Engaging Undergraduates in Science Research: Not Just About Faculty Willingness.

Despite the many benefits of involving undergraduates in research and the growing number of undergraduate research programs, few scholars have investigated the factors that affect faculty members' decisions to involve undergraduates in their research projects. We investigated the individual factors and institutional contexts that predict faculty members' likelihood of engaging undergraduates in their research project(s). Using data from the Higher Education Research Institute's 2007-2008 Faculty Survey, we employ hierarchical generalized linear modeling to analyze data from 4,832 science, technology, engineering, and mathematics (STEM) faculty across 194 institutions to examine how organizational citizenship behavior theory and social exchange theory relate to mentoring students in research. Key findings show that faculty who work in the life sciences and those who receive government funding for their research are more likely to involve undergraduates in their research project(s). In addition, faculty at liberal arts or historically Black colleges are significantly more likely to involve undergraduate students in research. Implications for advancing undergraduate research opportunities are discussed

Antarctic sea ice region as a source of biogenic organic nitrogen in aerosols

Dall'Osto, Manuel ... et al.-- 10 pages, 5 figuresClimate warming affects the development and distribution of sea ice, but at present the evidence of polar ecosystem feedbacks on climate through changes in the atmosphere is sparse. By means of synergistic atmospheric and oceanic measurements in the Southern Ocean near Antarctica, we present evidence that the microbiota of sea ice and sea ice-influenced ocean are a previously unknown significant source of atmospheric organic nitrogen, including low molecular weight alkyl-amines. Given the keystone role of nitrogen compounds in aerosol formation, growth and neutralization, our findings call for greater chemical and source diversity in the modelling efforts linking the marine ecosystem to aerosol-mediated climate effects in the Southern OceanThe cruise was funded by the Spanish Ministry of Economy through projects PEGASO (CTM2012-37615) and Bio-Nuc (CGL2013-49020-R), and by the EU though the FP7-PEOPLE-2013-IOF programme (Project number 624680, MANU – Marine Aerosol NUcleations). [...] The NUI Galway and ISAC-CNR Bologna groups acknowledge funding from the European Union’s Seventh Framework Programme (FP7/2007-2013) project BACCHUS under grant agreement n° 603445. The work was further supported by the CNR (Italy) under AirSEaLab: Progetto Laboratori Congiunti. The National Centre for Atmospheric Science NCAS Birmingham group is funded by the UK Natural Environment Research Council. [...] CC, MFF and RA acknowledge funding from the Marine Institute, University of Plymouth to enable participation in PEGASOPeer Reviewe

A Novel Semi-Supervised Methodology for Extracting Tumor Type-Specific MRS Sources in Human Brain Data

BackgroundThe clinical investigation of human brain tumors often starts with a non-invasive imaging study, providing information about the tumor extent and location, but little insight into the biochemistry of the analyzed tissue. Magnetic Resonance Spectroscopy can complement imaging by supplying a metabolic fingerprint of the tissue. This study analyzes single-voxel magnetic resonance spectra, which represent signal information in the frequency domain. Given that a single voxel may contain a heterogeneous mix of tissues, signal source identification is a relevant challenge for the problem of tumor type classification from the spectroscopic signal.Methodology/Principal FindingsNon-negative matrix factorization techniques have recently shown their potential for the identification of meaningful sources from brain tissue spectroscopy data. In this study, we use a convex variant of these methods that is capable of handling negatively-valued data and generating sources that can be interpreted as tumor class prototypes. A novel approach to convex non-negative matrix factorization is proposed, in which prior knowledge about class information is utilized in model optimization. Class-specific information is integrated into this semi-supervised process by setting the metric of a latent variable space where the matrix factorization is carried out. The reported experimental study comprises 196 cases from different tumor types drawn from two international, multi-center databases. The results indicate that the proposed approach outperforms a purely unsupervised process by achieving near perfect correlation of the extracted sources with the mean spectra of the tumor types. It also improves tissue type classification.Conclusions/SignificanceWe show that source extraction by unsupervised matrix factorization benefits from the integration of the available class information, so operating in a semi-supervised learning manner, for discriminative source identification and brain tumor labeling from single-voxel spectroscopy data. We are confident that the proposed methodology has wider applicability for biomedical signal processing

Short-Lived Trace Gases in the Surface Ocean and the Atmosphere

The two-way exchange of trace gases between the ocean and the atmosphere is important for both the chemistry and physics of the atmosphere and the biogeochemistry of the oceans, including the global cycling of elements. Here we review these exchanges and their importance for a range of gases whose lifetimes are generally short compared to the main greenhouse gases and which are, in most cases, more reactive than them. Gases considered include sulphur and related compounds, organohalogens, non-methane hydrocarbons, ozone, ammonia and related compounds, hydrogen and carbon monoxide. Finally, we stress the interactivity of the system, the importance of process understanding for modeling, the need for more extensive field measurements and their better seasonal coverage, the importance of inter-calibration exercises and finally the need to show the importance of air-sea exchanges for global cycling and how the field fits into the broader context of Earth System Science

Land use change alters malaria transmission parameters by modifying temperature in a highland area of Uganda

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73403/1/j.1365-3156.2000.00551.x.pd

Herbal Medicines for Parkinson's Disease: A Systematic Review of Randomized Controlled Trials

OBJECTIVE: We conducted systematic review to evaluate current evidence of herbal medicines (HMs) for Parkinson's disease (PD). METHODS: Along with hand searches, relevant literatures were located from the electronic databases including CENTRAL, MEDLINE, EMBASE, CINAHL, AMED, PsycInfo, CNKI, 7 Korean Medical Databases and J-East until August, 2010 without language and publication status. Randomized controlled trials (RCTs), quasi-randomized controlled trials and randomized crossover trials, which evaluate HMs for idiopathic PD were selected for this review. Two independent authors extracted data from the relevant literatures and any disagreement was solved by discussion. RESULTS: From the 3432 of relevant literatures, 64 were included. We failed to suggest overall estimates of treatment effects on PD because of the wide heterogeneity of used herbal recipes and study designs in the included studies. When compared with placebo, specific effects were not observed in favor of HMs definitely. Direct comparison with conventional drugs suggested that there was no evidence of better effect for HMs. Many studies compared combination therapy with single active drugs and combination therapy showed significant improvement in PD related outcomes and decrease in the dose of anti-Parkinson's drugs with low adverse events rate. CONCLUSION: Currently, there is no conclusive evidence about the effectiveness and efficacy of HMs on PD. For establishing clinical evidence of HMs on PD, rigorous RCTs with sufficient statistical power should be promoted in future

The non-coding transcriptome as a dynamic regulator of cancer metastasis.

Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered "housekeeping" genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients' prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms

Euclid : I. Overview of the Euclid mission

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015–2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared imaging and spectroscopy, over about 14 000 deg2 of extragalactic sky. In addition to accurate weak lensing and clustering measurements that probe structure formation over half of the age of the Universe, its primary probes for cosmology, these exquisite data will enable a wide range of science. This paper provides a high-level overview of the mission, summarising the survey characteristics, the various data-processing steps, and data products. We also highlight the main science objectives and expected performance