Search

JTE-607 is an anticancer and anti-inflammatory compound and its active form, compound 2, directly binds to and inhibits CPSF73, the endonuclease for the cleavage step in pre-messenger RNA (pre-mRNA) 3' processing. Surprisingly, compound 2-mediated inhibition of pre-mRNA cleavage is sequence specific and the drug sensitivity is predominantly determined by sequences flanking the cleavage site (CS). Using massively parallel in vitro assays, we identified key sequence features that determine drug sensitivity. We trained a machine learning model that can predict poly(A) site (PAS) relative sensitivity to compound 2 and provide the molecular basis for understanding the impact of JTE-607 on PAS selection and transcription termination genome wide. We propose that CPSF73 and associated factors bind to the CS region in a sequence-dependent manner and the interaction affinity determines compound 2 sensitivity. These results have not only elucidated the mechanism of action of JTE-607, but also unveiled an evolutionarily conserved sequence specificity of the mRNA 3' processing machinery.

This article proposes an adaptive robust formation control scheme for the connected and autonomous vehicle (CAV) swarm system by utilizing swarm property, diffeomorphism transformation, and constraint following. The control design is processed by starting from a 2-D dynamics model with (possibly fast) time varying but bounded uncertainty. The uncertainty bounds are unknown. For compact formation, the CAV system is treated as an artificial swarm system, for which the ideal swarm performance is taken as a desired constraint. By this, formation control is converted into a problem of constraint following and then a performance measure β is defined as the control object to evaluate the constraint following error. For collision avoidance, a diffeomorphism transformation on space measure between two vehicles is creatively performed, by which the space measure is positive restricted. For uncertainty handling, an adaptive robust control scheme is proposed to render the β -measure to be uniformly bounded and uniformly ultimately bounded, that is, drive the controlled (CAV) swarm system to follow the desired constraint approximatively. As a result, the system can achieve the ideal swarm performance; thereout, compact formation is realized, regardless of the uncertainty. The main contribution of this article is exploring a 2-D formation control scheme for (CAV) swarm system under the consideration of collision avoidance and time-varying uncertainty.

This article addresses a cooperative game-oriented optimal constraint-following problem for fuzzy mechanical systems. The state of the concerned system is affected by possibly (fast) time-varying uncertainty. The fuzzy set theory is adopted to describe such uncertainty. The task is to drive the system to obey a set of prescribed constraints optimally. Since the control objective may be changing along with the system uncertainty, a time-varying β-measure is defined to gauge the constraint-following error; based on which, an adaptive robust control scheme with two tunable parameters is then proposed to render it to be uniform boundedness and uniform ultimate boundedness. For the seeking of the optimal design parameters, two cost functions, each of which is dominated by one tunable parameter, are developed with the fuzzy information, and thereout a two-player cooperative game is formulated. Finally, the optimal design problem is successfully solved: with the existence, uniqueness, and analytical expression of the Pareto optimality.

Pointing tracking control of marching turret-barrel system is one of the important topics in exploration of intelligent ground combat platform. This paper focuses on an adaptive robust control scheme for pointing tracking of marching turret-barrel system driven by a motor and an electric cylinder. Three types of possibly fast time-varying but bounded uncertainty are considered: system modeling error, external disturbance and road excitation. The uncertainty bounds are not necessary to be known. First, the pointing tracking system is constructed as a coupled, nonlinear and uncertain dynamical system with two interconnected (horizontal and vertical) subsystems. Second, a tracking error e is defined as a gauge of control objective, and then the dynamical equation of the pointing tracking system is built in state-space form. Third, for uncertainty control, a comprehensive uncertainty bound α is derived to measure the most conservative influence of the uncertainty, and then an adaptive law is proposed to evaluate it in real time. Finally, for pointing tracking control, an adaptive robust control is proposed to render the pointing tracking system to be practically stable; thereout, the objective of pointing tracking is achieved. This work should be among the first ever endeavours to cast all the coupling, nonlinearity and bound-unknown uncertainty into the pointing tracking framework of marching turret-barrel system.

This paper proposes an optimal parameter design of control scheme for mechanical systems by adopting the Stackelberg game theory. The goal of the control is to drive the mechanical system to follow the prescribed constraints. The system uncertainty is (possibly fast) time-varying and bounded. A β-measure is defined to gauge the performance. A robust control is proposed to render the β-measure uniformly ultimately bounded. This control scheme is based on feasible design parameters (i.e., parameters within prescribed range), and the choices of these parameters may not be unique. For optimal (unique) parameter selection, a Stackelberg game is formulated. By taking the control design parameters as the players, for each player, a cost function is built with the consideration of the performance cost, the time cost and the control cost. To follow, the Stackelberg strategy is then carried out via backward induction, which results in the choice of the optimal parameters.

RNA molecules can fold into complex structures and interact with trans-acting factors to control their biology. Recent methods have been focused on developing novel tools to measure RNA structure transcriptome-wide, but their utility to study and predict RNA-protein interactions or RNA processing has been limited thus far. Here, we extend these studies with the first transcriptome-wide mapping method for cataloging RNA solvent accessibility, icLASER. By combining solvent accessibility (icLASER) with RNA flexibility (icSHAPE) data, we efficiently predict RNA-protein interactions transcriptome-wide and catalog RNA polyadenylation sites by RNA structure alone. These studies showcase the power of designing novel chemical approaches to studying RNA biology. Further, our study exemplifies merging complementary methods to measure RNA structure inside cells and its utility for predicting transcriptome-wide interactions that are critical for control of and regulation by RNA structure. We envision such approaches can be applied to studying different cell types or cells under varying conditions, using RNA structure and footprinting to characterize cellular interactions and processing involving RNA.

Eukaryotic gene expression is extensively regulated by cellular stress and pathogen infections. We have previously shown that herpes simplex virus 1 (HSV-1) and several cellular stresses cause widespread disruption of transcription termination (DoTT) of RNA polymerase II (RNAPII) in host genes and that the viral immediate early factor ICP27 plays an important role in HSV-1-induced DoTT. Here, we show that HSV-1 infection also leads to widespread changes in alternative polyadenylation (APA) of host mRNAs. In the majority of cases, polyadenylation shifts to upstream poly(A) sites (PAS), including many intronic PAS. Mechanistically, ICP27 contributes to HSV-1-mediated APA regulation. HSV-1- and ICP27-induced activation of intronic PAS is sequence-dependent and does not involve general inhibition of U1 snRNP. HSV1-induced intronic polyadenylation is accompanied by early termination of RNAPII. HSV-1-induced mRNAs polyadenylated at intronic PAS (IPA) are exported into the cytoplasm while APA isoforms with extended 3' UTRs are sequestered in the nuclei, both preventing the expression of the full-length gene products. Finally we provide evidence that HSV-induced IPA isoforms are translated. Together with other recent studies, our results suggest that viral infection and cellular stresses induce a multi-faceted host response that includes DoTT and changes in APA profiles.

Infection by viruses, including herpes simplex virus-1 (HSV-1), and cellular stresses cause widespread disruption of transcription termination (DoTT) of RNA polymerase II (RNAPII) in host genes. However, the underlying mechanisms remain unclear. Here, we demonstrate that the HSV-1 immediate early protein ICP27 induces DoTT by directly binding to the essential mRNA 3 processing factor CPSF. It thereby induces the assembly of a dead-end 3 processing complex, blocking mRNA 3 cleavage. Remarkably, ICP27 also acts as a sequence-dependent activator of mRNA 3 processing for viral and a subset of host transcripts. Our results unravel a bimodal activity of ICP27 that plays a key role in HSV-1-induced host shutoff and identify CPSF as an important factor that mediates regulation of transcription termination. These findings have broad implications for understanding the regulation of transcription termination by other viruses, cellular stress and cancer.

(Cell 172, 106–120; January 11, 2018) Due to a production error, the original publication of this article included typographic errors in Figure 1. In that figure, four instances of “THY-1” appeared as “HY-1”. These errors have been corrected in print and online, and we apologize for any inconvenience. [Figure presented] A Serial siRNA Screen Identifies Nudt21 as a Potent Barrier to Reprogramming (corrected) [Figure presented] A Serial siRNA Screen Identifies Nudt21 as a Potent Barrier to Reprogramming (original)

Alternative mRNA processing is a critical mechanism for proteome expansion and gene regulation in higher eukaryotes. The SR family proteins play important roles in splicing regulation. Intriguingly, mammalian genomes encode many poorly characterized SR-like proteins, including subunits of the mRNA 3'-processing factor CFIm, CFIm68 and CFIm59. Here we demonstrate that CFIm functions as an enhancer-dependent activator of mRNA 3' processing. CFIm regulates global alternative polyadenylation (APA) by specifically binding and activating enhancer-containing poly(A) sites (PASs). Importantly, the CFIm activator functions are mediated by the arginine-serine repeat (RS) domains of CFIm68/59, which bind specifically to an RS-like region in the CPSF subunit Fip1, and this interaction is inhibited by CFIm68/59 hyper-phosphorylation. The remarkable functional similarities between CFIm and SR proteins suggest that interactions between RS-like domains in regulatory and core factors may provide a common activation mechanism for mRNA 3' processing, splicing, and potentially other steps in RNA metabolism.

Multiple mRNA processing steps, including splicing and 3' processing, take place in macromolecular complexes that contain many proteins and sometimes RNA molecules. A key challenge in the mRNA processing field has been to define the structure-function relationship of these sophisticated molecular machines. A prerequisite for addressing this challenge is to develop tools for purifying mRNA processing complexes in their native and intact forms that are suitable for functional and structural studies. Among many methods that have been developed, RNA affinity-based methods are most widely applied. In these methods, RNA molecules that are substrates to mRNA processing machineries are fused with an affinity tag, incubated with cellular extracts/lysates to allow for the assembly of mRNA processing complexes, and finally the assembled complexes are purified using RNA affinity tag. In this chapter, we will overview RNA affinity-based purification methods and describe in detail one such method, MS2-tagging, and its application in the purification of mRNA 3' processing complexes. Although these methods were originally developed for purifying mRNA processing complexes, they should be applicable to purification of other RNA-protein complexes as well.

To effectively suppress the effects of uncertainties including unmodeled dynamics and external disturbances in the vehicle stabilization system, a nonlinear robust control strategy based on a multilayer neural network is proposed in this paper. First, the mechanical and electrical coupling dynamics model of the vehicle stabilization system, considering model uncertainty and actuator dynamics, is refined. Second, the lumped uncertainty of the vehicle stabilization system is estimated by a multi-layer neural network and compensated by feedforward control. The high robustness of the system is ensured by constructing the sliding mode feedback control law. The proposed control method overcomes the limitations of sliding mode technology and the neural network and is naturally applied to the vehicle stabilization system, avoiding the adverse effects of high-gain feedback. Based on Lyapunov theory, it is demonstrated that the proposed controller is able to achieve the desired stability tracking performance. Finally, the effectiveness of the proposed control strategy is verified by co-simulation and comparative experiments. [ABSTRACT FROM AUTHOR]

This paper proposes an adaptive robust control scheme to deal with the uncertainty problem of unmanned combat platform. Under the constraint of the controller, the rescue vehicle aims to follow the trajectory of the reconnaissance vehicle and avoid obstacles (e.g., craters and destroyed tanks), while they eventually reach the defined target location (an accident area). First, for the control objective, the original constraints are innovatively separated into two parts: arrival constraint and tracking‐avoidance constraint. An approximate constraint‐following control substitutes for the triple problem, and the constraint‐following error is subsequently established. Second, for the control strategy, a β‐measure is introduced to measure the constraint‐following error. To ensure the tracking‐avoidance constraint and the arrival constraint can be fully satisfied by the system, an adaptive robust control is designed. Finally, for the fast time‐varying uncertainty with unknown boundary, an adaptive law is introduced to evaluate the triple tracking‐avoidance‐arrival performance. In conclusion, the main contribution of this paper is to achieve triple tracking‐avoidance arrival for unmanned combat platform, and the problem of military detection and rescue on complex battlefields can be eliminated. [ABSTRACT FROM AUTHOR]

To enhance the hitting accuracy of tank with moving firing, an uncertain optimization method based on stochastic programming is adopted to reduce the initial disturbance of projectile. Firstly, the firing dynamics model of moving tank is modeled to simulate the initial disturbance of projectile. Secondly, the controllable interior ballistic parameters such as projectile structure parameters and propellant parameters are treated as random design variables. The surrogate model for the firing dynamics model of moving tank is constructed by using the neural network based on deep learning. The uncertain optimization problem is transformed into a deterministic optimization problem by stochastic programming method. Then multi-objective genetic algorithm is adopted to settle optimization model, and reasonable design interval of random design variables is obtained. Finally, a six-degree-of-freedom rigid external ballistics model is used to establish a hitting accuracy evaluation model of moving tank based on interval uncertainty analysis. Through this model, the effectiveness of the optimization method is demonstrated. [ABSTRACT FROM AUTHOR]