Metabolic Labeling of Peptidoglycan with NIR-II Dye Enables in vivo Imaging of Gut Microbiota.

Deepening our understanding of mammalian gut microbiota has been greatly hampered by the lack of a facile, real-time and in vivo bacterial imaging method. To address this unmet need in microbial visualization, we herein report the development of a second near-infrared (NIR-II)-based method for in vivo imaging of gut bacteria. Using D-propargylglycine in gavage and then click reaction with an azide-containing NIR-II dye, gut microbiota of a donor mouse was strongly labeled with NIR-II fluorescence on their peptidoglycan. The bacteria could be readily visualized in recipient mouse gut with high spatial resolution and deep tissue penetration under NIR irradiation. We then adopted this chemical strategy to image different bacterial species, which expanded its applicability in microbiology. Moreover, by employing this method, we found that the biogeography of gut microbiota was dramatically affected by host’s gastrointestinal motilities. The NIR-II-based metabolic labeling strategy reported here, to our knowledge, provides the first protocol for facile in vivo visualization of gut microbiota within deep tissues, and offers an instrumental tool for deciphering the complex biology of these gut "dark matters"

Earliest Triassic microbialites in the South China Block and other areas; controls on their growth and distribution

Earliest Triassic microbialites (ETMs) and inorganic carbonate crystal fans formed after the end-Permian mass extinction (ca. 251.4 Ma) within the basal Triassic Hindeodus parvus conodont zone. ETMs are distinguished from rarer, and more regional, subsequent Triassic microbialites. Large differences in ETMs between northern and southern areas of the South China block suggest geographic provinces, and ETMs are most abundant throughout the equatorial Tethys Ocean with further geographic variation. ETMs occur in shallow-marine shelves in a superanoxic stratified ocean and form the only widespread Phanerozoic microbialites with structures similar to those of the Cambro-Ordovician, and briefly after the latest Ordovician, Late Silurian and Late Devonian extinctions. ETMs disappeared long before the mid-Triassic biotic recovery, but it is not clear why, if they are interpreted as disaster taxa. In general, ETM occurrence suggests that microbially mediated calcification occurred where upwelled carbonate-rich anoxic waters mixed with warm aerated surface waters, forming regional dysoxia, so that extreme carbonate supersaturation and dysoxic conditions were both required for their growth. Long-term oceanic and atmospheric changes may have contributed to a trigger for ETM formation. In equatorial western Pangea, the earliest microbialites are late Early Triassic, but it is possible that ETMs could exist in western Pangea, if well-preserved earliest Triassic facies are discovered in future work

An adaptive critic approach to event-triggered robust control of nonlinear systems with unmatched uncertainties

In this paper, we develop a novel event-triggered robust control strategy for continuous-time nonlinear systems with unmatched uncertainties. First, we build a relationship to show that the event-triggered robust control can be obtained by solving an event-triggered nonlinear optimal control problem of the auxiliary system. Then, within the framework of reinforcement learning, we propose an adaptive critic approach to solve the event-triggered nonlinear optimal control problem. Unlike typical actor-critic dual approximators used in reinforcement learning, we employ a unique critic approximator to derive the solution of the event-triggered Hamilton-Jacobi-Bellman equation arising in the nonlinear optimal control problem. The critic approximator is updated via the gradient descent method, and the persistence of excitation condition is necessary. Meanwhile, under a newly proposed event-triggering condition, we prove that the developed critic approximator update rule guarantees all signals in the auxiliary closed-loop system to be uniformly ultimately bounded. Moreover, we demonstrate that the obtained event-triggered optimal control can ensure the original system to be stable in the sense of uniform ultimate boundedness. Finally, a F-16 aircraft plant and a nonlinear system are provided to validate the present event-triggered robust control scheme

Reinforcement learning for robust adaptive control of partially unknown nonlinear systems subject to unmatched uncertainties

This paper proposes a novel robust adaptive control strategy for partially unknown continuous-time nonlinear systems subject to unmatched uncertainties. Initially, the robust nonlinear control problem is converted into a nonlinear optimal control problem by constructing an appropriate value function for the auxiliary system. After that, within the framework of reinforcement learning, an identifier-critic architecture is developed. The presented architecture uses two neural networks: the identifier neural network (INN) which aims at estimating the unknown internal dynamics and the critic neural network (CNN) which tends to derive the approximate solution of the Hamilton-Jacobi-Bellman equation arising in the obtained optimal control problem. The INN is updated by using both the back-propagation algorithm and the e-modification technique. Meanwhile, the CNN is updated via the modified gradient descent method, which uses historical and current state data simultaneously. Based on the classic Lyapunov technique, all the signals in the closed-loop auxiliary system are proved to be uniformly ultimately bounded. Moreover, the original system is kept asymptotically stable under the obtained approximate optimal control. Finally, two illustrative examples, including the F-16 aircraft plant, are provided to demonstrate the effectiveness of the developed method

Continuous-Time Distributed Policy Iteration for Multicontroller Nonlinear Systems

In this article, a novel distributed policy iteration algorithm is established for infinite horizon optimal control problems of continuous-time nonlinear systems. In each iteration of the developed distributed policy iteration algorithm, only one controller\u27s control law is updated and the other controllers\u27 control laws remain unchanged. The main contribution of the present algorithm is to improve the iterative control law one by one, instead of updating all the control laws in each iteration of the traditional policy iteration algorithms, which effectively releases the computational burden in each iteration. The properties of distributed policy iteration algorithm for continuous-time nonlinear systems are analyzed. The admissibility of the present methods has also been analyzed. Monotonicity, convergence, and optimality have been discussed, which show that the iterative value function is nonincreasingly convergent to the solution of the Hamilton-Jacobi-Bellman equation. Finally, numerical simulations are conducted to illustrate the effectiveness of the proposed method

Adaptive dynamic programming with applications in optimal control

This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP approach which is then extended to other branches of control theory including decentralized control, robust and guaranteed cost control, and game theory. In the last part of the book the real-world significance of ADP theory is presented, focusing on three application examples developed from the authors’ work: • renewable energy scheduling for smart power grids; • coal gasification processes; and • water–gas shift reactions. Researchers studying intelligent control methods and practitioners looking to apply them in the chemical-process and power-supply industries will find much to interest them in this thorough treatment of an advanced approach to control. Advances in Industrial Control aims to report and encourage the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control

IGF2BP2 acts as a m6A modification regulator in laryngeal squamous cell carcinoma through facilitating CDK6 mRNA stabilization

Abstract Laryngeal squamous cell carcinoma (LSCC) is one of the most commonly seen cancers in the head and neck region with increasing morbidity and mortality globally. N6-methyladenosine (m6A) modification plays a critical role in the carcinogenesis of LSCC. In this study, two datasets from online database were analyzed for differentially expressed genes (DEGs) between LSCC and normal samples. Furthermore, we carried out a series of experiments, including hematoxylin & eosin staining, immunohistochemical (IHC) staining, CCK-8, colony formation, transwell, flow cytometry, xenograft tumor model assays, actinomycin D assay, cycloheximide (CHX) assay, methylated m6A RNA immunoprecipitation (Me-RIP), RNA immunoprecipitation (RIP) assay, to verify the relevant findings in vivo and in vitro. Insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2) was identified as an up-regulated m6A regulator in LSCC samples. Lower IGF2BP2 expression was linked to higher survival probability in LSCC and other head and neck squamous cell carcinoma patients. In LSCC cells, IGF2BP2 knockdown attenuated cancer cell aggressiveness, possibly through modulating cell cycle arrest. In the xenograft tumor model derived from IGF2BP2 knocked-down LSCC cells, IGF2BP2 knockdown inhibited tumor growth. IGF2BP2 up-regulated CDK6 expression through facilitating the stability of CDK6 mRNA and protein. CDK6 knockdown caused no changes in IGF2BP2 expression, but partially eliminated the promotive effects of IGF2BP2 overexpression on LSCC cells’ aggressiveness. Overexpressed IGF2BP2 in LSCC serves as an oncogenic factor, promoting LSCC cell proliferation and invasion in vitro and tumor growth in a xenograft tumor model in vivo through facilitating CDK6 mRNA stabilization

Post-Warranty Replacement Models for the Product under a Hybrid Warranty

In this article, by considering both a limited number of failure replacements and a limited number of random working cycles as warranty terms, a hybrid warranty (HW) is designed from the manufacturer’s point of view to warrant the product that does successive projects at random working cycles. The warranty cost produced by HW is derived and analyzed. By defining that HW warrants the product, two types of post-warranty replacement models are investigated from the consumer’s point of view to ensure the reliability of the product through HW, i.e., customized post-warranty replacement and uniform post-warranty replacement. Depreciation expense is integrated into each post-warranty replacement. The expected cost rate model is presented for each post-warranty replacement and some special cases are obtained by setting parameters in the expected cost rate. Finally, sensitivities on both HW and post-warranty replacements are analyzed in numerical experiments. It is shown that when a limited number of failure replacements or/and a limited number of random working cycles are introduced to a warranty, the warranty cost can be reduced; and the performance of the uniform post-warranty replacement is superior to the customized post-warranty replacement