Differential regional expression patterns of alpha-synuclein, TNF-alpha, and IL-1beta; and variable status of dopaminergic neurotoxicity in mouse brain after Paraquat treatment

BACKGROUND: Paraquat (1, 1-dimethyl-4, 4-bipyridium dichloride; PQ) causes neurotoxicity, especially dopaminergic neurotoxicity, and is a supposed risk factor for Parkinson's disease (PD). However, the cellular and molecular mechanisms of PQ-induced neurodegeneration are far from clear. Previous studies have shown that PQ induces neuroinflammation and dopaminergic cell loss, but the prime cause of those events is still in debate. METHODS: We examined the neuropathological effects of PQ not only in substantia nigra (SN) but also in frontal cortex (FC) and hippocampus of the progressive mouse (adult Swiss albino) model of PD-like neurodegeneration, using immunohistochemistry, western blots, and histological and biochemical analyses. RESULTS: PQ caused differential patterns of changes in cellular morphology and expression of proteins related to PD and neuroinflammation in the three regions examined (SN, FC and hippocampus). Coincident with behavioral impairment and brain-specific ROS generation, there was differential immunolocalization and decreased expression levels of tyrosine hydroxylase (TH) in the three regions, whereas α-synuclein immunopositivity increased in hippocampus, increased in FC and decreased in SN. PQ-induced neuroinflammation was characterized by area-specific changes in localization and appearances of microglial cells with or without activation and increment in expression patterns of tumor necrosis factor-α in the three regions of mouse brain. Expression of interleukin-1β was increased in FC and hippocampus but not significantly changed in SN. CONCLUSION: The present study demonstrates that PQ induces ROS production and differential α-synuclein expression that promotes neuroinflammation in microglia-dependent or -independent manners, and produces different patterns of dopaminergic neurotoxicity in three different regions of mouse brain

Dynamics of a methane hydrophobe in aqueous choline chloride solution: Insights from molecular dynamics simulations

Motion of hydrophobic moieties in solvent plays a crucial role in biomolecular functioning and is strongly influenced by the properties of the surrounding environment. To have a molecular-level picture of the dynamics of tiny hydrophobes, we simulate a methane molecule in different concentrations of aqueous choline chloride (ChCl) solution. Our analyses reveal slower translational dynamics of methane and the emergence of spatiotemporal heterogeneity at the timescales across which methane shows cage and jump motion. This results non-Gaussianity in the dynamics and it becomes increasingly pronounced with higher ChCl concentration. This illustrates more confined motion of methane inside the smaller and closely spaced cages. Hence, the jump percentage increases, and the jump length decreases. However, the maximum contribution to total diffusion comes from residual diffusion, which accounts for caging and small step displacements

News Analytics and Sentiment Analysis to Predict Stock Price

Abstract — Business news carries varied information of different companies. But in this rapidly moving world the number of news sources present is uncountable, and it’s humanly impossible to read and find all relevant information in the form of news to draw a conclusion timely to make an investment plan that returns maximum profit. In this paper, we have proposed a predictive model to predict sentiment around stock price. First the relevant real time news headlines and press-releases have been filtered from the large set of business news sources, and then they have been analyzed to predict the sentiment around companies. In order to find correlation between sentiment predicted from news and original stock price and to test efficient market hypothesis, we plot the sentiments of 15 odd companies over a period of 4 weeks. Our result shows an average accuracy score for identifying correct sentiment of around 70.1%. We also have plotted the errors of prediction for different companies which have brought out the RMSE and MAE of 30.3 % and 30.04% respectively and an enhanced F1 factor of 78.1%. The comparison between positive sentiment curve and stock price trends reveals 67 % co-relation between them, which indicates towards existence of a semi-strong to strong efficient market hypothesis

Locating Faults in Thyristor-Based LCC-HVDC Transmission Lines Using Single End Measurements and Boosting Ensemble

Most of the fault location methods in high voltage direct current (HVDC) transmission lines usemethods which require signals from both ends. It will be difficult to estimate fault location if the signal recorded is not correct due to communication problems.Hence a robust method is required which can locate fault with minimum error. In this work, faults are located using boosting ensembles in HVDC transmission lines based on single terminal direct current (DC) signals. The signals are processed to obtain input features that vary with the fault distance. These input features are obtained by taking maximum of half cycle current signals after fault and minimum of half cycle voltage signals after fault from the root mean square of DC signals. The input features are input to a boosting ensemble for estimating the location of fault. Boosting ensemble method attempts to correct the errors from the previous models and find outputs by combining all models. The boosting ensemble method has been also compared with the decision tree method and thebagging-based ensemble method. Fault locations are estimated using three methods and compared to obtain an optimal method. The boosting ensemble method has better performance than all the other methods in locating the faults. It also validated varying fault resistance, smoothing reactors, boundary faults, pole to ground faults and pole to pole faults. The advantage of the method is that no communication link is needed. Another advantage is that it allowsreach setting up to 99.9% and does not exhibitthe problem of over-fitting. Another advantage is that the percentage error in locating faults is within 1% and has a low realization cost. The proposed method can be implemented in HVDC transmission lines effectively as an alternative to overcome the drawbacks of traveling wave methods