Antidepressant Interactions with the NMDA NR1-1b Subunit

The targets for tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), and selective norepinephrine reuptake inhibitors (SNRIs) are known to be the serotonin and norepinephrine transport (reuptake) proteins which are embedded in presynaptic nerve terminals and function to bring these neurotransmitters from the synaptic cleft back into the presynaptic neuron. Using a combination of intrinsic and extrinsic fluorescence quenching, Stern-Volmer analysis, and protease protection assays, we have shown that therapeutics from each of these three classes of antidepressants bind to the extracellular S1S2 domain of the NR1-1b subunit of the NMDA receptor. These results are in agreement with recent work from our lab demonstrating the interaction of antidepressants with the S1S2 domain of the GluR2 subunit of the AMPA receptor, another member of the ionotropic glutamate receptor subfamily, as well as work from other labs, and continue the discussion of the involvement of ionotropic glutamate receptors in depression

User driven information extraction with LODIE

Information Extraction (IE) is the technique for transforming unstructured or semi-structured data into structured representation that can be understood by machines. In this paper we use a user-driven Information Extraction technique to wrap entity-centric Web pages. The user can select concepts and properties of interest from available Linked Data. Given a number of websites containing pages about the concepts of interest, the method will exploit (i) recurrent structures in the Web pages and (ii) available knowledge in Linked data to extract the information of interest from the Web pages

Table2Vec: Neural Word and Entity Embeddings for Table Population and Retrieval

Tables contain valuable knowledge in a structured form. We employ neural language modeling approaches to embed tabular data into vector spaces. Specifically, we consider different table elements, such caption, column headings, and cells, for training word and entity embeddings. These embeddings are then utilized in three particular table-related tasks, row population, column population, and table retrieval, by incorporating them into existing retrieval models as additional semantic similarity signals. Evaluation results show that table embeddings can significantly improve upon the performance of state-of-the-art baselines.Comment: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '19), 201

Challenging Disciplinary Boundaries in the First Year: A New Introductory Integrated Science Course for STEM Majors

To help undergraduates make connections among disciplines so they are able to approach, evaluate, and contribute to the solutions of important global problems, our campus has been focused on interdisciplinary research and education opportunities across the science, technology, engineering, and mathematics (STEM) disciplines. This paper describes the mobilization, planning, and implementation of a first-year interdisciplinary course for STEM majors that integrates key concepts found in traditional first-semester biology, chemistry, computer science, mathematics, and physics courses. This team-taught course, Integrated Quantitative Science (IQS), is half of a first-year student’s schedule in both semesters and is composed of a double lecture and a weekly lab and workshop. Features of this first-year course, including themes and concepts covered each semester, some of the materials developed, lessons learned, challenges, and preliminary measures of success are described

Challenging Disciplinary Boundaries in the First Year: A New Introductory Integrated Science Course for STEM Majors

To help undergraduates make connections among disciplines so they are able to approach, evaluate, and contribute to the solutions of important global problems, our campus has been focused on interdisciplinary research and education opportunities across the science, technology, engineering, and mathematics (STEM) disciplines. This paper describes the mobilization, planning, and implementation of a first-year interdisciplinary course for STEM majors that integrates key concepts found in traditional first-semester biology, chemistry, computer science, mathematics, and physics courses. This team-taught course, Integrated Quantitative Science (IQS), is half of a first-year student’s schedule in both semesters and is composed of a double lecture and a weekly lab and workshop. Features of this first-year course, including themes and concepts covered each semester, some of the materials developed, lessons learned, challenges, and preliminary measures of success are described

Results of the GREAT08 Challenge: an image analysis competition for cosmological lensing

We present the results of the Gravitational LEnsing Accuracy Testing 2008 (GREAT08) Challenge, a blind analysis challenge to infer weak gravitational lensing shear distortions from images. The primary goal was to stimulate new ideas by presenting the problem to researchers outside the shear measurement community. Six GREAT08 Team methods were presented at the launch of the Challenge and five additional groups submitted results during the 6-month competition. Participants analyzed 30 million simulated galaxies with a range in signal-to-noise ratio, point spread function ellipticity, galaxy size and galaxy type. The large quantity of simulations allowed shear measurement methods to be assessed at a level of accuracy suitable for currently planned future cosmic shear observations for the first time. Different methods perform well in different parts of simulation parameter space and come close to the target level of accuracy in several of these. A number of fresh ideas have emerged as a result of the Challenge including a re-examination of the process of combining information from different galaxies, which reduces the dependence on realistic galaxy modelling. The image simulations will become increasingly sophisticated in future GREAT Challenges, meanwhile the GREAT08 simulations remain as a benchmark for additional developments in shear measurement algorithm

Development of the Adolescent Preoccupation with Screens Scale

Abstract Background Although public health concerns have been raised regarding the detrimental health effects of increasing rates of electronic screen use among adolescents, such effects have been small. Instruments currently available tend to be lengthy, have a clinical research focus, and assess young people’s screen use on specific screen-based activities (e.g., TV, computer, or internet). None appear to address screen use across a broad range of screens, including mobile devices and screen-based activities. The objective was to develop a new and short self-report scale for investigating adolescents’ screen use across all screens and screen-based activities in non-clinical settings. Methods The Adolescent Preoccupation with Screens Scale (APSS) was developed over a three stage process. First, a review of the current literature and existing instruments was undertaken and suitable items identified. Second, the draft APSS was piloted with adolescents and item affectivity and discrimination indices were calculated. Third, a cross sectional school based online survey of 1967 Australian adolescents in grades 5 (10 years old), 7 (13 years) and 9 (15 years) from 25 randomly selected schools was conducted. Results Factor Analysis on a sub-sample of the data (n = 782) and Confirmatory Factor Analysis on the remaining sub-sample (n = 1185), supported a two-factor model. The first factor reflects adolescents’ mood management with screen use, and the second reflects a behavioural preoccupation. The measure demonstrated strong invariance across sex and across Grades 5, 7, and 9. Both factors displayed good internal consistency (α = .91 and .87, respectively). Sex and grade differences on both scales were investigated and boys in Grade 5 reported higher levels of both mood management and behavioural preoccupation with screens. There were no sex differences on mood management in Grades 7 and 9, but girls reported higher behavioural preoccupation in both these later grades. Conclusion The APSS provides researchers with a new, brief and robust measure of potentially problematic screen use across a wide array of screens, including mobile devices, so readily accessed during adolescence

Genetic Susceptibility on CagA-Interacting Molecules and Gene-Environment Interaction with Phytoestrogens: A Putative Risk Factor for Gastric Cancer

OBJECTIVES: To evaluate whether genes that encode CagA-interacting molecules (SRC, PTPN11, CRK, CRKL, CSK, c-MET and GRB2) are associated with gastric cancer risk and whether an interaction between these genes and phytoestrogens modify gastric cancer risk. METHODS: In the discovery phase, 137 candidate SNPs in seven genes were analyzed in 76 incident gastric cancer cases and 322 matched controls from the Korean Multi-Center Cancer Cohort. Five significant SNPs in three genes (SRC, c-MET and CRK) were re-evaluated in 386 cases and 348 controls in the extension phase. Odds ratios (ORs) for gastric cancer risk were estimated adjusted for age, smoking, H. pylori seropositivity and CagA strain positivity. Summarized ORs in the total study population (462 cases and 670 controls) were presented using pooled- and meta-analysis. Plasma concentrations of phytoestrogens (genistein, daidzein, equol and enterolactone) were measured using the time-resolved fluoroimmunoassay. RESULTS: SRC rs6122566, rs6124914, c-MET rs41739, and CRK rs7208768 showed significant genetic effects for gastric cancer in both the pooled and meta-analysis without heterogeneity (pooled OR = 3.96 [95% CI 2.05-7.65], 1.24 [95% CI = 1.01-1.53], 1.19 [95% CI = 1.01-1.41], and 1.37 [95% CI = 1.15-1.62], respectively; meta OR = 4.59 [95% CI 2.74-7.70], 1.36 [95% CI = 1.09-1.70], 1.20 [95% CI = 1.00-1.44], and 1.32 [95% CI = 1.10-1.57], respectively). Risk allele of CRK rs7208768 had a significantly increased risk for gastric cancer at low phytoestrogen levels (p interaction<0.05). CONCLUSIONS: Our findings suggest that SRC, c-MET and CRK play a key role in gastric carcinogenesis by modulating CagA signal transductions and interaction between CRK gene and phytoestrogens modify gastric cancer risk