TRIP6 a potential diagnostic marker for colorectal cancer with glycolysis and immune infiltration association.

Thyroid hormone receptor interactor 6 (TRIP6) it is an adaptor protein belonging to the zyxin family of LIM proteins, participating in signaling events through interactions with various molecules. Despite this, TRIP6's role in colorectal cancer (CRC), particularly its correlation with glucose metabolism and immune cell infiltration, remains unclear. Through the TCGA and GEO databases, we obtained RNA sequencing data to facilitate our in-depth study and analysis of TRIP6 expression. To investigate the prognostic value of TRIP6 in CRC, we also used univariate Cox regression analysis. In addition, this study also covered a series of analyses, including clinicopathological analysis, functional enrichment analysis, glycolysis correlation analysis, immunoinfiltration analysis, immune checkpoint analysis, and angiogenesis correlation analysis, to gain a comprehensive and in-depth understanding of this biological phenomenon. It has been found that TRIP6 expression is significantly upregulated in CRC and correlates with the stage of the disease. Its overexpression portends a worse survival time. Functional enrichment analysis reveals that TRIP6 is associated with focal adhesion and glycolysis. Mechanistically, TRIP6 appears to exert its tumorigenic effect by regulating the glycolysis-related gene GPI. A higher level of expression of TRIP6 is associated with an increase in the number of iDC immune cells and a decrease in the number of Th1 immune cells. Also, TRIP6 may promote angiogenesis in tumor cells by promoting the expression of JAG2. Our study uncovers the upregulation of TRIP6 in CRC, illuminating its prognostic and diagnostic value within this context. Furthermore, we examine the relationship between TRIP6 expression levels, glycolysis, angiogenesis and immune cell infiltration. This underscores its potential as a biomarker for CRC treatment and as a therapeutic target.

A novel prescribed performance controller for strict-feedback nonlinear systems with input constraints.

This paper is devoted to the prescribed performance control (PPC) for a class of strict-feedback nonlinear systems with input saturation constraints. With the help of an improved tuning function, the system can achieve the desired steady-state and transient performance in the pre-designed time. A new error transformation function is introduced, which has inherent robustness, so it does not need to use any approximation technique or calculate the analytical derivative. Compared with the relevant results, the proposed scheme has the same lower complexity, but better transient and steady-state performance, although there exists uncertain nonlinearity and uncertain disturbances in the system. Finally, the correctness of the above algorithm is verified by simulation experiments.

Lower triangle factor based sliding mode observers design for T-S fuzzy systems with faults.

The paper mainly focuses on the fault estimation for a class of Takagi-Sugeno (T-S) fuzzy systems with faults. A synthetic estimation observer design method is proposed. The synthetic estimation observer can cover the robust observer, adaptive observer and intermediate estimation observer in the existing study work. Based on the observer design method, an LTF-based sliding mode observer (SMO) is designed for the T-S fuzzy system in consideration. Under the observer, the fault occurring in the system can be well estimated. The obtained LMI-based conditions guarantee the states of the error dynamics to be uniformly ultimately bounded. A numerical example tests the proposed method.

Comprehensive Analysis of GLUT1 Immune Infiltrates and ceRNA Network in Human Esophageal Carcinoma.

BACKGROUND: Glucose transporter 1 (GLUT1) is encoded by the solute carrier family 2A1 (SLC2A1) gene and is one of the glucose transporters with the greatest affinity for glucose. Abnormal expression of GLUT1 is associated with a variety of cancers. However, the biological role of GLUT1 in esophageal carcinoma (ESCA) remains to be determined. METHODS: We analyzed the expression of GLUT1 in pan-cancer and ESCA as well as clinicopathological analysis through multiple databases. Use R and STRING to perform GO/KEGG function enrichment and PPI analysis for GLUT1 co-expression. TIMER and CIBERSORT were used to analyze the relationship between GLUT1 expression and immune infiltration in ESCA. The TCGA ESCA cohort was used to analyze the relationship between GLUT1 expression and m6A modification in ESCA, and to construct a regulatory network in line with the ceRNA hypothesis. RESULTS: GLUT1 is highly expressed in a variety of tumors including ESCA, and is closely related to histological types and histological grade. GO/KEGG functional enrichment analysis revealed that GLUT1 is closely related to structural constituent of cytoskeleton, intermediate filament binding, cell-cell adheres junction, epidermis development, and P53 signaling pathway. PPI shows that GLUT1 is closely related to TP53, GIPC1 and INS, and these three proteins all play an important role in tumor proliferation. CIBERSORT analysis showed that GLUT1 expression is related to the infiltration of multiple immune cells. When GLUT1 is highly expressed, the number of memory B cells decreases. ESCA cohort analysis found that GLUT1 expression was related to 7 m6A modifier genes. Six possible crRNA networks in ESCA were constructed by correlation analysis, and all these ceRNA networks contained GLUT1. CONCLUSION: GLUT1 can be used as a biomarker for the diagnosis and treatment of ESCA, and is related to tumor immune infiltration, m6A modification and ceRNA network.

Neural Network Adaptive Tracking Control of Uncertain MIMO Nonlinear Systems With Output Constraints and Event-Triggered Inputs.

This article is concerned with a neural adaptive tracking control scheme for a class of multiinput and multioutput (MIMO) nonaffine nonlinear systems with event-triggered mechanisms, which include the fixed thresholds, triggering control inputs, and decreasing functions of tracking errors. Unlike the existing results of nonaffine nonlinear controller decoupling, a novel nonlinear multiple control inputs separated design method is proposed based on the mean-value theorem and the Taylor expansion technique. By this way, a weaker condition of nonlinear decoupling is provided to instead of the previous ones. Then, introducing a prescribed performance barrier Lyapunov function (PPBLF) and using neural networks (NNs), the presented event-triggered controller can maintain better tracking performance and effectively alleviate the computation burden of the communication procedure. Furthermore, it is proved that all the closed-loop signals are bounded and the system output tracking errors are confined within the prescribed bounds. Finally, the simulation results are given to demonstrate the validity of the developed control scheme.

Adaptive Fuzzy Tracking Control for a Class of Uncertain Switched Nonlinear Systems With Full-State Constraints and Input Saturations.

In this article, an adaptive fuzzy tracking control scheme is developed for a class of uncertain switched nonlinear systems with input saturations and full-state constraints. First to surmount the design difficulty with respect to a saturation nonlinearity controller, a nonlinear smooth function approximating the nondifferential saturation function is introduced to establish a standard switched adaptive tracking control strategy based on the mean-value theorem and the input compensation technique. Then, invoking fuzzy-logic systems (FLSs), a novel analysis method of average dwell time for switched nonlinear systems with full-state constraints is proposed by using an artful logarithmic inequality. Furthermore, the designed adaptive controller can ensure that all the states of uncertain switched nonlinear systems are not to violate the set constraint bounds by employing barrier Lyapunov functions (BLFs), and that the system output tracking error can converge to a desired neighborhood of the origin within a suitable compact set. Finally, the simulation results are given to demonstrate the validity of the presented approach.

Event-triggered adaptive prescribed performance control of uncertain nonlinear systems with unknown control directions.

The problem of event-triggered prescribed performance control for a class of uncertain nonlinear systems with unknown control directions and faults is investigated. Compared with the existing methods, a new set of error transformation functions is defined for the first time. Although no approximate structure is adopted, prescribed performance control (PPC) and event triggered control (ETC) are realized simultaneously for the nonlinear system considered in this paper for the first time. The proposed control scheme can guarantee that all closed-loop signals are bounded, and the tracking error, as well as all state errors, converges within the adjustable constraint functions. Finally, two simulation experiments verify the effectiveness of the proposed algorithm.

Robust Adaptive Fault-Tolerant Tracking Control for Nonaffine Stochastic Nonlinear Systems With Full-State Constraints.

In this article, the adaptive fault-tolerant tracking control problem of nonaffine stochastic nonlinear systems with actuator failures and full-state constraints is studied. To surmount the design difficulty from nonaffine nonlinear term with multi-input and single-output (MISO) faulty modes, a novel nonlinear fault compensation function with adjustable parameter factor is first introduced to establish a standard adaptive fault-tolerant control (AFTC) strategy based on the mean-value theorem. Then, the remaining nonlinear function, including the partial loss of effectiveness, outage, and stuck cases, together with the constructed compound nonlinear function can be approximated by using the suitable fuzzy-logic system (FLS). Moreover, it is shown that all the states of nonaffine stochastic nonlinear systems are not violating the preset constraint bounds by employing the barrier Lyapunov functions (BLFs). Also, the given adaptive controller can guarantee all the closed-loop signals are uniformly ultimately bounded (UUB) in probability in the sense of fourth-moment within the appropriate compact sets. Finally, two simulation examples are given to demonstrate the validity of the proposed method.

Convergent Estimation Mechanism Design for Nonlinear Fuzzy Systems With Faults.

The convergent estimation for a class of nonlinear Takagi-Sugeno fuzzy systems is concerned, where time-varying process faults and input disturbances are both involved. A convergent estimation mechanism (CEM) based on a set of fuzzy iterative estimation observers is constructed for the nonlinear fuzzy system; meanwhile, the convergence of the mean sequence of estimation errors (for both states and faults) to zero (vector) is proved. However, in the existing literature, the estimation errors can only be proved to be uniformly ultimately bounded when the fault is time varying. In the design procedure, the disturbances on systems in consideration can be isolated effectively in the obtained fuzzy iterative error dynamics through introducing a suitable isolation technique. Numerical examples give the simulation results to show the effectiveness and merits of the proposed CEM.

Effect of organic additives on silver release from nanosilver-polyethylene composite films to acidic food simulant.

The effects of organic additives (Irgafos 168, Irganox 1076, Tinuvin 622, Chimassorb 944, UV-P, and UV-531) on silver release from nanosilver-polyethylene composite films into an acidic food simulant (3% acetic acid) were investigated using inductively coupled plasma mass spectrometry. The limits of detection and quantification, coefficient of determination, and recoveries of the method used were 3.7ngL-1, 12.4ngL-1, 0.999, and 89-113%, respectively. The results indicated that additives can affect silver release via two simultaneous processes: (i) reactions between organic additives and silver that promote silver release from the composite film to the acidic food simulant; and (ii) the promotion or inhibition of silver release by affecting silver oxidation. High temperature and humidity treatment of the composite films was found to significantly increase silver release by promoting silver oxidation.

Adaptive Output Neural Network Control for a Class of Stochastic Nonlinear Systems With Dead-Zone Nonlinearities.

This paper investigates the problem of adaptive output neural network (NN) control for a class of stochastic nonaffine and nonlinear systems with actuator dead-zone inputs. First, based on the intermediate value theorem, a novel design scheme that converts the nonaffine system into the corresponding affine system is developed. In particular, the priori knowledge of the bound of the derivative of the nonaffine and nonlinear functions is removed; then, by employing NNs to approximate the appropriate nonlinear functions, the corresponding adaptive NN tracking controller with the adjustable parameter updated laws is designed through a backstepping technique. Furthermore, it is shown that all the closed-loop signals are bounded in probability, and the system output tracking error can converge to a small neighborhood in the sense of a mean quartic value. Finally, experimental simulations are provided to demonstrate the efficiency of the proposed adaptive NN tracking control method.

Effect of antioxidants and light stabilisers on silver migration from nanosilver-polyethylene composite packaging films into food simulants.

The effect of exposure time, temperature and food simulants, especially additives, on the release of silver from nanosilver-polyethylene composite films to food simulants was studied. Two different type of nanosilver-polyethylene composite films (with or without additives) were chosen to conduct the experiment with the aim of exploring the behaviour of silver migration. It was shown that the migration of silver into 50% ethanol at 40 and 70°C was much less than that into 3% acetic acid. With the increase of exposure time and temperature, the release of silver increased. The migration even continued after a long exposure time (14 days at 20°C, 10 days at 40°C, and 6 days at 70°C respectively). Only about 0.15‰ of silver migrated from composite films with the additives into 3% acetic acid after 6 days of exposure at 70°C, while about 1.3% of silver migrated from composite films that did not contain additives under the same conditions. This could be because the addition of the antioxidants and light stabilisers prevents silver from being oxidised, which is an important way for the release of silver.