Event-based hyperspace analogue to language for query expansion

Bag-of-words approaches to information retrieval (IR) are effective but assume independence between words. The Hyperspace Analogue to Language (HAL) is a cognitively motivated and validated semantic space model that captures statistical dependencies between words by considering their co-occurrences in a surrounding window of text. HAL has been successfully applied to query expansion in IR, but has several limitations, including high processing cost and use of distributional statistics that do not exploit syntax. In this paper, we pursue two methods for incorporating syntactic-semantic information from textual ‘events’ into HAL. We build the HAL space directly from events to investigate whether processing costs can be reduced through more careful definition of word co-occurrence, and improve the quality of the pseudo-relevance feedback by applying event information as a constraint during HAL construction. Both methods significantly improve performance results in comparison with original HAL, and interpolation of HAL and relevance model expansion outperforms either method alone

Beyond redundancies: a metric-invariant method for unsupervised feature selection

A fundamental goal of unsupervised feature selection is denoising, which aims to identify and reduce noisy features that are not discriminative. Due to the lack of information about real classes, denoising is a challenging task. The noisy features can disturb the reasonable distance metric and result in unreasonable feature spaces, i.e., the feature spaces in which common clustering algorithms cannot effectively find real classes. To overcome the problem, we make a primary observation that the relevance of features is intrinsic and independent of any metric scaling on the feature space. This observation implies that feature selection should be invariant, at least to some extent, with respect to metric scaling. In this paper, we clarify the necessity of considering the metric invariance in unsupervised feature selection and propose a novel model incorporating metric invariance. Our proposed method is motivated by the following observations: if the statistic that guides the unsupervised feature selection process is invariant with respect to possible metric scaling, the solution of this model will also be invariant. Hence, if a metric-invariant model can distinguish discriminative features from noisy ones in a reasonable feature space, it will also work on the unreasonable counterpart transformed from the reasonable one by metric scaling. A theoretical justification of the metric invariance of our proposed model is given and the empirical evaluation demonstrates its promising performance

Red wine polyphenols reverse depressive-like behaviors in mice induced by repeated corticosterone treatment

The aim of this study was to investigate the antidepressant-like effect of red wine phenolic extracts in mouse model exposed to exogenous corticosterone. The results showed that 3-week corticosterone injections caused depression-like behavior in mice, as indicated by the significant decrease in sucrose consumption and increase immobility time in the forced swimming test (FST). Red wine phenolic extracts treatment significantly reduced serum corticosterone levels. Moreover, it was found that red wine phenolic extract increased the brain-derived neurotrophic factor protein (BNDF) and tropomyosin-related kinase B (TrkB) phosphorylation and cAMP-responsive element binding protein (CREB) phosphorylation levels in the hippocampus and prefrontal cortex. However, K252a, an inhibitor of TrkB, completely abolished those antidepressant-like effects. These results suggested that the red wine phenolic extracts produce an antidepressant-like effect in corticosteronetreated mice, at least in part, which is possibly mediated by modulating hypothalamic-pituitary-adrenal (HPA) axis, BDNF, TrkB and CREB phosphorylation levels in the brain region of mice

Antidepressant-like activity of red wine phenolic extracts in repeated corticosterone-induced depression mice via BDNF/TrkB/CREB signaling pathway

The aim of this study was to investigate the antidepressant-like effect of red wine phenolic extracts in mouse model exposed to exogenous corticosterone. The results showed that 3-week corticosterone injections caused depression-like behavior in mice, as indicated by the significant decrease in sucrose consumption and increase immobility time in the forced swim test. Red wine phenolic extracts treatment significantly reduced serum corticosterone levels. Moreover, it was found that red wine phenolic extract increased the brain-derived neurotrophic factor protein (BNDF) and Tropomyosin-related kinase B (TrkB) phosphorylation and cAMP-responsive element binding protein (CREB) phosphorylation levels in the hippocampus and prefrontal cortex. However, K252a, an inhibitor of TrkB, completely abolished those antidepressant-like effects. These results suggested that the red wine phenolic extracts produce an antidepressant-like effect in corticosterone-treated mice, at least in part, which is possibly mediated by modulating hypothalamic-pituitary-adrenal (HPA) axis, BDNF, TrkB and CREB phosphorylation levels in the brain region of mice

An Investigation of the Anti-Depressive Properties of Phenylpropanoids and Flavonoids in <i>Hemerocallis citrina</i> Baroni

The World Health Organization predicts that over the next several years, depression will become the most important mental health issue globally. Growing evidence shows that the flower buds of Hemerocallis citrina Baroni (H. citrina) possess antidepressant properties. In the search for new anti-depression drugs, a total of 15 phenylpropanoids and 22 flavonoids were isolated and identified based on spectral data (1D and 2D NMR, HR-ESI-MS, UV) from H. citrina. Among them, compound 8 was a novel compound, while compounds 1–4, 6, 9, 10, 15, 17, 24–26, 28, and 37 were isolated for the first time from Hemerocallis genus. To study the antidepressant activity of phenylpropanoids and flavonoids fractions from H. citrina, macroporous resin was used to enrich them under the guidance of UV characteristics. UHPLC-MS/MS was applied to identify the constituents of the enriched fractions. According to behavioral tests and biochemical analyses, it showed that phenylpropanoid and flavonoid fractions from H. citrina can improve the depressive-like mental state of chronic unpredictable mild stress (CUMS) rats. This might be accomplished by controlling the amounts of the inflammatory proteins IL-6, IL-1β, and TNF-α in the hippocampus as well as corticosterone in the serum. Thus, the monomer compounds were tested for their anti-neuroinflammatory activity and their structure–activity relationship was discussed in further detail

Antidepressant-like activity of red wine phenolic extracts in repeated corticosterone-induced depression mice via BDNF/TrkB/CREB signaling pathway

The aim of this study was to investigate the antidepressant-like effect of red wine phenolic extracts in mouse model exposed to exogenous corticosterone. The results showed that 3-week corticosterone injections caused depression-like behavior in mice, as indicated by the significant decrease in sucrose consumption and increase immobility time in the forced swim test. Red wine phenolic extracts treatment significantly reduced serum corticosterone levels. Moreover, it was found that red wine phenolic extract increased the brain-derived neurotrophic factor protein (BNDF) and Tropomyosin-related kinase B (TrkB) phosphorylation and cAMP-responsive element binding protein (CREB) phosphorylation levels in the hippocampus and prefrontal cortex. However, K252a, an inhibitor of TrkB, completely abolished those antidepressant-like effects. These results suggested that the red wine phenolic extracts produce an antidepressant-like effect in corticosterone-treated mice, at least in part, which is possibly mediated by modulating hypothalamic-pituitary-adrenal (HPA) axis, BDNF, TrkB and CREB phosphorylation levels in the brain region of mice