Alternative Splicing of TaGS3 Differentially Regulates Grain Weight and Size in Bread Wheat.

The heterotrimeric G-protein mediates growth and development by perceiving and transmitting signals in multiple organisms. Alternative splicing (AS), a vital process for regulating gene expression at the post-transcriptional level, plays a significant role in plant adaptation and evolution. Here, we identified five splicing variants of Gγ subunit gene TaGS3 (TaGS3.1 to TaGS3.5), which showed expression divergence during wheat polyploidization, and differential function in grain weight and size determination. TaGS3.1 overexpression significantly reduced grain weight by 5.89% and grain length by 5.04%, while TaGS3.2-3.4 overexpression did not significantly alter grain size compared to wild type. Overexpressing TaGS3.5 significantly increased the grain weight by 5.70% and grain length by 4.30%. Biochemical assays revealed that TaGS3 isoforms (TaGS3.1-3.4) with an intact OSR domain interact with WGB1 to form active Gßγ heterodimers that further interact with WGA1 to form inactive Gαßγ heterotrimers. Truncated isoforms TaGS3.2-3.4 , which lack the C-terminal Cys-rich region but have enhanced binding affinity to WGB1, antagonistically compete with TaGS3.1 to bind WGB1, while TaGS3.5 with an incomplete OSR domain does not interact with WGB1. Taking these observations together, we proposed that TaGS3 differentially regulates grain size via AS, providing a strategy by which the grain size is fine-tuned and regulated at the post-transcriptional level.

Case report: A case study of neoadjuvant immunochemotherapy for locally advanced esophageal squamous carcinoma.

In locally advanced esophageal cancer, the controversy over the two traditional treatment modalities, neoadjuvant radiotherapy and neoadjuvant chemotherapy, has been unending and also challenged by the addition of neoadjuvant immunotherapy. Neoadjuvant immunotherapy has led to an increasing diversity of neoadjuvant combination treatment modalities, among which neoadjuvant immunochemotherapy has emerged, with current clinical studies initially demonstrating its efficacy and safety. We report a case of a patient with locally advanced esophageal cancer who underwent two cycles of neoadjuvant immunochemotherapy and successful surgery and achieved a pathological complete response (pCR). A 73-year-old elderly female patient presented with progressive dysphagia for more than 1 month with an Eastern Cooperative Oncology Group (ECOG) score of 1. After completing gastroscopy + pathological biopsy, chest enhanced CT, barium esophageal meal, PET-CT, and other related examinations, the clinical diagnosis was thoracic segmental esophageal poorly differentiated squamous carcinoma cT2N2M0 stage III. After a multidisciplinary discussion of the comprehensive treatment plan, two cycles of neoadjuvant therapy were given on February 16, 2023, and March 9, 2023, and the treatment plan was as follows: cisplatin 30 mg d1-3 + albumin paclitaxel 200 mg d1 and 100 mg d8 + sintilimab 200 mg d4, q3w. After the neoadjuvant therapy, the patient underwent an imaging examination. The chest enhanced CT suggested that the lesion range was significantly reduced compared with the previous scan, and mediastinal lymph nodes were partially reduced. Then, thoracoscopic radical esophageal cancer surgery was performed on April 23, 2023. pCR was achieved by pathological evaluation, and the postoperative diagnosis was thoracic segmental esophageal hypofractionated squamous carcinoma ypT0N0M0. Two cycles of adjuvant immunochemotherapy were performed after surgery on May 30, 2023, and June 21, 2023, and the regimen was as follows: cisplatin 30 mg d1-3 + albumin paclitaxel 200 mg d1 and 100 mg d8 + sindilizumab 200 mg d4, q3w. As of the latest review on March 20, 2024, the patient was not seen to have any significant postoperative complications and remains in a state of complete response (CR). Neoadjuvant immunochemotherapy has positive significance for the treatment of patients with locally advanced esophageal cancer. Whether neoadjuvant immunochemotherapy can replace neoadjuvant synchronous radiotherapy is a future direction of research, which needs to be further verified by more reliable clinical trials.

Improving Tracking Accuracy for Repetitive Learning Systems by High-Order Extended State Observers.

For systems executing repetitive tasks, how to realize the perfect tracking objective is generally desirable, for which an effective method called "iterative learning control (ILC)" emerges thanks to the incorporation of the repetitive execution of systems into an ILC design framework. However, nonrepetitive (iteration-varying) uncertainties are often inevitable in practice and greatly degrade the tracking accuracy of ILC, which has not been treated well, regardless of considerable robust ILC results. This motivates this article to develop a new design method to improve the tracking accuracy of ILC by adopting a high-order extended state observer (ESO) to address ill effects of nonrepetitive uncertainties and uncertain system models. With the designed ESO-based ILC, the robust tracking of any desired trajectory can be achieved such that the tracking error can be decreased to vary in a small bound depending continuously on the bounds of high-order variations of nonrepetitive uncertainties with respect to the iteration. It makes the tracking accuracy of ILC possible to be regulated through the design of ESO, of which the validity is demonstrated by including a simulation example.

Iterative Rectifying Methods for Nonrepetitive Continuous-Time Learning Control Systems.

To implement iterative learning control (ILC), one of the most fundamental hypotheses is the strict repetitiveness (i.e., iteration-independence) of the controlled systems, especially of their plant models. This hypothesis, however, results in difficulties of developing theoretic analysis methods and promoting practical applications for ILC, especially in the presence of continuous-time systems, which is the motivation of the current paper to cope with robust tracking problems of continuous-time ILC systems subject to nonrepetitive (i.e., iteration-dependent) uncertainties. Based on integrating an iterative rectifying mechanism, continuous-time ILC can effectively address the ill effects of the multiple nonrepetitive uncertainties that arise from the system models, initial states, load and measurement disturbances, and desired references. Furthermore, a robust convergence analysis method is presented for continuous-time ILC by combining a contraction mapping-based method and a system equivalence transformation method. It is disclosed that regardless of continuous-time ILC systems with zero or nonzero system relative degrees, the robust tracking tasks in the presence of nonrepetitive uncertainties can be accomplished, together with the boundedness of all the system trajectories being ensured. Two examples are included to verify the validity of our robust tracking results for nonrepetitive continuous-time ILC systems.

Distributed Control Problems on Signed Networks Under Mixed Static and Dynamic Protocols.

This article aims at exploring the dynamic behaviors of signed networks under the mixed static and dynamic control protocols, which reflect the existence of two classes of communication channels. An extended leader-follower framework admitting multiple dynamic leaders is established to identify the roles of all nodes in signed networks, depending on the union of two related signed digraphs. It is shown that bipartite containment tracking is achieved for signed networks despite any topology conditions. To be specific, every leader group realizes modulus consensus and the leaders dominate the dynamic evolutions of signed networks such that all followers converge within the bounded zone spanned by the leaders' converged states and their symmetric states. Furthermore, conditions on the zero convergence of dynamic control inputs are exploited, together with those on the (interval) bipartite consensus of signed networks. Simulation examples are given to demonstrate the convergence behaviors of signed networks with respect to the mixed static and dynamic control protocols.

Hybrid triggering design for global attitude synchronization of networked rigid bodies.

This paper is devoted to dealing with the problem of global attitude synchronization for quaternion-based multiple rigid bodies, regardless of the general directed topologies of networks and arbitrary initial orientations of rigid bodies. A novel canonical quaternion is constructed to represent all physical attitudes of rigid bodies such that the pseudo-synchronization of their quaternion representations (namely, the quaternions' vector parts of all rigid bodies reach agreement on some identical value, whereas their scalar parts do not) can be precluded. Moreover, to reduce unnecessary communication requirements of rigid bodies, a hybrid triggering mechanism involving both the time regulation and neighbors' non-real-time information is proposed, with which a distributed protocol is developed by leveraging the constructed canonical quaternion. It is shown that the presented protocol for rigid bodies over directed networks can simultaneously realize the global attitude synchronization and naturally exclude the Zeno behavior. In addition, these observations are also validated via the application of our hybrid triggering protocol to networked spacecraft.

Accurate integrated position measurement system for mobile applications in GPS-denied coal mine.

The automatic positioning of underground mobile applications plays a crucial role in enabling intelligent coal mining. However, due to the diverse kinematics and dynamics of these applications, various positioning methods have been proposed to match different targets. Nonetheless, the accuracy and applicability of these methods still fall short of meeting the requirements for field applications. Based on the vibration characteristics of underground mobile devices, a multi-sensor fusion positioning system is developed to enhance the accuracy of positioning in long and narrow global positioning system denied (GPS-denied) underground coal mine roadways. The system combines inertial navigation (INS), odometer, and ultra wide band (UWB) technologies through extended Kalman filter (EKF) and unscented Kalman filter (UKF). This approach enables accurate positioning by recognizing target carrier vibrations and facilitating fast conversion between multi-sensor fusion modes. The proposed system is tested on both a small unmanned mine vehicle (UMV) and a large roadheader, demonstrating that UKF enhances stability for roadheaders with strong nonlinear vibrations while EKF is more suitable for flexible UMVs. Detailed results confirm that the proposed system achieves an accuracy level of 0.15 m, meeting most coal mine application requirements.

Design and Analysis of Data-Driven Learning Control: An Optimization-Based Approach.

Learning to perform perfect tracking tasks based on measurement data is desirable in the controller design of systems operating repetitively. This motivates this article to seek an optimization-based design and analysis approach for data-driven learning control systems by focusing on iterative learning control (ILC) of repetitive systems with unknown nonlinear time-varying dynamics. It is shown that perfect output tracking can be realized with updating inputs, where no explicit model knowledge but only measured input-output data are leveraged. In particular, adaptive updating strategies are proposed to obtain parameter estimations of nonlinearities. A double-dynamics analysis approach is applied to establish ILC convergence, together with boundedness of input, output, and estimated parameters, which benefits from employing properties of nonnegative matrices. Simulations are implemented to verify the validity of our optimization-based adaptive ILC.

Nonsynchronous Model Reduction for Uncertain 2-D Markov Jump Systems.

Mode information is of great significance when investigating the Markov jump systems (MJSs). However, it is common in practical scenarios that the mode information is not completely accessible, which probably induces nonsynchronization problems. Taking this into consideration, in this article, we study nonsynchronous H∞ model order reduction for 2-D MJSs with model uncertainty. The considered 2-D system and reduced-order model are characterized by the Roesser model. The nonsynchronization phenomenon between the original system and the reduced-order model is dealt with under the framework of the hidden Markov model. By appropriately selecting the Lyapunov function, the asymptotic mean-square stability and the H∞ performance of the error system are analyzed, and sufficient conditions are proposed. Based on this, an efficient design method for nonsynchronous model order reduction is further proposed with the help of a projection lemma. Finally, the correctness and effectiveness of the designed reduced-order model are verified through some simulations.

Distributed Control of Time-Varying Signed Networks: Theories and Applications.

Signed networks admitting antagonistic interactions among agents may polarize, cluster, or fluctuate in the presence of time-varying communication topologies. Whether and how signed networks can be stabilized regardless of their sign patterns is one of the fundamental problems in the network system control areas. To address this problem, this paper targets at presenting a self-appraisal mechanism in the protocol of each agent, for which a notion of diagonal dominance degree is proposed to represent the dominant role of agent's self-appraisal over external impacts from all other agents. Selection conditions on diagonal dominance degrees are explored such that signed networks in the presence of directed time-varying topologies can be ensured to achieve the uniform asymptotic stability despite any sign patterns. Further, the established stability results can be applied to achieve bipartite consensus tracking of time-varying signed networks and realize state-feedback stabilization of time-varying systems. Simulations are implemented to verify our uniform asymptotic stability results for directed time-varying signed networks.

Transient Bipartite Synchronization for Cooperative-Antagonistic Multiagent Systems With Switching Topologies.

This article aims at addressing the transient bipartite synchronization problem for cooperative-antagonistic multiagent systems with switching topologies. A distributed iterative learning control protocol is presented for agents by resorting to the local information from their neighbor agents. Through learning from other agents, the control input of each agent is updated iteratively such that the transient bipartite synchronization can be achieved over the targeted finite horizon under the simultaneously structurally balanced signed digraph. To be specific, all agents finally have the same output moduli at each time instant over the desired finite-time interval, which overcomes the influences caused by the antagonisms among agents and topology nonrepetitiveness along the iteration axis. As a counterpart, it is revealed that the stability can be achieved over the targeted finite horizon in the presence of a constantly structurally unbalanced signed digraph. Simulation examples are carried out to demonstrate the effectiveness of the distributed learning results developed among multiple agents.

Fully Distributed Synchronization of Complex Networks With Adaptive Coupling Strengths.

This article considers the fully distributed leaderless synchronization in a complex network by only utilizing local neighboring information to design and tune the coupling strength of each node such that the synchronization problem can be solved without involving any global information of the network. For an undirected network, a fully distributed synchronization algorithm is presented to adjust the coupling strength of each node based on a simple adaptive law. When the topology of a network is directed, two different types of adaptive algorithms are developed to achieve synchronization in a fully distributed manner, where the coupling strength of each node is designed to be either the sum or product of two non-negative scalar functions. The fully distributed leaderless synchronization of a directed network is investigated in a leader-follower framework, where the leader subnetwork is analyzed by using the techniques from constrained Rayleigh quotients and the follower subnetwork is addressed by employing the properties of nonsingular M -matrices. Simulations are given to illustrate the theoretical results.

Transcriptomic analysis reveals the contribution of QMrl-7B to wheat root growth and development.

Roots are the major organs for water and nutrient acquisition and substantially affect plant growth, development and reproduction. Improvements to root system architecture are highly important for the increased yield potential of bread wheat. QMrl-7B, a major stable quantitative trait locus (QTL) that controls maximum root length (MRL), essentially contributes to an improved root system in wheat. To further analyze the biological functions of QMrl-7B in root development, two sets of Triticum aestivum near-isogenic lines (NILs), one with superior QMrl-7B alleles from cultivar Kenong 9204 (KN9204) named NILKN9204 and another with inferior QMrl-7B alleles from cultivar Jing 411 (J411) named NILJ411, were subjected to transcriptomic analysis. Among all the mapped genes analyzed, 4871 genes were identified as being differentially expressed between the pairwise NILs under different nitrogen (N) conditions, with 3543 genes expressed under normal-nitrogen (NN) condition and 2689 genes expressed under low-nitrogen (LN) condition. These genes encode proteins that mainly include N O 3 - transporters, phytohormone signaling components and transcription factors (TFs), indicating the presence of a complex regulatory network involved in root determination. In addition, among the 13524 LN-induced differentially expressed genes (DEGs) detected in this study, 4308 and 2463 were specifically expressed in the NILKN9204 and NILJ411, respectively. These DEGs reflect different responses of the two sets of NILs to varying N supplies, which likely involve LN-induced root growth. These results explain the better-developed root system and increased root vitality conferred by the superior alleles of QMrl-7B and provide a deeper understanding of the genetic underpinnings of root traits, pointing to a valuable locus suitable for future breeding efforts for sustainable agriculture.

Comparative genomic and transcriptomic analyses uncover the molecular basis of high nitrogen-use efficiency in the wheat cultivar Kenong 9204.

Studying the regulatory mechanisms that drive nitrogen-use efficiency (NUE) in crops is important for sustainable agriculture and environmental protection. In this study, we generated a high-quality genome assembly for the high-NUE wheat cultivar Kenong 9204 and systematically analyzed genes related to nitrogen uptake and metabolism. By comparative analyses, we found that the high-affinity nitrate transporter gene family had expanded in Triticeae. Further studies showed that subsequent functional differentiation endowed the expanded family members with saline inducibility, providing a genetic basis for improving the adaptability of wheat to nitrogen deficiency in various habitats. To explore the genetic and molecular mechanisms of high NUE, we compared genomic and transcriptomic data from the high-NUE cultivar Kenong 9204 (KN9204) and the low-NUE cultivar Jing 411 and quantified their nitrogen accumulation under high- and low-nitrogen conditions. Compared with Jing 411, KN9204 absorbed significantly more nitrogen at the reproductive stage after shooting and accumulated it in the shoots and seeds. Transcriptome data analysis revealed that nitrogen deficiency clearly suppressed the expression of genes related to cell division in the young spike of Jing 411, whereas this suppression of gene expression was much lower in KN9204. In addition, KN9204 maintained relatively high expression of NPF genes for a longer time than Jing 411 during seed maturity. Physiological and transcriptome data revealed that KN9204 was more tolerant of nitrogen deficiency than Jing 411, especially at the reproductive stage. The high NUE of KN9204 is an integrated effect controlled at different levels. Taken together, our data provide new insights into the molecular mechanisms of NUE and important gene resources for improving wheat cultivars with a higher NUE trait.

Convergence Analysis of Robust Iterative Learning Control Against Nonrepetitive Uncertainties: System Equivalence Transformation.

This article is concerned with the robust convergence analysis of iterative learning control (ILC) against nonrepetitive uncertainties, where the contradiction between convergence conditions for the output tracking error and the input signal (or error) is addressed. A system equivalence transformation (SET) is proposed for robust ILC such that given any desired reference trajectories, the output tracking problems for general nonsquare multi-input, multi-output (MIMO) systems can be equivalently transformed into those for the specific class of square MIMO systems with the same input and output numbers. As a benefit of SET, a unified condition is only needed to guarantee both the uniform boundedness of all system signals and the robust convergence of the output tracking error, which avoids causing the condition contradiction problem in implementing the double-dynamics analysis approach to ILC. Simulation examples are included to demonstrate the validity of our established robust ILC results.

Further Results for Edge Convergence of Directed Signed Networks.

The edge convergence problems have been explored for directed signed networks recently in 2019 by Du, Ma, and Meng, of which the analysis results, however, depend heavily on the strong connectivity of the network topologies. The question asked in this article is: whether and how can the edge convergence be achieved when the strong connectivity is not satisfied? The answer for the case of spanning tree is given. It is shown that if a signed network is either structurally balanced or r-structurally unbalanced, then the edge state can be ensured to converge to a constant vector. In contrast, if a signed network is both structurally unbalanced and r-structurally balanced, then its edge state does not converge to a constant vector any longer, but to a time-varying vector trajectory with a constant speed. Further, the dynamic behavior results of edges can be derived to address the node convergence problems of signed networks. The simulation examples are provided to illustrate the validity of the established edge convergence results.

Distributed Controller Design and Analysis of Second-Order Signed Networks With Communication Delays.

This article concentrates on dealing with distributed control problems for second-order signed networks subject to not only cooperative but also antagonistic interactions. A distributed control protocol is proposed based on the nearest neighbor rules, with which necessary and sufficient conditions are developed for consensus of second-order signed networks whose communication topologies are described by strongly connected signed digraphs. Besides, another distributed control protocol in the presence of a communication delay is designed, for which a time margin of the delay can be determined simultaneously. It is shown that under the delay margin condition, necessary and sufficient consensus results can be derived even though second-order signed networks with a communication delay are considered. Simulation examples are included to illustrate the validity of our established consensus results of second-order signed networks.

Adaptive robust precision motion control of single PAM actuated servo systems with non-local memory hysteresis force compensation.

An adaptive robust controller with non-local memory hysteresis force compensation is investigated for the precision tracking control of pneumatic artificial muscle (PAM). The proposed controller presents a two-layer cascade structure, and each layer has an adaptive law part and a robust control law part. A modified operator based Prandtl-Ishlinskii (PI) model is employed in the development of the robust control algorithm with the hysteresis feedback linearization compensation. Moreover, in the robust control law part, the problem of unbounded uncertain nonlinearities introduced by the hysteresis force term is addressed by applying an on-line monitoring method. In the adaptive law part, model parameters including weights of the modified operator are updated online by the recursive least squares estimation (RLSE) method, and then the effect of the hysteresis non-local memory characteristic is further attenuated. The tracking error is guaranteed to converge to a small residual set. Comparative experimental results demonstrate the significance of the non-local memory hysteresis force compensation, then, a desired precision can be guaranteed.

QMrl-7B Enhances Root System, Biomass, Nitrogen Accumulation and Yield in Bread Wheat.

Genetic improvement of root systems is an efficient approach to improve yield potential and nitrogen use efficiency (NUE) of crops. QMrl-7B was a major stable quantitative trait locus (QTL) controlling the maximum root length in wheat (Triticum aestivum L). Two types of near isogenic lines (A-NILs with superior and B-NILs with inferior alleles) were used to specify the effects of QMrl-7B on root, grain output and nitrogen-related traits under both low nitrogen (LN) and high nitrogen (HN) environments. Trials in two consecutive growing seasons showed that the root traits, including root length (RL), root area (RA) and root dry weight (RDW), of the A-NILs were higher than those of the B-NILs at seedling stage (SS) before winter, jointing stage (JS), 10 days post anthesis (PA10) and maturity (MS), respectively. Under the LN environment, in particular, all the root traits showed significant differences between the two types of NILs (p < 0.05). In contrast, there were no critical differences in aerial biomass and aerial N accumulation (ANA) between the two types of NILs at SS and JS stages. At PA10 stage, the aerial biomass and ANA of the A-NILs were significantly higher than those of the B-NILs under both LN and HN environments (p < 0.05). At MS stage, the A-NILs also exhibited significantly higher thousand-grain weight (TGW), plot grain yield, harvest index (HI), grain N accumulation (GNA), nitrogen harvest index (NHI) and nitrogen partial factor productivity (NPFP) than the B-NILs under the corresponding environments (p < 0.05). In summary, the QMrl-7B A-NILs manifested larger root systems compared to the B-NILs which is favorable to N uptake and accumulation, and eventually enhanced grain production. This research provides valuable information for genetic improvement of root traits and breeding elite wheat varieties with high yield potential and NPFP.

Convergence Analysis of Saturated Iterative Learning Control Systems With Locally Lipschitz Nonlinearities.

In this article, the robust trajectory tracking problem of iterative learning control (ILC) for uncertain nonlinear systems is considered, and the effects from locally Lipschitz nonlinearities, input saturations, and nonzero system relative degrees are treated. A saturated ILC algorithm is given, with the convergence analysis exploited using a composite energy function-based approach. It is shown that the tracking error can be guaranteed to converge both pointwisely and uniformly. Furthermore, the input updating signal can be ensured to eventually satisfy the input saturation requirements with increasing iterations. Two examples are given to demonstrate the validity of saturated ILC for systems with the relative degree of one, input saturation, and locally Lipschitz nonlinearity.