Integrated transcriptomic and metabolomic analysis provides insights into cold tolerance in lettuce (Lactuca sativa L.).

The popular leafy vegetable lettuce (Lactuca sativa L.) is susceptible to cold stress during the growing season, which slows growth rate, causes leaf yellowing and necrosis, and reduced yield and quality. In this study, transcriptomic and metabolomic analyses of two cold-resistant lettuce cultivars (GWAS-W42 and F11) and two cold-sensitive lettuce cultivars (S13K079 and S15K058) were performed to identify the mechanisms involved in the cold response of lettuce. Overall, transcriptome analysis identified 605 differentially expressed genes (DEGs), including significant enrichment of genes involved in the flavonoid and flavonol (CHS, CHI, F3H, FLS, CYP75B1, HCT, etc.) biosynthetic pathways related to oxidation-reduction and catalytic activity. Untargeted metabolomic analysis identified fifteen flavonoid metabolites and 28 other metabolites potentially involved in the response to cold stress; genistein, quercitrin, quercetin derivatives, kaempferol derivatives, luteolin derivatives, apigenin and their derivatives accumulate at higher levels in cold-resistant cultivars. Moreover, MYBs, bHLHs, WRKYs and Dofs also play positive role in the low temperature response, which affected the expression of structural genes contributing to the variation of metabolites between the resistant and sensitive. These results provide valuable evidence that the metabolites and genes involved in the flavonoid biosynthetic pathway play important roles in the response of lettuce to cold stress.

Correction: Mechanistic insights into Ag+ induced size-growth from [Au6(DPPP)4]2+ to [Au7(DPPP)4]2+ clusters.

[This corrects the article DOI: 10.1039/D2NA00301E.].

A Distributed Proximal Consensus Algorithm for Energy Saving in Ethylene Production.

This article presents a distributed optimization framework in order to solve the plant-wide energy-saving problem of an ethylene plant. First, the ethylene production process is abstracted into a distributed network, and then, a new distributed consensus algorithm is proposed, which is called adaptive step-size-based distributed proximal consensus algorithm (ASS-DPCA). This algorithm can dynamically adjust the step size and automatically abandon the irrational evolutionary route while eliminating the dependence of optimization algorithms on model gradient information. Moreover, the designed algorithm is able to converge to an optimal solution for any convex cost functions and approach to a convex constraint set of agents over an undirected connected graph. Finally, the results of numerical simulation and industrial experiments show that the algorithm can reduce the total energy consumption of an ethylene plant with less computing time and assured consensus.

Seed color in lettuce is determined by the LsTT2, LsCHS, and Ls2OGD genes from the flavonoid biosynthesis pathway.

KEY MESSAGE: The mutated LsTT2 and Ls2OGD genes are responsible for white seeds and yellow seeds in lettuce, respectively. Three LsCHS genes are involved in the biosynthesis of flavonoid in seed coats. Lettuce seeds have several different colors, including black, yellow, and white. The genetic mechanisms underlying color variations of lettuce seeds remain unknown. We used genome-wide association studies (GWAS) and map-based cloning approaches to clone genes controlling the color of lettuce seeds. LsTT2, which encodes an R2R3-MYB transcription factor and is homologous to the TT2 gene in Arabidopsis, was shown to be the causal gene for the variation of black and white seeds in lettuce. A point mutation leads to the lack of stop codon in the LsTT2 transcript, resulting in white seeds. Knockout of the LsTT2 gene converted black seeds to white seeds. The locus controlling yellow seeds was mapped to Chromosome 2. Knockout of two 2-oxoglutarate-dependent dioxygenases (2OGD) genes from the candidate region converted black seeds to yellow seeds, suggesting that these two 2OGD proteins catalyze the conversion of yellow metabolites to black metabolites. We also showed that three LsCHS genes from the candidate region are associated with flavonoid biosynthesis in seeds. Knockout mutants of the three LsCHS genes decreased color intensity. This study provides new insights into the regulation of flavonoid biosynthesis in plants.

Motif-to-Core Nucleation in a Decahedral Evolution Pattern.

The atomic precision of ultrasmall metal nanoclusters has opened the door to elucidating the structural evolution principles of metal nanomaterials at the molecular level. Here, we report a novel set of super-atomic Ag clusters, including [Ag19(TBBT)16(DPPP)4]+ (Ag19), [Ag22(DMAT)8(DPPM)4Cl8]2+ (Ag22), Ag26(SPh3,5-CF3)15(DPPF)4Cl5 (Ag26), and [Ag30(DMAT)12(DPPP)4Cl8]2+ (Ag30). The core structures of these clusters correspond to one decahedral Ag7, perpendicular bi-decahedrons, three-dimensional penta-decahedrons, and hexa-decahedrons, respectively. The Ag atoms in AgS2 blocks show a strong correlation with the decahedral cores: the five equatorial Ag atoms in the decahedral Ag7 core of Ag19 all adopt the AgS2 coordination, while the Ag atoms in AgS2 blocks of Ag22, Ag26, and Ag30 unexceptionally constitute additional decahedral structures with the core Ag atoms. Specifically, two and four core Ag atoms of Ag26 and Ag30 clusters occupy positions that highly resemble that of Ag (in AgS2 motifs) of Ag22. The strong structural correlation demonstrates the motif-to-core evolution of the surface Ag (on AgS2) to build extra-decahedral blocks. Density functional theory calculations indicate that the 2e, 4e, 6e, and 8e clusters (from Ag19 to Ag30) adopt 1S2, 1S21P2, 1S21P4, and 1S21P6 electron configurations, all of which feature excellent super-atomic characters.

The one/two atom size-reduction of [Au23SCy16]- induced by the [Au6(dppp)4]2+ cluster.

The recent progress in atomically precise metal (Au, Ag etc.) nanoclusters has greatly enriched the molecular-level mechanistic understanding of metal nanomaterials. Herein, using two meta-stable (easy formation, easy transformation) clusters, i.e. [Au23SCy16]- and [Au6(dppp)4]2+ (HSCy and dppp denote cyclohexanethiol and 1,3-bis(diphenylphosphino)propane), as the reaction precursors, the etching of Au23 occurs smoothly, giving the one/two-atom size-reduced [Au21SCy12(dppp)2]+ and [Au22SCy14(dppp)]2+ as the major products. Structural analysis and DFT calculations indicate that the active reaction site of Au23 lies in the core-shell interference of the bi-capped icosahedral Au15 core and the AuS2 motifs. The fluorescence, band gap, and thermostability of the Au21 cluster products are improved compared to that of the Au23 precursors.

Data-driven control of hydraulic servo actuator: An event-triggered adaptive dynamic programming approach.

Hydraulic servo actuators (HSAs) are often used in the industry in tasks that request great power, high accuracy and dynamic motion. It is well known that an HSA is a highly complex nonlinear system, and that the system parameters cannot be accurately determined due to various uncertainties, an inability to measure some parameters and disturbances. This paper considers an event-triggered learning control problem of the HSA with unknown dynamics based on adaptive dynamic programming (ADP) via output feedback. Due to increasing practical application of the control algorithm, a linear discrete model of HSA is considered and an online learning data driven controller is used, which is based on measured input and output data instead of unmeasurable states and unknown system parameters. Hence, the ADP-based data driven controller in this paper requires neither the knowledge of the HSA dynamics nor exosystem dynamics. Then, an event-based feedback strategy is introduced to the closed-loop system to save the communication resources and reduce the number of control updates. The convergence of the ADP-based control algorithm is also theoretically shown. Simulation results verify the feasibility and effectiveness of the proposed approach in solving the optimal control problem of HSAs.

Co-Design of Adaptive Event-Triggered Mechanism and Asynchronous H∞ Control for 2-D Markov Jump Systems via Genetic Algorithm.

This article concerns the co-design scheme of the adaptive event-triggered mechanism (AETM) and asynchronous H∞ control for two-dimensional (2-D) Markov jump systems. First, we introduce a hidden Markov model with the observation that the asynchronous phenomenon is inevitable between the plant mode and the controller mode. Besides, for economizing the communication times, an innovative 2-D AETM is constructed, which can dynamically regulate the event-triggered thresholds to strive for better system performance. Then, by utilizing the 2-D Lyapunov stability theory, nonlinear matrix inequalities are built to ensure the asymptotic mean-square stability with an H∞ performance for the closed-loop 2-D system. To avoid introducing any conservatism when handling the above nonlinear matrix inequalities, a binary-based genetic algorithm (BGA) is exploited to treat some variables as known, such that derive some directly solvable linear matrix inequalities. Finally, a simulation example is provided to verify the effectiveness of the proposed 2-D AETM-based asynchronous controller strategy with a BGA.

Co-Design of Adaptive Event Generator and Asynchronous Fault Detection Filter for Markov Jump Systems via Genetic Algorithm.

This article investigates the co-design problem of adaptive event-triggered schemes (AETSs) and asynchronous fault detection filter (AFDF) for nonhomogeneous higher-level Markov jump systems, involving the hidden Markov model (HMM), higher-level Markov chain (MC), and conic-type nonlinearities. The transformation of the system transition probability can be reflected by the designed higher-level MC. An HMM with another conditional transition probability is applied to detect higher-level Markov processes and make the system be more practical. In order to balance the utilization of network resources and system performance, a novel AETS is proposed and used in the construction of the AFDF. By the Lyapunov theory, sufficient conditions are given to ensure the existences of the AETS and AFDF. It is not only an appropriate tradeoff between the utilization of network resources and system performance, but also reduces the conservatism. Finally, a numerical example is given to detect the faults effectively by the co-designed AFDF.

Solving the Zero-Sum Control Problem for Tidal Turbine System: An Online Reinforcement Learning Approach.

A novel completely mode-free integral reinforcement learning (CMFIRL)-based iteration algorithm is proposed in this article to compute the two-player zero-sum games and the Nash equilibrium problems, that is, the optimal control policy pairs, for tidal turbine system based on continuous-time Markov jump linear model with exact transition probability and completely unknown dynamics. First, the tidal turbine system is modeled into Markov jump linear systems, followed by a designed subsystem transformation technique to decouple the jumping modes. Then, a completely mode-free reinforcement learning algorithm is employed to address the game-coupled algebraic Riccati equations without using the information of the system dynamics, in order to reach the Nash equilibrium. The learning algorithm includes one iteration loop by updating the control policy and the disturbance policy simultaneously. Also, the exploration signal is added for motivating the system, and the convergence of the CMFIRL iteration algorithm is rigorously proved. Finally, a simulation example is given to illustrate the effectiveness and applicability of the control design approach.

The Novel Fluorescent Probe Toward Yttrium(III) and its Bioimaging.

In this paper, the novel fluorescence probe XP based on Schiff-base was designed, synthesized and characterized, which could detect Y3+selectively and sensitively. The recognition mechanism of XP toward Y3+ was studied by Job's plot and HRMS. It was investigated that stoichiometric ratio of the probe XP conjugated with Y3+ was 1:2. And the detection limit was calculated as 0.30 µM. In addition, Y3+ was recognized by the test paper made from XP. And the probe XP could detect  Y3+ selectively in Caenorhabditis elegans and the main organs of mice. Thus, XP was considered to have some potential for application in bioimaging.

DFT Insights into the Variety in the Coordination Modes of the Equatorial Halides in [Au13 Ag12 (PR3 )10 X8 ]+ (X=Cl/Br) Clusters.

The bonding character within metal nanoclusters represents an intriguing topic, shedding light on the inherent driving force for the packing preference in nanomaterials. Herein, density functional theory (DFT) calculations were conducted to investigate the correlation of the series of isomeric [Au13 Ag12 (PR3 )10 X8 ]+ (X=Cl/Br) clusters, which are mainly differentiated by the coordination mode of the equatorial halides (µ2 -, µ3 - and µ4 -) in the rod-like, bi-icosahedral framework. The theoretical simulation corroborates the variety in the configuration of the Au13 Ag12 clusters and elucidates the fast isomerization kinetics among the different configurations. The easy tautomerization and the variety in chloride binding modes correspond to a fluxionality character of the equatorial halides and are verified by the potential energy curve analysis. The structural flexibility of the central Au3 Ag10 block is the main driving force, while the relatively stronger Ag-X bonding interaction (compared to that of Au-X), and a sufficient number of halides are also requisite for the associating Ag-X tautomerizations.

First Report of Enterobacter cloacae Causing Stem, Leaf and Fruit Rot on Tomato in China.

Tomato (Solanum lycopersicum L.), as one of the most economically important and highly nutritious vegetable crops across the world, is widely cultivated in China, one of the largest tomato-concuming countries in the world (Ye et al., 2020; Wang and Liu, 2021). At present, major bacterial diseases in tomato include bacterial speck disease, tomato bacterial wilt and bacterial canker, all of which affect the tomato production around the world (Rosli et al., 2021; Peritore-Galve et al., 2021; Wang et al., 2022). In April 2022, a new bacterial disease was discovered on leaves, stems and fruits of tomato in a farmer's greenhouse located in Longfeng District in DaQing (125°07`-125°15`E, 46°28`-46°32`N), Heilongjiang Province, China. This field had tomato disease incidences approximately 50%. Apparent brown discolorations were found on fruits, leaves and stems in tomato plants. Symptoms were similar to fungal brown spots caused by Phytophthora infestans of tomato (Zhi et al.,2021; Liu et al.,2021) (Supplementary Figure S1). To isolate and identify the pathogen, the tissues of infected fruits, leaves and stems with typical symptoms were excised from diseased plants separately, and were disinfected with 75% ethanol for 10 s followed by 2% NaClO for 3 min and then washed five to eight times with sterile water (Wang et al., 2017). Afterwards, the samples were plated on nutrient agar (NA) solid medium and incubated. After incubation at 30°C for 2-3 days, bacterial colonies were isolated, then purified on nutrient agar (NA) solid medium at least twice by a streak plate method (Dou et al., 2019; Li et al, 2021; Zhao et al., 2022). White colonies grew on the NA medium after incubating for 2 days, showing round, opaque and smooth, which was similar to characteristics described as Enterobacter cloacae (García-González et al., 2018; Li et al, 2021). To further confirm the speculation on the identity of the isolated bacterium, the fragments of 16S rRNA were amplified and sequenced. The sequence of 16S rRNA was uploaded into GeneBank with accession numbers (OP077195.1). BLAST analysis of the sequence showed 97.68% identity with one corresponding sequence of E. cloacae in GeneBank (namely MK937637.1). Furthermore, a phylogenetic tree based on the sequence of 16S rRNA gene revealed that the isolate was grouped in the same clade as E. cloacae (Supplementary Figure S2). Based on Koch postulates to test pathogenicity of isolated bacteria, bacteria were inoculated on 30 day-old healthy tomato plants with three leaves stages, and the re-isolation of bacteria were carried out after 2 days of inoculation. To confirm pathogenicity, the isolates were cultured on LB medium at 30℃ for 2 days to prepare suspensions and adjusted to an optical density (OD) of 0.2 at A600, with a final concentration of 1ⅹ108 CFU/ml. Eight potted tomato plants were sprayed with bacteria suspensions, and eight control potted plants were sprayed with sterile distilled water. These seedlings were incubated in a chamber at 30°C with a 12 h light/dark photoperiod, with 85% relative humidity. After 2 days, inoculated tomato seedlings showed irregular small spots in leaves and brown necrosis at blade tips, and 8 to 10 days later, the leaves of tomato plants browned and died. The symptoms were the same with those of the initial diseased leaves of tomato plants (Supplementary Figure S1). No symptoms were observed on the control leaves (Supplementary Figure S3). Pathogenicity tests were repeated three biological times with same results. Meanwhile, the bacteria strains were re-isolated from symptomatic inoculated seedlings and confirmed as E. cloacae by culture and sequence methods as above. In China, there are no detailed records about the causal agent of this disease on tomato in a published paper in Chinese and English. To our knowledge, this is the first report of Enterobacter leaf brown necrosis caused by E. cloacae on tomato in China. Those results are of great significance for the production and management of tomato in greenhouse and control of the disease.

Mechanistic Insights into Oxidation-Induced Size Conversion of [Au6(dppp)4]2+ to [Au8(dppp)4Cl2]2.

Oxidation-induced conversion of gold nanoclusters is an important strategy for preparing novel atomically precise clusters and elucidating the kinetic correlations of different clusters. Herein, the oxidation-induced growth from [Au6(dppp)4]2+ to [Au8(dppp)4Cl2]2+ (reported by Konishi and co-workers) has been studied by density functional theory calculations. A successive oxidation → Cl- coordination → oxidation → Cl- coordination sequence occurs first to activate the Au6 structure, resulting in the high Au(core)-Au(corner) bond cleavage activity and the subsequent formation of [Au2(dppp)2Cl]+ and [Au4(dppp)2Cl]+ fragments. Then, the dimerization of two Au4 fragments and the rearrangement of the diphosphine coordination occur to generate the thermodynamically stable [Au8(dppp)4Cl2]2+ products. The proposed mechanism agrees with the experimental outcome for the fast reaction rate and the residual of the Au2 components. Specifically, a multivariate linear regression analysis indicates the strong correlation of the oxidation potential of Au6, Au8, Au23, and Au25 clusters with the HOMO energy, the number of Au atoms, and cluster charge state. The main conclusions [e.g., oxidation-induced Au(corner)-Au(core) bond activation, easy 1,2-P transfer steps, etc.] of this study might be widely applicable in improving our understanding of the mechanism of other cluster-conversion reactions.

Mechanistic insights into Ag+ induced size-growth from [Au6(DPPP)4]2+ to [Au7(DPPP)4]2+ clusters.

The size conversion of atomically precise metal nanoclusters lays the foundation to elucidate the inherent structure-activity correlations on the nanometer scale. Herein, the mechanism of the Ag+-induced size growth from [Au6(dppp)4]2+ to [Au7(dppp)4]3+ (dppp is short for 1,3-bis(diphenylphosphino)propane) is studied via density functional theory (DFT) calculations. In the absence of extra Au sources, the one "Au+" addition was found to be regulated by the Ag+ doping induced Au-activation, i.e., the formation of formal Au(i) blocks via the Ag+ alloying processes. The Au(i) blocks could be extruded from the core structure in the formed Au-Ag alloy clusters, triggering a facile Au+ migration to the Au6 precursor to form the Au7 product. This study sheds light on the structural and stability changes of gold nanoclusters upon the addition of Ag+ and will hopefully benefit the development of more metal ion-induced size-conversion of metal nanoclusters.

Fuzzy Fault Detection for Markov Jump Systems With Partly Accessible Hidden Information: An Event-Triggered Approach.

This article addresses the design issue of fuzzy asynchronous fault detection filter (FAFDF) for a class of nonlinear Markov jump systems by an event-triggered (ET) scheme. The ET scheme can be applied to cut down the transmission times from the system to FAFDF. It is assumed that the system modes cannot be obtained synchronously by the filter, and instead, there is a detector that can measure the estimated modes of the system. The asynchronous phenomenon between the system and the filter is characterized via a hidden Markov model with partly accessible mode detection probabilities. Applying the Lyapunov function methods, sufficient conditions for the presence of FAFDF are obtained. Finally, an application of a wheeled mobile manipulator with hybrid joints is employed to clarify that the devised FAFDF can detect the faults without any incorrect alarm.

Asynchronous Fault Detection Observer for 2-D Markov Jump Systems.

In this article, the problem of the asynchronous fault detection (FD) observer design is discussed for 2-D Markov jump systems (MJSs) expressed by a Roesser model. In general, the FD observer cannot work synchronously with the system, that is, the mode of the observer varies with the mode of the system in line with some conditional transitional probabilities. For dealing with this difficult point, a hidden Markov model (HMM) is employed. Then, combining the H∞ attenuation index and H_ increscent index, a multiobjective solution to the FD problem is formed. In terms of linear matrix inequality technology, sufficient conditions are gained to guarantee the existence of the asynchronous FD. Simultaneously, an asynchronous FD algorithm is generated to acquire the optimal performance indices. Finally, a numerical example concerned with the Darboux equation is demonstrated to exhibit the soundness of the developed approach.

Dynamics in C, N, and P stoichiometry and microbial biomass following soil depth and vegetation types in low mountain and hill region of China.

Changes in soil carbon (C):nitrogen (N):phosphorus (P) stoichiometry have great significance on understand regulatory mechanism and restoration of ecosystem functions. However, the responses of C, N and P stoichiometry to soil depth and different vegetation types remains elusive. To address this problem, the study aims to explore the effects of soil depth and vegetation types on soil C, N, and P stoichiometry, and their relationships with microbial biomass in low mountain and hill region of China. The results indicated that soil SOC and TN concentrations in oak forest were markedly higher than those in grassland, and the vertical distribution of SOC and TN concentration showed an inverted triangle trend as the soil deepens. However, there was no significant change in soil TP concentration among 0-20 cm, 20-40 cm, and 40-60 cm. Soil C/N among different layers (0-20, 20-40, and 40-60 cm) is narrower fluctuation margin, and its value is basically stable within a certain range (11-14.5). Both soil C/P and N/P showed significant variability in different vegetation types, and soil N/P decreased with soil layers deepen. Both the microbial biomass C (MBC) and N (MBN) showed a decreasing trend with the increase of soil depth, and three soil layers from high to low was: oak forest > pine forest > grassland. Our results will potentially provide useful information for the vegetation restoration and forest management and great significance to enrich the scientific theory of ecological stoichiometry.

Effects of irrigation and nitrogen on chlorophyll content, dry matter and nitrogen accumulation in sugar beet (Beta vulgaris L.).

A 2-year field experiment was conducted to analyze the growth conditions, physical features, yield, and nitrogen use efficiency (NUE) of sugar-beet under limited irrigation conditions in northeast of China. A cultivar H003 was used as plant materials; six treatments (C1-C6) were included: C1, no nitrogen applied, rain-fed; C2, nitrogen (120.00 kg ha-1), rain-fed; C3, no nitrogen applied, hole irrigation for seeding; C4, nitrogen (120.00 kg ha-1), hole irrigation for seeding; C5, no nitrogen applied, hole irrigation for seeding; and C6, nitrogen (120.00 kg ha-1), hole irrigation for seeding, and irrigation at foliage rapid growth stage. The irrigation supply was only 500 mL/plant once. Results showed C6 showed the highest chlorophyll content, dry matter accumulation, yield, etc. and had the best NUE among all the treatments. In conclusion, under the routine fertilization conditions of northeast of China, the cultivation measure of hole irrigation 500 mL/plant for seeding combined with irrigation 500 mL/plant at foliage rapid growth stage greatly improved sugar-beet yield and NUE.

New atomically precise M1Ag21 (M = Au/Ag) nanoclusters as excellent oxygen reduction reaction catalysts.

By introducing 1,1'-bis-(diphenylphosphino)ferrocene (dppf) as an activating ligand, two novel nanoclusters, M1Ag21 (M = Au/Ag), have been controllably synthesized and structurally characterized. The atomically precise structures of the M1Ag21 nanoclusters were determined by SCXC and further confirmed by ESI-TOF-MS, TGA, XPS, DPV, and FT-IR measurements. The M1Ag21 nanoclusters supported on activated carbon (C) are exploited as efficient oxygen reduction reaction (ORR) catalysts in alkaline solutions. Density functional theory (DFT) calculations verify that the catalytic activities of the two cluster-based systems originate from the significant ensemble synergy effect between the M13 kernel and dppf ligand in M1Ag21. This work sheds lights on the preparation of cluster-based electrocatalysts and other catalysts that are activated and modified by peripheral ligands.