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The study of multivariate time series forecasting (MTSF) problems has high significance in many areas, such as industrial forecasting and traffic flow forecasting. Traditional forecasting models pay more attention to the temporal features of variables and lack depth in extracting spatial and spatiotemporal features between variables. In this paper, a novel model based on the Transformer, convolutional neural network (CNN), and long short-term memory (LSTM) network is proposed to address the issues. The model first extracts the spatial feature vectors through the proposed Multi-kernel CNN. Then it fully extracts the temporal information by the Encoder layer that consists of the Transformer encoder layer and the LSTM network, which can also obtain the potential spatiotemporal correlation. To extract more feature information, we stack multiple Encoder layers. Finally, the output is decoded by the Decoder layer composed of the ReLU activation function and the Linear layer. To further improve the model's robustness, we also integrate an autoregressive model. In model evaluation, the proposed model achieves significant performance improvements over the current benchmark methods for MTSF tasks on four datasets. Further experiments demonstrate that the model can be used for long-horizon forecasting and achieve satisfactory results on the yield forecasting of test items (our private dataset, TIOB). [ABSTRACT FROM AUTHOR]

Compared with traditional hydrodesulfurization, new nonhydrodesulfurization methods have the advantage of a high removal efficiency for thiophene compounds under mild conditions. However, independent nonhydrodesulfurization technologies are faced with their own shortcomings, such as limitations of the desulfurization performance and regeneration of materials. To overcome these limitations, four nanofluids were prepared by dispersing different metal-modified MCM-41 particles in deep eutectic solvent as multifunctional promoters to develop a comprehensive desulfurization method. Based on the excellent adsorbability and high catalytic activity of the dispersed particles and the outstanding extractability of deep eutectic solvent in nanofluids, a high sulfur removal of 99.33% was achieved for model oil under mild conditions in 15 min. The nanofluids also showed excellent reusability due to their high structural stability. In addition, NF@Cu/Al-MCM-41-2.5% exhibited the best desulfurization performance among the prepared nanofluids. This result was obtained because the introduction of Al ions increased the number of acid sites and defect sites to improve the catalytic activity and adsorbability, and the best affinity of Cu/Al-MCM-41 for the deep eutectic solvent favored the reaction mass transfer. This work opens the door to the development of a comprehensive nonhydrodesulfurization method based on the design of nanofluid materials. [ABSTRACT FROM AUTHOR]

Summary: The asynchronous filtering problem for networked fuzzy non‐homogeneous Markov jump systems is investigated, with the consideration of packet dropout and quantization. An event‐triggered dynamic quantization scheme is proposed, and a stability criterion is given to ensure the stochastic stability of the filtering error systems with desired extended dissipative performance. This performance provides a unified framework in the sense that it can degenerate to H∞$$ {H}_{\infty } $$, l2−l∞$$ {l}_2-{l}_{\infty } $$, dissipativity and passivity filter, respectively, under certain parameter sets. Furthermore, an asynchronous filter design method with extended dissipative performance is given based on the proposed stability criterion. In this method, the existence of the quantizer is ensured by dynamic quantization levels and the solution scope of the filter is enlarged by a free‐connection weighting matrices method. The theoretical design and analysis is finally evaluated using a practical example. [ABSTRACT FROM AUTHOR]

Cluster consensus is investigated for multiple coupled harmonic oscillators under a weighted cooperative-competitive network. Consensus protocols for three categories of communication networks are constructed by employing a weighted gain, and sufficient conditions for guaranteeing cluster consensus are obtained. It is found that under the proposed protocols, the states of all oscillators can be guaranteed to reach periodic orbits that are the same in frequency no matter which cluster the oscillators belong to. In particular, cluster partitions here are not given a prior, but are determined by the communication topology among oscillators. Numerical examples are given to validate the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

Functional corticomuscular coupling (FCMC) between the cerebral motor cortex and muscle activity reflects multi-layer and nonlinear interactions in the sensorimotor system. Considering the inherent multiscale characteristics of physiological signals, we proposed multiscale transfer spectral entropy (MSTSE) and introduced the unidirectionally coupled Hénon maps model to verify the effectiveness of MSTSE. We recorded electroencephalogram (EEG) and surface electromyography (sEMG) in steady-state grip tasks of 29 healthy participants and 27 patients. Then, we used MSTSE to analyze the FCMC base on EEG of the bilateral motor areas and the sEMG of the flexor digitorum superficialis (FDS). The results show that MSTSE is superior to transfer spectral entropy (TSE) method in restraining the spurious coupling and detecting the coupling more accurately. The coupling strength was higher in the ${\boldsymbol{\beta}}$ 1, ${\boldsymbol{\beta}}$ 2, and $\ {\boldsymbol{\gamma}}$ 2 bands, among which, it was highest in the ${\boldsymbol{\beta}}$ 1 band, and reached its maximum at the 22–30 scale. On the directional characteristics of FCMC, the coupling strength of EEG→sEMG is superior to the opposite direction in most cases. In addition, the coupling strength of the stroke-affected side was lower than that of healthy controls’ right hand in the ${\boldsymbol{\beta}}$ 1 and ${\boldsymbol{\beta}}$ 2 bands and the stroke-unaffected side in the ${\boldsymbol{\beta}}$ 1 band. The coupling strength of the stroke-affected side was higher than that of the stroke-unaffected side and the right hand of healthy controls in the sEMG→EEG direction of ${\boldsymbol{\gamma}}$ 2 band. This study provides a new perspective and lays a foundation for analyzing FCMC and motor dysfunction. [ABSTRACT FROM AUTHOR]

The scheduling and control of wireless cloud control systems involving multiple independent control systems and a centralized cloud computing platform are investigated. For such systems, the scheduling of the data transmission as well as some particular design of the controller can be equally important. From this observation, we propose a dual channel-aware scheduling strategy under the packet-based model predictive control framework, which integrates a decentralized channel-aware access strategy for each sensor, a centralized access strategy for the controllers, and a packet-based predictive controller to stabilize each control system. First, the decentralized scheduling strategy for each sensor is set in a noncooperative game framework and is then designed with asymptotical convergence. Then, the central scheduler for the controllers takes advantage of a prioritized threshold strategy, which outperforms a random one neglecting the information of the channel gains. Finally, we prove the stability for each system by constructing a new Lyapunov function, and further reveal the dependence of the control system stability on the prediction horizon and successful access probabilities of each sensor and controller. These theoretical results are successfully verified by numerical simulation. [ABSTRACT FROM AUTHOR]

The experiment was to investigate the effect of phytosterol formula on growth performance, immune function, nutrient apparent digestibility and intestinal microflora of piglets. The results showed that the feeding phytosterol formula increased the average daily gain of piglets by 14.73%, and reduced diarrhea rate by 62.21%. The serum test found that growth hormone in serum increased by 18.59%, total protein increased by 13.07%, immunoglobulin G increased by 42.70%, and TNF-α decreased by 24.49%. The apparent digestibility rate of dry matter, crude fat and crude protein was improved and the intestinal microbes was significantly boosted. The experiment indicates that the phytosterol formula significantly improves the immune function of piglets and growth performance, which can be potentially used as an antibiotics replacement products in feed industry. [ABSTRACT FROM AUTHOR]

This article investigates the predictive control scheme and related stability issue for a class of discrete-time perturbed nonlinear system with state and input constraints. First, we propose a novel control framework, i.e., networked dual-mode adaptive horizon model predictive control (MPC), which consists of a local controller, a remote controller that is subject to packet losses, and a judger coordinating the switchings between them. The optimization procedure of MPC with variable prediction horizon is implemented in the remote controller while a simple state-feedback control law is in the local one. Second, to establish the stability condition, we propose a new Lyapunov function. By specifying the relation between the Lyapunov function and the optimal MPC value function, the input-to-state practical stability is established. Finally, simulation results show the effectiveness of our proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, an approximation-based event-triggered model predictive control (AETMPC) strategy is proposed to implement event-triggered model predictive control for continuous-time constrained nonlinear systems under the digital platform. In the AETMPC strategy, both of the optimal control problem (OCP) and the triggering conditions are defined in a discrete-time manner based on approximate discrete-time models, while the plant under control is continuous time. In doing so, sensing load is alleviated because the triggering condition does not need to be checked continuously, and the computation of the OCP is simpler since which is calculated in the discrete-time framework. Meanwhile, robust constraints are satisfied in a continuous-time sense by taking inter-sampling behavior into consideration, and a novel constraint tightening approach is presented accordingly. Furthermore, the feasibility of the AETMPC strategy is analyzed and the associated stability of the overall system is established. Finally, this strategy is validated by a numerical example. [ABSTRACT FROM AUTHOR]

Simultaneous and continuous joint angle estimation plays an important role in motion intention recognition and rehabilitation training. A surface electromyography (sEMG) state-space model is proposed to estimate simultaneous and continuous lower-limb-joint movements from sEMG signals in this article. The model combines the forward dynamics with Hill-based muscle model (HMM), making the extended model capable of estimating the lower-limb-joint motion directly. sEMG features including root-mean-square and wavelet coefficients are then extracted to construct a measurement equation used to reduce system error and external disturbances. With the proposed model, unscented Kalman filter is used to estimate joint angle from sEMG signals. In the experiments, sEMG signals were recorded from ten subjects during muscle contraction involving three lower-limb-joint motions (knee-joint motion, ankle-joint motion, and simultaneous knee-ankle-joint motion). Comprehensive experiments are conducted on three motions and the results show that the mean root–mean–square error for knee-joint motion, ankle-joint motion, and simultaneous motion of the proposed model are 5.1143°, 5.2647°, and 6.3941°, respectively, and significant improvements are demonstrated compared with the traditional methods. [ABSTRACT FROM AUTHOR]

Schisandrin B has been proved to possess anti‐inflammatory and anti‐endoplasmic effects, could improve cardiac function, inhibit apoptosis, and reduce inflammation after ischemic injury. However, the detailed metabolic mechanism and potential pathways of Schisandrin B effects on myocardial injury are unclear. Metabolomics could yield in‐depth mechanistic insights and explore the potential therapeutic effect of natural products. In this study, the preparation of doxorubicin‐induced myocardial injury rat model for evaluation of Schisandrin B on viral myocarditis sequelae related pathological changes and its mechanism. The metabolite profiling of myocardial injury rats was performed through ultra‐high performance liquid chromatography combined with mass spectrometry combined with pattern recognition approaches and pathway analysis. A total of 15 metabolites (nine in positive ion mode and six in negative ion mode) were considered as potential biomarkers of myocardial injury, and these metabolites may correlate with the regulation of Schisandrin B treatment. A total of six metabolic pathways are closely related to Schisandrin B treatment, including glycerophospholipid metabolism, sphingolipid metabolism, purine metabolism, etc. This study revealed the potential biomarkers and metabolic network pathways of myocardial injury, and illuminated the protective mechanism of Schisandrin B on myocardial injury. [ABSTRACT FROM AUTHOR]

Ultra‐performance liquid chromatography/mass spectrometry‐based metabolomics can been used for discovery of metabolite biomarkers to explore the metabolic pathway of diseases. Identification of metabolic pathways is key to understanding the pathogenesis and mechanism of disease. Myocardial dysfunction induced by sepsis (SMD) is a severe complication of septic shock and represents major causes of death in intensive care units; however its pathological mechanism is still not clear. In this study, ultrahigh‐pressure liquid chromatography with mass spectrometry‐based metabolomics with chemometrics anaylsis and multivariate pattern recognition analysis were used to detect urinary metabolic profile changes in a lipopolysaccharide‐induced SMD mouse model. Multivariate statistical analysis including principal component analysis and orthogonapartial least squares discriminant analysis for the discrimination of SMD was conducted to identify potential biomarkers. A total of 19 differential metabolites were discovered by high‐resolution mass spectrometry‐based urinary metabolomics strategy. The altered biochemical pathways based on these metabolites showed that tyrosine metabolism, phenylalanine metabolism, ubiquinone biosynthesis and vitamin B6 metabolism were closely connected to the pathological processes of SMD. Consequently, integrated chemometric analyses of these metabolic pathways are necessary to extract information for the discovery of novel insights into the pathogenesis of disease. [ABSTRACT FROM AUTHOR]

Surface electromyography (sEMG) is an electrophysiological reflection of skeletal muscle contractile activity that can directly reflect neuromuscular activity. It has been a matter of research to investigate feature extraction methods of sEMG signals. In this letter, we propose a feature extraction method of sEMG signals based on the improved small-world leaky echo state network (ISWLESN). The reservoir of leaky echo state network (LESN) is connected by a random network. First, we improved the reservoir of the echo state network (ESN) by these networks and used edge-added probability to improve these networks. That idea enhances the adaptability of the reservoir, the generalization ability, and the stability of ESN. Then we obtained the output weight of the network through training and used it as features. We recorded the sEMG signals during different activities: falling, walking, sitting, squatting, going upstairs, and going downstairs. Afterward, we extracted corresponding features by ISWLESN and used principal component analysis for dimension reduction. At the end, scatter plot, the class separability index, and the Davies-Bouldin index were used to assess the performance of features. The results showed that the ISWLESN clustering performance was better than those of LESN and ESN. By support vector machine, it was also revealed that the performance of ISWLESN for classifying the activities was better than those of ESN and LESN. [ABSTRACT FROM AUTHOR]

Continuous joint angle estimation plays an important role in motion intention recognition and rehabilitation training. In this study, a surface electromyography- (sEMG-) mechanomyography (MMG) state-space model is proposed to estimate continuous multijoint movements from sEMG and MMG signals accurately. The model combines forward dynamics with a Hill-based muscle model that estimates joint torque only in a nonfeedback form, making the extended model capable of predicting the multijoint motion directly. The sEMG and MMG features, including the Wilson amplitude and permutation entropy, are then extracted to construct a measurement equation to reduce system error and external disturbances. Using the proposed model, a closed-loop prediction-correction approach, unscented particle filtering, is used to estimate the joint angle from sEMG and MMG signals. Comprehensive experiments are conducted on the human elbow and shoulder joint, and remarkable improvements are demonstrated compared with conventional methods. [ABSTRACT FROM AUTHOR]

Most video surveillance systems use both RGB and infrared cameras, making it a vital technique to re‐identify a person cross the RGB and infrared modalities. This task can be challenging due to both the cross‐modality variations caused by heterogeneous images in RGB and infrared, and the intra‐modality variations caused by the heterogeneous human poses, camera position, light brightness etc. To meet these challenges, a novel feature learning framework, hard pentaplet and identity loss network (HPILN), is proposed. In the framework existing single‐modality re‐identification models are modified to fit for the cross‐modality scenario, following which specifically designed hard pentaplet loss and identity loss are used to increase the accuracy of the modified cross‐modality re‐identification models. Based on the benchmark of the SYSU‐MM01 dataset, extensive experiments have been conducted, showing that the authors' method outperforms all existing ones in terms of cumulative match characteristic curve and mean average precision. [ABSTRACT FROM AUTHOR]

Daily activity monitoring plays an important role among frail or elderly people and has caught attention. Surface electromyography (sEMG) can extract the feature of activity, but it is not stable because of electrode displacement, postural changes, and individual-dependent features, such as the condition of muscles, subcutaneous fat, and skin surface. To effectively extract the feature of sEMG signal, we proposed a new method of feature extraction based on coherence analysis. The sEMG signals were recorded from gastrocnemius, tibialis anterior, rectus femoris, and semitendinosus. After de-noising, sEMG signals were decomposed into 32-scale by wavelet transformation, and their wavelet coefficients were employed to calculate wavelet coherence coefficients (WCC). We employed T test to find out if the coherence between sEMG signals was statistically different among six activities. The 32nd scale WCC of RF–ST and ST–TA as eigenvector was entered into the support vector machine (SVM). The six activities, namely, standing, walking, running, stair-ascending, stair-descending, and falling, were successfully identified by the WCC feature with the SVM classifier. [ABSTRACT FROM AUTHOR]

A classification‐based control approach is proposed for wireless networked control systems with lossy multipacket transmission. This approach takes advantage of a state reconstruction process to deal with the distinct feature of partial failure of data transmission caused by multipacket transmission, and then classifies the difference of the latest received system states and reconstructed ones to design a classification‐based controller. The closed‐loop stability of the system is proven using the switched systems theory. By considering more communication characteristics of multipacket transmission, the proposed approach is shown to give rise to a better system performance by a numerical example. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

The stochastic stabilisation of networked control systems is investigated with a special focus on the lossy multi‐packet transmission in the wireless communication context. The resulting partially available system states due to multi‐packet transmission are firstly reconstructed at the controller, and the sufficient conditions for stochastic stability are then given for the closed‐loop system, which finally leads to a controller design method with explicit consideration of multi‐packet transmission. The proposed theoretical results are verified by both numerical and TrueTime‐based examples. [ABSTRACT FROM AUTHOR]

The control problem of vehicle platoons considering sensors with limited measurement range and actuator time delay is investigated in the face of constraints. A new delayed feedback model predictive control scheme is proposed to solve the problem while satisfying the constraints on measurement range and driving behaviors. A family of controllers is presented with free parameters which are then computed by online solving of a receding horizon optimal control problem. Terminal equality constraints are adopted to guarantee stability of the closed‐loop system. Some sufficient conditions with guaranteed string stability of the platoon and zero steady‐state error are established. The effectiveness and advantages of the presented method are demonstrated by simulating two classical road scenarios. [ABSTRACT FROM AUTHOR]

The output consensus of multi‐agent systems is investigated, where constant communication delay is present and the dynamics of the agents are heterogeneous. Based on the networked predictive control scheme, the distributed consensus protocol with dynamic output feedback controller is designed, and the sufficient conditions of the output consensus are obtained. Numerical examples illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: The bipartite consensus problem is investigated for double‐integrator multi‐agent systems in the presence of measurement noise. A distributed protocol with time‐varying consensus gain is proposed. By using tools of state transition matrix and algebraic graph theory, necessary and sufficient conditions for the designed protocol to be a mean square bipartite linear χ‐consensus protocol are given. It is shown that the signed digraph being structurally balanced and having a spanning tree are not only sufficient, but also necessary for bipartite consensus. Furthermore, the protocol is proved to be a mean square bipartite average consensus protocol if the signed graph is weight balanced. [ABSTRACT FROM AUTHOR]

The bipartite consensus problem for integrator multi‐agent systems over signed fixed digraphs is investigated in the presence of measurement noise. A time‐varying consensus gain is introduced and then a stochastic type protocol is proposed, whose performance is analysed using the state transition matrix of the closed‐loop system. Necessary and sufficient conditions for ensuring a mean square bipartite consensus protocol are obtained in the presence of noise. Furthermore, in the absence of noise it is shown that these conditions are also necessary and sufficient for ensuring the bipartite consensus except for the quadratic integrability of the consensus gain. It is found that the signed digraph being structurally balanced and having a spanning tree are the weakest assumptions on connectivity for achieving bipartite consensus regardless of the measurement noise. In particular, if the signed digraph is structurally unbalanced, then under some mild conditions, the states of the closed‐loop system converge to zero in mean square, regardless of the initial states. [ABSTRACT FROM AUTHOR]

mRNA translation is a complex process involving the progression of ribosomes on the mRNA, resulting in the synthesis of proteins, and is subject to multiple layers of regulation. This process has been modelled using different formalisms, both stochastic and deterministic. Recently, we introduced a Probabilistic Boolean modelling framework for mRNA translation, which possesses the advantage of tools for numerically exact computation of steady state probability distribution, without requiring simulation. Here, we extend this model to incorporate both random sequential and parallel update rules, and demonstrate its effectiveness in various settings, including its flexibility in accommodating additional static and dynamic biological complexities and its role in parameter sensitivity analysis. In these applications, the results from the model analysis match those of TASEP model simulations. Importantly, the proposed modelling framework maintains the stochastic aspects of mRNA translation and provides a way to exactly calculate probability distributions, providing additional tools of analysis in this context. Finally, the proposed modelling methodology provides an alternative approach to the understanding of the mRNA translation process, by bridging the gap between existing approaches, providing new analysis tools, and contributing to a more robust platform for modelling and understanding translation. [ABSTRACT FROM PUBLISHER]

An extended asynchronous switching model is investigated for a class of switched stochastic nonlinear retarded systems in the presence of both detection delay and false alarm, where the extended asynchronous switching is described by two independent and exponentially distributed stochastic processes, and further simplified as Markovian. Based on the Razumikhin-type theorem incorporated with average dwell-time approach, the sufficient criteria for global asymptotic stability in probability and stochastic input-to-state stability are given, whose importance and effectiveness are finally verified by numerical examples. [ABSTRACT FROM PUBLISHER]

As an emerging research field, networked control systems have shown the increasing importance and attracted more and more attention in the recent years. The integration of control and communication in networked control systems has made the design and analysis of such systems a great theoretical challenge for conventional control theory. Such an integration also makes the implementation of networked control systems a necessary intermediate step towards the final convergence of control, communication, and computation. We here introduce the basics of networked control systems and then describe the state-of-the-art research in this field. We hope such a brief tutorial can be useful to inspire further development of networked control systems in both theory and potential applications. [ABSTRACT FROM AUTHOR]

In this paper, a new method for stability analysis of a single degree of freedom (SDOF) cutting system with sinusoidal spindle speed variation (SSSV) is proposed. Based on the approximately periodic property of the time delay in the turning process and the delay decomposition method, novel criteria of stability analysis for an SDOF cutting system are presented. Moreover, a state feedback controller is designed to stabilize the system and improve the steady-state response. Numerical simulation shows the effectiveness of the method. [ABSTRACT FROM PUBLISHER]

The sensor-to-controller and the controller-to-actuator delays in networked control systems (NCSs) are investigated for the first time with respect to their different effects on the system performance. This study starts with identifying the delay-independent and delay-dependent control laws in NCSs, and confirms that only two delay-dependent control laws can cause different delay effects in different channels. The conditions under which the different delays in different channels can cause different effects are then given for both delay-dependent control laws. The results are verified by numerical examples. Potentially, these results can be regarded as important design principles in the practical implementation of NCSs. [ABSTRACT FROM AUTHOR]

The input-to-state stability problem of a class of nonlinear switched networked control systems subject to time-varying transmission intervals, periodical packet dropouts, and communication constraints is investigated. By adopting the extended input-to-state stability(eISS) protocol and constructing a novel Lyapunov function, the input-to-state stability properties of such systems are discussed. Then, by making use of the small-gain theorem, the maximum allowable transmission interval to guarantee system stability is obtained. A batch reactor is finally considered to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The stability of a class of switched stochastic nonlinear retarded systems with asynchronous switching controller is investigated. By constructing a virtual switching signal and using the average dwell time approach incorporated with Razumikhin-type theorem, the sufficient criteria for pth moment exponential stability and global asymptotic stability in probability are given. It is shown that the stability of the asynchronous stochastic systems can be guaranteed provided that the average dwell time is sufficiently large and the mismatched time between the controller and the systems is sufficiently small. This result is then applied to a class of switched stochastic nonlinear delay systems where the controller is designed with both state and switching delays. A numerical example illustrates the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

Data packet disorder is inevitable in discrete-time networked control systems, which however has been ignored in most literature to date. This work investigates the cause and the negative effects of data packet disorder in discrete-time networked control systems, and a compensation scheme is proposed to deal with these negative effects. This analysis shows that most existing works in the related areas have assumed unrealistic characteristics of the communication network and thus further improvements within this new framework are necessary. For this purpose the closed-loop system with the use of the proposed compensation scheme is mathematically modeled as a Markov jump systems, and stochastic stability and stabilization results are then obtained. Numerical examples illustrate the negative effects caused by data packet disorder and also the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

An error bounded sensing strategy is proposed within the packet-based control framework for networked control systems (NCSs). This strategy reduces the data transmissions in both the sensor-to-controller and the controller-to-actuator channels by allowing the transmissions of only the sensing and control data packets that satisfy some predetermined transmission rules. By fitting it into the packet-based control framework for NCSs, this strategy can achieve the goal of reducing the use of the communication resources while at the same time maintaining the system performance at an acceptable level. Stabilized controllers are designed within this framework, and the effects on the system stability brought by this approach are also investigated. Numerical and experimental examples illustrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

The effect of selenium (Se) in reducing the toxicity of cisplatin in cancer patients was studied. Forty-one patients were randomized into group A (20 patients with Se administration in first cycle of chemotherapy as study cases and without Se in second cycle of chemotherapy as control) and group B (21 patients without Se in first cycle of chemotherapy and with Se in second cycle of chemotherapy). The 400 μg per day of Se as Seleno-Kappacarrageenan were administered from 4 before to 4 d after chemotherapy for study cases. The serum Se increased from 70.4±22.86 to 157.04±60.23 ng/mL ( P<0.001) in patients received Se. The cisplatin dosage was iv administration in 60–80 mg/m2 on the first day. The results showed that the peripheral WBC counts on day 14 after initiation of chemotherapy in study cases was significantly higher than the controls (3.35±2.01 vs 2.31±1.38 [×109L])/L, p<0.05). On the other hand, the consumption of GCSF for the cases was significantly less than the controls (110.1±82.2 vs 723.6±192.6 IU, p<0.05). The volumes of blood transfusion for the study group were also significantly less than the controls (0 vs 62±38mL, p<0.05). The nephrotoxicity of cisplatin was measured by urine enzymes (NAG, GGT, AAP, LAP, and ALP) were determined prior to and at 2, 24, 48, and 72h after initiation of chemotherapy. The urine enzymes NAG, GGT, AAP, and ALP after chemotherapy for cases were significantly lower than the controls. No toxicity of Seleno-Kappacarrageenan was noted. The above results suggest that the Se can be used as an agent for reducing the nephrotoxicity and bone marrow suppression induced by cisplatin. [ABSTRACT FROM AUTHOR]

In eukaryotes, the binding of poly(A) binding protein (PAB) to the poly(A) tail is central to maintaining mRNA stability. PABP interacts with the translation termination apparatus, and with eIF4G to maintain 3′–5′ mRNA interactions as part of an mRNA closed loop. It is however unclear how ribosome recycling on a closed loop mRNA is influenced by the proximity of the stop codon to the poly(A) tail, and how post-termination ribosome recycling affects mRNA stability. We show that in a yeast disabled for nonsense mediated mRNA decay (NMD), a PGK1 mRNA with an early stop codon at codon 22 of the reading frame is still highly unstable, and that this instability cannot be significantly countered even when 50% stop codon readthrough is triggered. In an NMD-deficient mutant yeast, stable reporter alleles with more 3′ proximal stop codons could not be rendered unstable through Rli1-depletion, inferring defective Rli1 ribosome recycling is insufficient in itself to trigger mRNA instability. Mathematical modelling of a translation system including the effect of ribosome recycling and poly(A) tail shortening supports the hypothesis that impaired ribosome recycling from 5′ proximal stop codons may compromise initiation processes and thus destabilize the mRNA. A model is proposed wherein ribosomes undergo a maturation process during early elongation steps, and acquire competency to re-initiate on the same mRNA as translation elongation progresses beyond the very 5′ proximal regions of the mRNA. [ABSTRACT FROM AUTHOR]