MMD patients before digital subtraction angiography

Sliding-Mode Perturbation Observer-Based Sliding-Mode Control for VSC-HVDC Systems

This chapter develops a sliding-mode perturbation observer-based sliding-mode control (POSMC) scheme for voltage source converter-based high voltage direct current (VSC-HVDC) systems. The combinatorial effect of nonlinearities, parameter uncertainties, unmodeled dynamics, and time-varying external disturbances is aggregated into a perturbation, which is estimated online by a sliding-mode state and perturbation observer (SMSPO). POSMC does not require an accurate VSC-HVDC system model and only the reactive power and DC voltage at the rectifier side while reactive and active powers at the inverter side need to be measured. Additionally, a considerable robustness can be provided through the real-time compensation of the perturbation, in which the upper bound of perturbation is replaced by the real-time estimation of the perturbation, such that the over-conservativeness of conventional sliding-mode control (SMC) can be effectively reduced. Four case studies are carried out on the VSC-HVDC system, such as active and reactive power tracking, AC bus fault, system parameter uncertainties, and weak AC gird connection. Simulation results verify its advantages over vector control and feedback linearization sliding-mode control. Then, a dSPACE-based hardware-in-the-loop (HIL) test is undertaken to validate the implementation feasibility of the proposed approach

Quantitative regulation of FLC via coordinated transcriptional initiation and elongation

The basis of quantitative regulation of gene expression is still poorly understood. In Arabidopsis thaliana, quantitative variation in expression of FLOWERING LOCUS C (FLC) influences the timing of flowering. In ambient temperatures, FLC expression is quantitatively modulated by a chromatin silencing mechanism involving alternative polyadenylation of antisense transcripts. Investigation of this mechanism unexpectedly showed that RNA polymerase II (Pol II) occupancy changes at FLC did not reflect RNA fold changes. Mathematical modeling of these transcriptional dynamics predicted a tight coordination of transcriptional initiation and elongation. This prediction was validated by detailed measurements of total and chromatin-bound FLC intronic RNA, a methodology appropriate for analyzing elongation rate changes in a range of organisms. Transcription initiation was found to vary ∼25-fold with elongation rate varying ∼8- to 12-fold. Premature sense transcript termination contributed very little to expression differences. This quantitative variation in transcription was coincident with variation in H3K36me3 and H3K4me2 over the FLC gene body. We propose different chromatin states coordinately influence transcriptional initiation and elongation rates and that this coordination is likely to be a general feature of quantitative gene regulation in a chromatin context

Overexpression of AtBMI1C, a Polycomb Group Protein Gene, Accelerates Flowering in Arabidopsis

Polycomb group protein (PcG)-mediated gene silencing is emerging as an essential developmental regulatory mechanism in eukaryotic organisms. PcGs inactivate or maintain the silenced state of their target chromatin by forming complexes, including Polycomb Repressive Complex 1 (PRC1) and 2 (PRC2). Three PRC2 complexes have been identified and characterized in Arabidopsis; of these, the EMF and VRN complexes suppress flowering by catalyzing the trimethylation of lysine 27 on histone H3 of FLOWER LOCUS T (FT) and FLOWER LOCUS C (FLC). However, little is known about the role of PRC1 in regulating the floral transition, although AtRING1A, AtRING1B, AtBMI1A, and AtBMI1B are believed to regulate shoot apical meristem and embryonic development as components of PRC1. Moreover, among the five RING finger PcGs in the Arabidopsis genome, four have been characterized. Here, we report that the fifth, AtBMI1C, is a novel, ubiquitously expressed nuclear PcG protein and part of PRC1, which is evolutionarily conserved with Psc and BMI1. Overexpression of AtBMI1C caused increased H2A monoubiquitination and flowering defects in Arabidopsis. Both the suppression of FLC and activation of FT were observed in AtBMI1C-overexpressing lines, resulting in early flowering. No change in the H3K27me3 level in FLC chromatin was detected in an AtBMI1C-overexpressing line. Our results suggest that AtBMI1C participates in flowering time control by regulating the expression of FLC; moreover, the repression of FLC by AtBMI1C is not due to the activity of PRC2. Instead, it is likely the result of PRC1 activity, into which AtBMI1C is integrated