EbMYBP1, a R2R3-MYB transcription factor, promotes flavonoid biosynthesis in Erigeron breviscapus

Erigeron breviscapus, a traditional Chinese medicinal plant, is enriched in flavonoids that are beneficial to human health. While we know that R2R3-MYB transcription factors (TFs) are crucial to flavonoid pathway, the transcriptional regulation of flavonoid biosynthesis in E. breviscapus has not been fully elucidated. Here, EbMYBP1, a R2R3-MYB transcription factor, was uncovered as a regulator involved in the regulation of flavonoid accumulation. Transcriptome and metabolome analysis revealed that a large group of genes related to flavonoid biosynthesis were significantly changed, accompanied by significantly increased concentrations of the flavonoid in EbMYBP1-OE transgenic tobacco compared with the wild-type (WT). In vitro and in vivo investigations showed that EbMYBP1 participated in flavonoid biosynthesis, acting as a nucleus-localized transcriptional activator and activating the transcription of flavonoid-associated genes like FLS, F3H, CHS, and CHI by directly binding to their promoters. Collectively, these new findings are advancing our understanding of the transcriptional regulation that modulates the flavonoid biosynthesis

A generalization of the graph Laplacian with application to a distributed consensus algorithm

In order to describe the interconnection among agents with multi-dimensional states, we generalize the notion of a graph Laplacian by extending the adjacency weights (or weighted interconnection coefficients) from scalars to matrices. More precisely, we use positive definite matrices to denote full multi-dimensional interconnections, while using nonnegative definite matrices to denote partial multi-dimensional interconnections. We prove that the generalized graph Laplacian inherits the spectral properties of the graph Laplacian. As an application, we use the generalized graph Laplacian to establish a distributed consensus algorithm for agents described by multi-dimensional integrators

Switching in Systems and Control—Daniel Liberzon (Boston, MA:

A hybrid system is a dynamical system whose evolution depends on a coupling between variables that take values in a continuum and variables that take values in a finite or countable set [8]. Therefore, two kinds of dynamics, namely continuous dynamics and discrete events, coexist and interact in such systems. Since there are many practical systems which should reasonably be described as hybrid systems, there has been increasing interest in the analysis and design for such systems in the last two decades. Due to its interdisciplinary nature, research attention in this relatively new but very active area has been growing among people with very diverse backgrounds including mathematicians, control engineers and computer scientists. As was also pointed out in [8], the current research on hybrid systems has been inspired by motivations in many areas. For example, computer scientists are interested in verification of correctness of programs interacting with continuous environments (embedded systems); control theorists are focused on hierarchica

Generalized Practical Stability Analysis of Discontinuous Dynamical Systems. In CDC’03. you find a list of the most recent technical reports of the Max-Planck-Institut f ür Informatik. They are available by anonymous ftp from ftp.mpi-sb.mpg.de under the

In practice, one is not only interested in the qualitative characterizations provided by the Lyapunov stability, but also in quantitative information concerning the system behavior, including estimates of trajectory bounds, possibly over finite time intervals. This type of information has been ascertained in the past in a systematic manner using the concept of practical stability. In the present paper, we give a new definition of generalized practical stability (abbreviated as GP-stability) and establish some sufficient conditions concerning GP-stability for a wide class of discontinuous dynamical systems. As in the classical Lyapunov theory, our results constitute a Direct Method, making use of auxiliary scalar-valued Lyapunovlike functions. These functions, however, have properties that differ significantly from the usual Lyapunov functions. We demonstrate the applicability of our results by means of several specific examples