Combining non-negative matrix factorization with graph Laplacian regularization for predicting drug-miRNA associations based on multi-source information fusion.

Increasing evidences suggest that miRNAs play a key role in the occurrence and progression of many complex human diseases. Therefore, targeting dysregulated miRNAs with small molecule drugs in the clinical has become a new treatment. Nevertheless, it is high cost and time-consuming for identifying miRNAs-targeted with drugs by biological experiments. Thus, more reliable computational method for identification associations of drugs with miRNAs urgently need to be developed. In this study, we proposed an efficient method, called GNMFDMA, to predict potential associations of drug with miRNA by combining graph Laplacian regularization with non-negative matrix factorization. We first calculated the overall similarity matrices of drugs and miRNAs according to the collected different biological information. Subsequently, the new drug-miRNA association adjacency matrix was reformulated based on the K nearest neighbor profiles so as to put right the false negative associations. Finally, graph Laplacian regularization collaborative non-negative matrix factorization was used to calculate the association scores of drugs with miRNAs. In the cross validation, GNMFDMA obtains AUC of 0.9193, which outperformed the existing methods. In addition, case studies on three common drugs (i.e., 5-Aza-CdR, 5-FU and Gemcitabine), 30, 31 and 34 of the top-50 associations inferred by GNMFDMA were verified. These results reveal that GNMFDMA is a reliable and efficient computational approach for identifying the potential drug-miRNA associations.

Combining K Nearest Neighbor With Nonnegative Matrix Factorization for Predicting Circrna-Disease Associations.

Accumulating evidences show that circular RNAs (circRNAs) play an important role in regulating gene expression, and involve in many complex human diseases. Identifying associations of circRNA with disease helps to understand the pathogenesis, treatment and diagnosis of complex diseases. Since inferring circRNA-disease associations by biological experiments is costly and time-consuming, there is an urgently need to develop a computational model to identify the association between them. In this paper, we proposed a novel method named KNN-NMF, which combines K nearest neighbors with nonnegative matrix factorization to infer associations between circRNA and disease (KNN-NMF). Frist, we compute the Gaussian Interaction Profile (GIP) kernel similarity of circRNA and disease, the semantic similarity of disease, respectively. Then, the circRNA-disease new interaction profiles are established using weight K nearest neighbors to reduce the false negative association impact on prediction performance. Finally, Nonnegative Matrix Factorization is implemented to predict associations of circRNA with disease. The experiment results indicate that the prediction performance of KNN-NMF outperforms the competing methods under five-fold cross-validation. Moreover, case studies of two common diseases further show that KNN-NMF can identify potential circRNA-disease associations effectively.

Globally Adaptive Neural Network Tracking for Uncertain Output-Feedback Systems.

This article investigates the problem of global neural network (NN) tracking control for uncertain nonlinear systems in output feedback form under disturbances with unknown bounds. Compared with the existing NN control method, the differences of the proposed scheme are as follows. The designed actual controller consists of an NN controller working in the approximate domain and a robust controller working outside the approximate domain, in addition, a new smooth switching function is designed to achieve the smooth switching between the two controllers, in order to ensure the globally uniformly ultimately bounded of all closed-loop signals. The Lyapunov analysis method is used to strictly prove the global stability under the combined action of unmeasured states and system uncertainties, and the output tracking error is guaranteed to converge to an arbitrarily small neighborhood through a reasonable selection of design parameters. A numerical example and a practical example were put forward to verify the effectiveness of the control strategy.

A weighted non-negative matrix factorization approach to predict potential associations between drug and disease.

BACKGROUND: Associations of drugs with diseases provide important information for expediting drug development. Due to the number of known drug-disease associations is still insufficient, and considering that inferring associations between them through traditional in vitro experiments is time-consuming and costly. Therefore, more accurate and reliable computational methods urgent need to be developed to predict potential associations of drugs with diseases. METHODS: In this study, we present the model called weighted graph regularized collaborative non-negative matrix factorization for drug-disease association prediction (WNMFDDA). More specifically, we first calculated the drug similarity and disease similarity based on the chemical structures of drugs and medical description information of diseases, respectively. Then, to extend the model to work for new drugs and diseases, weighted [Formula: see text] nearest neighbor was used as a preprocessing step to reconstruct the interaction score profiles of drugs with diseases. Finally, a graph regularized non-negative matrix factorization model was used to identify potential associations between drug and disease. RESULTS: During the cross-validation process, WNMFDDA achieved the AUC values of 0.939 and 0.952 on Fdataset and Cdataset under ten-fold cross validation, respectively, which outperforms other competing prediction methods. Moreover, case studies for several drugs and diseases were carried out to further verify the predictive performance of WNMFDDA. As a result, 13(Doxorubicin), 13(Amiodarone), 12(Obesity) and 12(Asthma) of the top 15 corresponding candidate diseases or drugs were confirmed by existing databases. CONCLUSIONS: The experimental results adequately demonstrated that WNMFDDA is a very effective method for drug-disease association prediction. We believe that WNMFDDA is helpful for relevant biomedical researchers in follow-up studies.

Asymptotic Tracking Control of State-Constrained Nonlinear Systems With Time-Varying Powers.

This article investigates the asymptotic tracking control problem for full-state-constrained nonlinear systems with unknown time-varying powers. By introducing a nonlinear state-dependent transformation, a continuous bounded scalar function, and lower and higher powers into adding a power integrator control design, full-state constraints are skillfully handled without imposing frequently used feasibility conditions in traditional barrier Lyapunov function-based methods, and an asymptotic tracking control design is provided. It is proved that all the closed-loop signals are bounded, full-state constraints are not transgressed, and the asymptotic tracking is achieved.

Adaptive Fuzzy Asymptotic Tracking Control of State-Constrained High-Order Nonlinear Time-Delay Systems and Its Applications.

This article discusses the adaptive fuzzy asymptotic tracking control for high-order nonlinear time-delay systems with full-state constraints. Fuzzy-logic systems and a separation principle are utilized to relax growth assumptions imposed on unknown nonlinearities. The adverse effect caused by unknown time delays is eliminated by choosing appropriate Lyapunov-Krasovskii functionals. By integrating nonlinear-transformed functions with a key coordinate transformation into the control design and constructing a specific compact set on the initial values of system states, the desired trajectory and parameter estimates, it is rigorously proved that all closed-loop signals are semiglobally bounded, the fuzzy approximation is valid, the full-state constraints are not violated without feasibility conditions on virtual controllers, and asymptotic tracking is achieved. The effectiveness and advantages of this control scheme are confirmed by two examples including a single-link robotic system.

Removing Feasibility Conditions on Adaptive Neural Tracking Control of Nonlinear Time-Delay Systems With Time-Varying Powers, Input, and Full-State Constraints.

This article investigates the tracking control for input and full-state-constrained nonlinear time-delay systems with unknown time-varying powers, whose nonlinearities do not impose any growth assumption. By utilizing the auxiliary control signal and nonlinear state-dependent transformation (NSDT) to counteract the effect of input saturation and cope with full-state constraints, respectively, and then introducing lower and higher powers and Lyapunov-Krasovskii (L-K) functionals in control design together with the adaptive neural-networks (NNs) method, an adaptive neural tracking control design is provided without feasibility conditions. It is proved that NNs approximation is valid, all the closed-loop signals are semiglobally bounded, and input and full-state constraints are not violated.

Further Results on Adaptive Practical Tracking for High-Order Nonlinear Systems With Full-State Constraints.

In this article, an adaptive practical tracking control scheme is presented for full-state constrained high-order nonlinear systems. By skillfully introducing the adaptive gain, nonlinear transformed functions and sign functions into control design, a novel continuous state-feedback controller is constructed without imposing restrictive approximation techniques and feasibility conditions. Under mild assumptions, the boundedness of all the closed-loop signals can be guaranteed, full-state constraints are not transgressed for all time, and the tracking error tends to an arbitrarily small region of zero in a finite time.

Adaptive Neural Output-Feedback Decentralized Control for Large-Scale Nonlinear Systems With Stochastic Disturbances.

This paper addresses the problem of adaptive neural output-feedback decentralized control for a class of strongly interconnected nonlinear systems suffering stochastic disturbances. An state observer is designed to approximate the unmeasurable state signals. Using the approximation capability of radial basis function neural networks (NNs) and employing classic adaptive control strategy, an observer-based adaptive backstepping decentralized controller is developed. In the control design process, NNs are applied to model the uncertain nonlinear functions, and adaptive control and backstepping are combined to construct the controller. The developed control scheme can guarantee that all signals in the closed-loop systems are semiglobally uniformly ultimately bounded in fourth-moment. The simulation results demonstrate the effectiveness of the presented control scheme.

Damage to Hippocampus of Rats after Being Exposed to Infrasound.

OBJECTIVE: The objective was to observe damage of hippocampus in rats after exposure to infrasound, and to assess HSP70 expression in hippocampus. METHODS: SD rats in the experimental group were exposed to 140 dB (8 Hz) infrasound for 2 h per day for 3 days. The morphology of the hippocampus was examined by transmission electronic microscopic (TEM). Cell apoptosis was observed by TUNEL staining at 0 h, 24 h, 48 h, and 2 w after exposure. HSP70 expression was detected by immunohistochemistry (IHC) and Western blotting (WB). RESULTS: TEM showed that hippocampus was significantly damaged by exposure, and exhibited recovery 1 week after exposure. The TUNEL data showed that neuronal apoptosis after exposure was significantly higher than in the control rats at 24 h and 48 h, and the apoptotic cells decreased one week after exposure. IHC and WB showed HSP70 expression was significantly higher in the exposed rats, peaked at 24 h. CONCLUSION: Exposure to 140 dB (8 Hz) infrasound for 2 h per day for 3 days appeared to induce damage to the hippocampus of rats, based on changes in ultrastructure and increased cell apoptosis. However, recovery from the damage occurred overtime. HSP70 expression also increased after the exposure and decreased by 48.

[Effect of Bushen Huoxue Compound on Retinal Müller Cells in High Glucose or AGEs Conditions].

OBJECTIVE: To explore the effect of Bushen Huoxue Compound (BHC) on lactate dehydrogenase (LDH) leakage, expressions of vascular endothelial growth factor (VEGF) and VEGF mRNA in retinal Muller cells under high glucose condition or advanced glycosylation end products (AGEs) condition by using serum pharmacological method. METHODS: The retinal Müller cells of 5-7 days post-natal Sprague Dawley (SD) rats were cultured with modified enzyme-digestion method. Purified retinal Muller cells were cultured in normal conditions, high glucose condition (50 mmol/L) or AGEs (50 mg/L and 100 mg/L) conditions, and BHC-containing serum was added to culture medium. The LDH leakage and VEGF expressions were measured by enzyme-linked immunosorbent assay (ELISA). In addition, the relative expression of VEGF mRNA was tested by reverse transcription polymerase chain reaction (RT-PCR). RESULTS: Compared with the normal control group, expressions of VEGF and VEGF mRNA were significantly increased in the high glucose group, the low dose AGEs group and the high dose AGEs group (all P < 0.01). The LDH leakage was obviously increased in the high dose AGEs group, when compared with the normal control group and the high glucose group (P < 0.01). The LDH leakage, expressions of VEGF and VEGF mRNA were obviously decreased by BHC-containing serum both in high glucose and AGEs conditions (P < 0.05, P < 0.01). BHC-containing serum had no significant effect on the LDH leakage and expressions of VEGF and VEGF mRNA in normal conditions (P > 0.05). CONCLUSIONS: AGEs intervention could obviously lower the stability of Müller cell membrane. Up-regulated expressions of VEGF and VEGF mRNA in cultured Müller cells could be induced by AGEs or high glucose. BHC-containing serum could stabilize the stability of Müller cell membrane, inhibit the transcription of VEGF mRNA and decrease the protein expression of VEGF, which might be one of important mechanisms for preventing and treating diabetic retinopathy.

Further results on global state feedback stabilization of nonlinear high-order feedforward systems.

In this paper, by introducing a combined method of sign function, homogeneous domination and adding a power integrator, and overcoming several troublesome obstacles in the design and analysis, the problem of state feedback control for a class of nonlinear high-order feedforward systems with the nonlinearity's order being relaxed to an interval rather than a fixed point is solved.

Electromagnetic-pulse-induced activation of p38 MAPK pathway and disruption of blood-retinal barrier.

The blood-retinal barrier (BRB) is critical for maintaining retina homeostasis and low permeability. In this study, we evaluated the effects of electromagnetic pulse (EMP) exposure on the permeability of BRB, alterations of tight junction (TJ) proteins of BRB and if any, involvement of mitogen-activated protein kinase (MAPK) pathway. Male Sprague-Dawley (SD) rats and RF/6A cells which were pretreated with or without MAPKs inhibitors were sham exposed or exposed to EMP at 200kV/m for 200 pulses. The alteration of BRB permeability was examined through fluorescence microscope and quantitatively assessed using Evans blue (EB) and endogenous albumin as tracers. The expressions of TJ proteins and some signaling molecules of MAPK pathway were measured by Western blots. The observations were that EMP exposure resulted in increased BRB permeability concurrent with the decreased expressions of occludin and claudin-5, which were correlated with the increased expressions of phospho-p38, phospho-JNK and phospho-ERK and could be blocked when pretreated with p38 MAPK inhibitor. Thus, the results suggested that the alterations of occludin and claudin-5 may play an important role in the disruption of TJs, which may lead to the transient breakdown of BRB after EMP exposure with the involvement of p38 MAPK pathway through phosphorylation of signaling molecules.

[Effects of electromagnetic pulse exposure on the permeability of inner blood-retinal barrier model in vitro].

OBJECTIVE: To establish the inner blood-retinal barrier (BRB) model in vitro by co-culturing RF/6A cells and C6 cells and to investigate the effects of EMP (200 kV/m, 200 pulses) exposure on the permeability of the inner BRB model in vitro. METHODS: RF/6A cells and C6 cells were co-cultured on transwell, and the characteristic of the inner BRB model was assessed by detecting transendothelial electrical resistance (TEER) and the permeability of horseradish peroxidase (HRP). The co-cultured model was exposed or sham exposed to the EMP (200 kV/m 200 pulses) for 0.5, 3, 6, 12, 24 h in vitro, then TEER and the permeability of HRP were measured for studying the effects of EMP on the permeability of inner BRB model in vitro. RESULTS: TEER value (145 Ωcm(2)) of the co-culturing inner BRB model significantly increased, as compared to that of RF/6A cells alone model (P < 0.05) on the 6th day after inoculation. There was significant difference of permeability of HRP between the co-culturing inner BRB model and RF/6A cells alone model (P < 0.05). The ability of inhibiting large molecular materials in the co-culturing inner BRB model enhanced. The TEER value decreased and the permeability of HRP increased as compared to the sham group at 0.5, 3, 6 h after the exposure. CONCLUSION: The inner BRB model by co-culturing RF/6A cells and C6 cells in vitro is efficient and suitable to study the alterations of the restricted permeability function of the inner BRB. EMP (200 kV/m for 200 pulses) could induce the enhanced permeability of the inner BRB model in vitro.

[Effect of drug-serum with Chinese drugs for nourishing shen and activating blood on the glutamate release in purified retinal ganglion cells cultured in high-glucose conditions].

OBJECTIVE: To investigate the impacts of steady high-glucose or fluctuated glucose conditions on glutamate (Glu) release in purified retinal ganglion cells (RGCs) cultured in vitro, and the effect of serum contained Chinese drugs for nourishing Shen and activating blood (S-NSAB) on it. METHODS: RGCs of neonatal SD rats were cultured by antibody combined two-step purified method in different conditions: the simulated normal condition, the steady high-glucose condition and the fluctuated glucose condition, and they were intervened with S-NSAB. Thereby, the experiment was carried out in 6 groups, i.e. the normal control group (A), the S-NSAB intervened group (B), the steady high-glucose cultured group (C), the steady high-glucose cultured and S-NSAB intervened group (D), the fluctuated glucose cultured group (E), and the fluctuated glucose cultured and S-NSAB intervened group (F). Content of Glu in the extracellular fluid was detected at 24, 48 and 72 h after intervention with a full-automatic biochemical analyzer. And the data obtained were statistically analyzed with SPSS 13.0 soft ware. RESULTS: Release of Glu at 24 h after intervention in Group E (256.33 +/- 25.73 mg/L) was obviously higher than that in Group A and Group C (134.22 +/- 9.14 mg/L and 141. 17 +/- 22.13 mg/L, P < 0.05); at 24 h and 72 h in Group B (124.50 +/- 10.30 mg/L and 30. 17 +/- 2.97 mg/L) was obviously lower than in Group A respectively (P < 0.05); in Group D at 24 h (127.50 +/- 16.94 mg/L), 48 h (26.17 +/- 3.99 mg/L) and 72 h (27.67 +/- 3.49 mg/L) were lower than in Group C; in Group F at 24 h (228.33 +/- 18.41 mg/L) and 72 h (28.00 +/- 2.41 mg/L) were lower than in Group E respectively at the corresponding time points. CONCLUSIONS: Fluctuated glucose condition could obviously increase the Glu release of RGCs, to cause extracellular large amount Glu accumulation, which induces the exciting neurotoxicity to RGCs and finally to aggravate the injury on cells. S-NSAB could reduce the Glu release to some extent in the steady-high or fluctuated glucose conditions, diminish the injury of RGCs from exciting neurotoxicity of Glu, and it might be one of the intervening pathways of Chinese drugs for NSAB in preventing and treating DRP.

[Effect of serum contained Chinese drugs for nourishing Shen and activating blood on activity of purified retinal ganglion cells cultured in high glucose medium].

OBJECTIVE: To investigate the effect of serum contained Chinese drugs for nourishing Shen and activating blood (S-NSAB) on activity of purified retinal ganglion cells (RGCs) cultured in high glucose medium. METHODS: Purified RGCs of SD rats were cultured in stimulative stable high glucose (50 mmol/L) condition (SHG) and fluctuated glucose condition (FGC) separately, they were intervened with S-NSAB, and the lactate dehydrogenase (LDH) leakage was detected by spectrophotometer for estimating the activity of RGCs. RESULTS: LDH leakage (U/L) in SHG culture was 1 349.17 +/- 215.50 at 24 h, 1220.24 +/- 124.53 at 48 h and 1982.14 +/- 219.03 at 72 h, all significantly lower than that in normal control at the corresponding time points (1628.10 +/-122.10, 1484.13 +/- 127.55 and 2155.75 +/- 140.44, respectively, P<0.05), whereas it was obviously higher in FGC culture at 72 h (2299.60 +/- 88.35), showing that LDH leakage in FGC was significantly higher than that in SHG at the corresponding time points (P<0.05). The LDH leakage was obviously decreased by Chinese medicine intervention with S-NSAB both in SHG at 72 h (1797.62 +/- 146.40) and in FGC at 48 h (1259.92 +/- 87.74) and 72 h (1940.40 +/- 155.47), the difference between pre- and post-intervention was significant (P<0.05). CONCLUSION: Fluctuated glucose conditions of culture medium could obviously damage the membranous stability of RGCs to enhance their permeability and lower the activity of cells; S-NSAB could improve these abnormalities in either SHG or FGC condition, which may be one of the important mechanisms of Chinese formula for nourishing Shen and activating blood in preventing and treating diabetic retinopathy.