Encouraging Dialogue around Social Issues with Latinx Students Through Literature Discussion and Culturally Relevant Literature

This teacher research study examines literature discussions with fourth and fifth grade Latinx students about books that reflect Latinx experiences. For this study, the following questions are explored (1) What social issues do students discuss in literature groups? (2) How do literary response strategies influence student dialogue? And (3) How does my theoretical frame influence my decision making as a teacher? Theories that informed the construction of the literature discussions and the decision making occurring throughout the study are examined closely. The theories intertwine and bridge education and students’ experiences as a resource in learning more about the educational setting. In this study, the discussions of students and the literature response strategies are explored as the data is analyzed to examine the student discussions around issues of immigration, family separation, borders, and so much more. The findings in this study indicate that the experiences of Latinx students are integral to the educational setting and an education that invites who they are enhances their learning experiences. Latinx students are eager for learning opportunities that invite their voices and stories. It is through the construction and assessment of the educational setting that educators can promote culturally responsive, relevant, and sustaining teaching experiences that go beyond the classroom setting. Latinx students build relationships with each other and their teachers as they engage in discussions that allow them to share and learn with each other. This study is a reminder of the crucial role teachers play in creating such powerful spaces and the value that Latinx students bring into the classroom when invited to discuss, engage, and create powerful learning experiences

A Methodology and Tool for Rapid Prototyping of Data Warehouses using Data Mining: Application to Birds Biodiversity

International audienceData Warehouses (DWs) are large repositories of data aimed at supporting the decision-making process by enabling flexible and interactive analyses via OLAP systems. Rapid prototyping of DWs is necessary when OLAP applications are complex. Some work about the integration of Data Mining and OLAP systems has been done to enhance OLAP operators with mined indicators, and/or to define the DW schema. However, to best of our knowledge, prototyping methods for DWs do not support this kind of integration. Then, in this paper we present a new prototyping methodology for DWs, extending [3], where DM methods are used to define the DW schema. We validate our approach on a real data set concerning bird biodiversity

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

Global, regional, national, and selected subnational levels of stillbirths, neonatal, infant, and under-5 mortality, 1980�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background Established in 2000, Millennium Development Goal 4 (MDG4) catalysed extraordinary political, financial, and social commitments to reduce under-5 mortality by two-thirds between 1990 and 2015. At the country level, the pace of progress in improving child survival has varied markedly, highlighting a crucial need to further examine potential drivers of accelerated or slowed decreases in child mortality. The Global Burden of Disease 2015 Study (GBD 2015) provides an analytical framework to comprehensively assess these trends for under-5 mortality, age-specific and cause-specific mortality among children under 5 years, and stillbirths by geography over time. Methods Drawing from analytical approaches developed and refined in previous iterations of the GBD study, we generated updated estimates of child mortality by age group (neonatal, post-neonatal, ages 1�4 years, and under 5) for 195 countries and territories and selected subnational geographies, from 1980�2015. We also estimated numbers and rates of stillbirths for these geographies and years. Gaussian process regression with data source adjustments for sampling and non-sampling bias was applied to synthesise input data for under-5 mortality for each geography. Age-specific mortality estimates were generated through a two-stage age�sex splitting process, and stillbirth estimates were produced with a mixed-effects model, which accounted for variable stillbirth definitions and data source-specific biases. For GBD 2015, we did a series of novel analyses to systematically quantify the drivers of trends in child mortality across geographies. First, we assessed observed and expected levels and annualised rates of decrease for under-5 mortality and stillbirths as they related to the Soci-demographic Index (SDI). Second, we examined the ratio of recorded and expected levels of child mortality, on the basis of SDI, across geographies, as well as differences in recorded and expected annualised rates of change for under-5 mortality. Third, we analysed levels and cause compositions of under-5 mortality, across time and geographies, as they related to rising SDI. Finally, we decomposed the changes in under-5 mortality to changes in SDI at the global level, as well as changes in leading causes of under-5 deaths for countries and territories. We documented each step of the GBD 2015 child mortality estimation process, as well as data sources, in accordance with the Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, 5·8 million (95 uncertainty interval UI 5·7�6·0) children younger than 5 years died in 2015, representing a 52·0% (95% UI 50·7�53·3) decrease in the number of under-5 deaths since 1990. Neonatal deaths and stillbirths fell at a slower pace since 1990, decreasing by 42·4% (41·3�43·6) to 2·6 million (2·6�2·7) neonatal deaths and 47·0% (35·1�57·0) to 2·1 million (1·8-2·5) stillbirths in 2015. Between 1990 and 2015, global under-5 mortality decreased at an annualised rate of decrease of 3·0% (2·6�3·3), falling short of the 4·4% annualised rate of decrease required to achieve MDG4. During this time, 58 countries met or exceeded the pace of progress required to meet MDG4. Between 2000, the year MDG4 was formally enacted, and 2015, 28 additional countries that did not achieve the 4·4% rate of decrease from 1990 met the MDG4 pace of decrease. However, absolute levels of under-5 mortality remained high in many countries, with 11 countries still recording rates exceeding 100 per 1000 livebirths in 2015. Marked decreases in under-5 deaths due to a number of communicable diseases, including lower respiratory infections, diarrhoeal diseases, measles, and malaria, accounted for much of the progress in lowering overall under-5 mortality in low-income countries. Compared with gains achieved for infectious diseases and nutritional deficiencies, the persisting toll of neonatal conditions and congenital anomalies on child survival became evident, especially in low-income and low-middle-income countries. We found sizeable heterogeneities in comparing observed and expected rates of under-5 mortality, as well as differences in observed and expected rates of change for under-5 mortality. At the global level, we recorded a divergence in observed and expected levels of under-5 mortality starting in 2000, with the observed trend falling much faster than what was expected based on SDI through 2015. Between 2000 and 2015, the world recorded 10·3 million fewer under-5 deaths than expected on the basis of improving SDI alone. Interpretation Gains in child survival have been large, widespread, and in many places in the world, faster than what was anticipated based on improving levels of development. Yet some countries, particularly in sub-Saharan Africa, still had high rates of under-5 mortality in 2015. Unless these countries are able to accelerate reductions in child deaths at an extraordinary pace, their achievement of proposed SDG targets is unlikely. Improving the evidence base on drivers that might hasten the pace of progress for child survival, ranging from cost-effective intervention packages to innovative financing mechanisms, is vital to charting the pathways for ultimately ending preventable child deaths by 2030. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY license

Reducing eIF4E-eIF4G interactions restores the balance between protein synthesis and actin dynamics in fragile X syndrome model mice.

Fragile X syndrome (FXS) is the most common form of inherited intellectual disability and autism spectrum disorder. FXS is caused by silencing of the <i>FMR1</i> gene, which encodes fragile X mental retardation protein (FMRP), an mRNA-binding protein that represses the translation of its target mRNAs. One mechanism by which FMRP represses translation is through its association with cytoplasmic FMRP-interacting protein 1 (CYFIP1), which subsequently sequesters and inhibits eukaryotic initiation factor 4E (eIF4E). CYFIP1 shuttles between the FMRP-eIF4E complex and the Rac1-Wave regulatory complex, thereby connecting translational regulation to actin dynamics and dendritic spine morphology, which are dysregulated in FXS model mice that lack FMRP. Treating FXS mice with 4EGI-1, which blocks interactions between eIF4E and eIF4G, a critical interaction partner for translational initiation, reversed defects in hippocampus-dependent memory and spine morphology. We also found that 4EGI-1 normalized the phenotypes of enhanced metabotropic glutamate receptor (mGluR)-mediated long-term depression (LTD), enhanced Rac1-p21-activated kinase (PAK)-cofilin signaling, altered actin dynamics, and dysregulated CYFIP1/eIF4E and CYFIP1/Rac1 interactions in FXS mice. Our findings are consistent with the idea that an imbalance in protein synthesis and actin dynamics contributes to pathophysiology in FXS mice, and suggest that targeting eIF4E may be a strategy for treating FXS

Dibromopinocembrin and Dibromopinostrobin Are Potential Anti-Dengue Leads with Mild Animal Toxicity

10.3390/molecules25184154Molecules2518415

In Online Structure Learning for Markov Logic Networks

Abstract. Most existing learning methods for Markov Logic Networks (MLNs) use batch training, which becomes computationally expensive and eventually infeasible for large datasets with thousands of training examples which may not even all fit in main memory. To address this issue, previous work has used online learning to train MLNs. However, they all assume that the model’s structure (set of logical clauses) is given, and only learn the model’s parameters. However, the input structure is usually incomplete, so it should also be updated. In this work, we present OSL—the first algorithm that performs both online structure and parameter learning for MLNs. Experimental results on two realworld datasets for natural-language field segmentation show that OSL outperforms systems that cannot revise structure.

The mixture of Ganoderma lucidum and Cordyceps militaris: Chemical composition and protective effect against oxidative stress

There is a growing demand for the consumption of medicinal mushrooms and their products. Ganoderma lucidum and Cordyceps militaris are two important medicinal mushrooms with significant pharmacological activities. In this study, we aim to develop a preparation of the extracts of these two mushrooms, and investigate its composition, antioxidant activities, and protective effects against oxidative damage. Liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (LC-QTOF MS) was employed to analyze the chemical profiles of the mixture. A total of 94 compounds were identified as belonging to phenolic acids, flavonoids, triterpenes, and nucleosides. In addition, HPLC-DAD was used to quantify major compounds. Ferulic and cinnamic acids were predominant in the phenolic acid groups, with corresponding concentrations of 0.41 and 0.29 mg/g. The concentration of ganoderic acid A was 0.08 mg/g, and the contents of adenosine and cordycepin were 0.53 and 0.14 mg/g, respectively. The mixture could scavenge free radicals and reduce ferric ions in vitro. The preparation also showed nontoxic but proliferative effects on human fibroblast cells. In addition, it could protect fibroblasts against oxidative stress, reducing 21–22% of cell death in the presence of H2O2. These findings provide more information on the applications of medicinal mushrooms in the functional food and pharmaceutical industries