Chronic intrahippocampal interleukin-1β overexpression in adolescence impairs hippocampal neurogenesis but not neurogenesis-associated cognition

Both neuroinflammation and adult hippocampal neurogenesis (AHN) are implicated in many neurodegenerative disorders as well as in neuropsychiatric disorders, which often become symptomatic during adolescence. A better knowledge of the impact that chronic neuroinflammation has on the hippocampus during the adolescent period could lead to the discovery of new therapeutics for some of these disorders. The hippocampus is particularly vulnerable to altered concentrations of the pro-inflammatory cytokine interleukin-1β (IL-1β), with elevated levels implicated in the aetiology of neurodegenerative disorders such as Alzheimer’s and Parkinson’s, and stress-related disorders such as depression. The effect of acutely and chronically elevated concentrations of hippocampal IL-1β have been shown to reduce AHN in adult rodents. However, the effect of exposure to chronic overexpression of hippocampal IL-1β during adolescence, a time of increased vulnerability, hasn’t been fully interrogated. Thus, in this study we utilized a lentiviral approach to induce chronic overexpression of IL-1β in the dorsal hippocampus of adolescent male Sprague Dawley rats for 5 weeks, during which time its impact on cognition and hippocampal neurogenesis were examined. A reduction in hippocampal neurogenesis was observed along with a reduced level of neurite branching on hippocampal neurons. However, there was no effect of IL-1β overexpression on performance in pattern separation, novel object recognition or spontaneous alternation in the Y maze. Our study has highlighted that chronic IL-1β overexpression in the hippocampus during the adolescent period exerts a negative impact on neurogenesis independent of cognitive performance, and suggests a degree of resilience of the adolescent hippocampus to inflammatory insult

SemEval-2013 task 4: Free paraphrases of noun compounds

Contains fulltext : 122615.pdf (publisher's version ) (Open Access

Genetic and Environmental Factors Associated With the Ganglion Cell Complex in a Healthy Aging British Cohort

IMPORTANCE: Measurement of ganglion cell complex (GCC) thickness may be more sensitive than current methods for glaucoma diagnosis and research. However, little is known about the factors influencing GCC thickness in the general population. OBJECTIVES: To investigate the heritability of and factors associated with GCC thickness in a healthy aging population. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional twin study was conducted from August 27, 2014, to March 31, 2016, among 1657 participants of white British ancestry from the TwinsUK study cohort without ocular pathologic conditions. Heritability analyses were conducted in 1432 twins (426 monozygous and 290 dizygous pairs). Association analyses were performed using univariable and multivariable stepwise linear regression models, taking family structure into account. Heritability analyses were conducted using maximum likelihood structural equation twin modeling. MAIN OUTCOMES AND MEASURES: Parameters measured included GCC thickness, autorefraction, intraocular pressure, blood pressure, body mass index, and cholesterol, creatinine, glucose, insulin, triglycerides, and urea levels. Estimated glomerular filtration rate was calculated using the Modification of Diet in Renal Disease formula. RESULTS: Among the 1657 participants (mean [SD] age, 56.0 [15.3] years; 89.5% women and 10.5% men), the mean [SD] inner GCC thickness was 96.0 [7.6] μm (95% CI, 95.1-96.2). In multivariable modeling, the mean inner GCC thickness was associated with advancing age (β, -0.14; P < .001), increased body mass index (β, -0.15; P = .001), spherical equivalent (β, 0.70; P < .001), and higher estimated glomerular filtration rate (β, 0.03; P = .02). A 1-U increase in age or body mass index was associated with a 0.14-µm and 0.15-µm decrease in GCC thickness, respectively (P < .001), while a 1-U increase in spherical equivalent or estimated glomerular filtration rate was associated with a 0.70-µm (P < .001) and 0.03-µm (P = .02) increase in GCC thickness, respectively. Ganglion cell complex thickness was not associated with sex, intraocular pressure, or diabetes. Age-adjusted GCC thickness was highly heritable, with additive genetic effects explaining 81% (95% CI, 78%-84%) of phenotypic variance and individual environmental factors explaining the remaining 19% (95% CI, 16%-22%). CONCLUSIONS AND RELEVANCE: Ganglion cell complex thickness appears to be highly heritable and further genetic analysis may help identify new biological pathways for glaucoma. The results suggest it may be important to account for age, body mass index, refractive error, and sex when using GCC thickness as a diagnostic tool. Replication of their results is required, as is further research to explain the association between renal function and GCC thickness

SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals

We present a brief overview of the main challenges in the extraction of semantic relations from English text, and discuss the shortcomings of previous data sets and shared tasks. This leads us to introduce a new task, which will be part of SemEval-2010: multi-way classification of mutually exclusive semantic relations between pairs of common nominals. The task is designed to compare different approaches to the problem and to provide a standard testbed for future research, which can benefit many applications in Natural Language Processing.

FacetGist

Given the large volume of technical documents available, it is crucial to automatically organize and categorize these documents to be able to understand and extract value from them. Towards this end, we introduce a new research problem called Facet Extraction. Given a collection of technical documents, the goal of Facet Extraction is to automatically label each document with a set of concepts for the key facets (e.g., application, technique, evaluation metrics, and dataset) that people may be interested in. Facet Extraction has numerous applications, including document summarization, literature search, patent search and business intelligence. The major challenge in performing Facet Extraction arises from multiple sources: concept extraction, concept to facet matching, and facet disambiguation. To tackle these challenges, we develop FacetGist, a framework for facet extraction. Facet Extraction involves constructing a graph-based heterogeneous network to capture information available across multiple local sentence-level features, as well as global context features. We then formulate a joint optimization problem, and propose an efficient algorithm for graph-based label propagation to estimate the facet of each concept mention. Experimental results on technical corpora from two domains demonstrate that Facet Extraction can lead to an improvement of over 25% in both precision and recall over competing schemes