High levels of salinity induce serious oxidative damage in plants. Flavonoids, as antioxidants, have important roles in reactive oxygen species (ROS) scavenging. In the present study, the tobacco R2R3 MYB type repressor, NtMYB4, was isolated and characterized. The expression of NtMYB4 was suppressed by salinity. Overexpression of NtMYB4 reduced the salt tolerance in transgenic tobacco plants. NtMYB4 repressed the promoter activity of NtCHS1 and negatively regulated its expression. Rutin accumulation was significantly decreased in NtMYB4 overexpressing transgenic plants and NtCHS1 RNAi silenced transgenic plants. Moreover, high H 2 O 2 and contents were detected in both types of rutin-reduced transgenic plants under high salt stress. In addition, exogenous rutin supplementation effectively scavenged ROS (H 2 O 2 and ) and improved the salt tolerance of the rutin-reduced transgenic plants. In contrast, NtCHS1 overexpressing plants had increased rutin accumulation, lower H 2 O 2 and contents, and higher tolerance to salinity. These results suggested that tobacco NtMYB4 acts as a salinity response repressor and negatively regulates NtCHS1 expression, which results in the reduced flavonoid accumulation and weakened ROS-scavenging ability under salt stress.

Numerous studies have demonstrated the important role of noise in the dynamical behaviour of a complex system. The most probable trajectories of nonlinear systems under the influence of Gaussian noise have recently been studied already. However, there has been only a few works that examine how most probable trajectories in the two-dimensional system (MeKS network) are influenced under non-Gaussian stable Lévy noise. Therefore, we discuss the most probable trajectories of a two-dimensional model depicting the competence behaviour in B. subtilis under the influence of stable Lévy noise. On the basis of the Fokker-Planck equation, we describe the noise-induced most probable trajectories of the MeKS network from the low ComK protein concentration (vegetative state) to the high ComK protein concentration (competence state) under stable Lévy noise.We demonstrate choices of the non-Gaussianity index α and the noise intensity ǫ which generate the ComK protein escape from the low concentration to the high concentration. We also reveal the optimal combination of both parameters α and ǫ making the tipping time shortest. Moreover, we find that different initial concentrations around the low ComK protein concentration evolve to a metastable state, and provide the optimal α and ǫ such that the distance between the deterministic competence state and the metastable state is smallest.

Summary Ferulate 5‐hydroxylase (F5H) catalyses the hydroxylation of coniferyl alcohol and coniferaldehyde for the biosynthesis of syringyl (S) lignin in angiosperms. However, the coordinated effects of F5H with caffeic acid O ‐methyltransferase ( COMT ) on the metabolic flux towards S units are largely unknown. We concomitantly regulated F5H expression in COMT ‐down‐regulated transgenic switchgrass ( Panicum virgatum L.) lines and studied the coordination of F5H and COMT in lignin biosynthesis. Down‐regulation of F5H in COMT ‐ RNA i transgenic switchgrass plants further impeded S lignin biosynthesis and, consequently, increased guaiacyl (G) units and reduced 5‐ OH G units. Conversely, overexpression of F5H in COMT ‐ RNA i transgenic plants reduced G units and increased 5‐ OH units, whereas the deficiency of S lignin biosynthesis was partially compensated or fully restored, depending on the extent of COMT down‐regulation in switchgrass. Moreover, simultaneous regulation of F5H and COMT expression had different effects on cell wall digestibility of switchgrass without biomass loss. Our results indicate that up‐regulation and down‐regulation of F5H expression, respectively, have antagonistic and synergistic effects on the reduction in S lignin resulting from COMT suppression. The coordinated effects between lignin genes should be taken into account in future studies aimed at cell wall bioengineering.

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We investigate a quantitative bistable two-dimensional model (MeKS network) of gene expression dynamics describing the competence development in the Bacillus subtilis under the influence of Lévy as well as Brownian motions. To analyze the transitions between the vegetative and the competence regions therein, two dimensionless deterministic quantities, the mean first exit time (MFET) and the first escape probability, are determined from a microscopic perspective, as well as their averaged versions from a macroscopic perspective. The relative contribution factor λ, the ratio of non-Gaussian and Gaussian noise strengths, is adopted to identify an optimum choice in these transitions. Additionally, we use a recent geometric concept, the stochastic basin of attraction (SBA), to exhibit a pictorial comprehension about the influence of the Lévy motion on the basin stability of the competence state. Our main results indicate that (i) the transitions between the vegetative and the competence regions can be induced by the noise intensities, the relative contribution factor λ and the Lévy motion index α; (ii) a higher noise intensity and a larger α with smaller jump magnitude make the MFET shorter, and the MFET as a function of λ exhibits one maximum value, which is a signature of the noise-enhanced stability phenomenon for the vegetative state; (iii) a larger α makes the transition from the vegetative to the adjacent competence region to occur at the highest probability. The Lévy motion index α≈0.5 (a larger jump magnitude with a lower frequency) is an ideal choice to implement the transition to the non-adjacent competence region; (iv) there is an expansion in SBA when α decreases.

Aiming at the three-dimensional path planning of unmanned aerial vehicle (UAV) in the complex environment of material delivery in earthquake-stricken areas, this paper proposes an improved adaptive grey wolf optimization algorithm (AGWO) based on the grey wolf optimization algorithm (GWO). There are two main contributions of the proposed method. Firstly, we propose an adaptive convergence factor adjustment strategy and an adaptive weight factor to update the individual's position. The effectiveness of the improved algorithm is verified by the convergence analysis and the test function simulation experiment. Secondly, the improved algorithm is applied to UAV path planning, the environmental map model is established by integrating digital elevation map and equivalent mountain threat model, and the performance evaluation function is established by fitting the calculated track length. The simulation results show that the improved AGWO is superior to the traditional intelligent algorithm in convergence precision, speed and stability performance, and it is effective for 3D trajectory optimization in complex environment.INDEX TERMS Adaptive grey wolf optimization algorithm (AGWO), path planning, unmanned aerial vehicle (UAV).

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