Reports Of Conferences, Institutes, And Seminars

This quarter\u27s column offers coverage of multiple sessions from the 2016 Electronic Resources & Libraries (ER&L) Conference, held April 3–6, 2016, in Austin, Texas. Topics in serials acquisitions dominate the column, including reports on altmetrics, cost per use, demand-driven acquisitions, and scholarly communications and the use of subscriptions agents; ERMS, access, and knowledgebases are also featured

Upgrades to StellaBase facilitate medical and genetic studies on the starlet sea anemone, Nematostella vectensis

© 2007 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The definitive version was published in Nucleic Acids Research 36 (2008): D607-D611, doi:10.1093/nar/gkm941.The starlet sea anemone, Nematostella vectensis, is a basal metazoan organism that has recently emerged as an important model system in developmental biology and evolutionary genomics. StellaBase, the Nematostella Genomics Database (http://stellabase.org), was developed in 2005 as a resource to support the Nematostella research community. Recently, it has become apparent that Nematostella may be a particularly useful system for studying (i) microevolutionary variation in natural populations, and (ii) the functional evolution of human disease genes. We have developed two new databases that will foster such studies: StellaBase Disease (http://stellabase.org/disease) is a relational database that houses 155 904 invertebrate homologous isoforms of human disease genes from four leading genomic model systems (fly, worm, yeast and Nematostella), including 14 874 predicted genes from the sea anemone itself. StellaBase SNP (http://stellabase.org/SNP) is a relational database that describes the location and underlying type of mutation for 20 063 single nucleotide polymorphisms.This work was supported by NSF grant FP-91656101-0 to J.C.S. and J.R.F. and EPA Grant F5E11155 to A.R.M. and J.R.F. and by a Postdoctoral Scholar Program at the Woods Hole Oceanographic Institution, with funding provided by The Beacon Institute for Rivers and Estuaries, and the J. Seward Johnson Fund to A.M.R

S100A6 preferentially labels type C nevus cells and nevic corpuscles: additional support for Schwannian differentiation of intradermal nevi

Melanocytic nevi typically show a morphologic sequence of maturation from epithelioid “type A” cells to fusiform, Schwann cell-like “type C” cells with dermal descent. Nevi may also produce Wagner-Meissner-like structures (nevic corpuscles). Previous studies have shown that this maturation of intradermal nevi recapitulates intermediate stages in Schwann cell development. In intradermal nevi, we have evaluated the pattern of S100A6 protein, a form of S100 found in Schwann cells. Methods: Formalin-fixed, paraffin-embedded archival tissues were evaluated by immunohistochemistry using antibodies specific for S100A6 and S100B in 38 intradermal nevi (IDN). Ten neurofibromas (NF), 3 Schwannomas (SCH), 2 palisaded and encapsulated neuromas (PEN), and 2 granular cell tumors (GCT) were included as positive controls since these lesions have large numbers of Schwann cells. Results: Melanocytic nevi demonstrated preferential anti-S100A6 staining of “type C” cells (36/38; 28 strong, 8 weak) and nevic corpuscles (25/38; 19 strong, 6 weak) compared to “type A” cells (17/38; 17 weak) and “type B” cells (17/38; 4 strong, 13 weak). All NF, SCH, and PEN stained strongly with anti-S100A6. Both GCT were negative with anti-S100A6 but positive with anti-S100B. Conclusions: The pattern of S100A6 expression in intradermal nevi further supports the hypothesis that maturation in these lesions recapitulates features of Schwann cell differentiation. The lack of S100A6 expression by both GCT suggests that these lesions have lost this feature of Schwann cells, which may play a role in their peculiar phenotypic appearance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75660/1/j.1600-0560.2001.028008393.x.pd

A Comparison of Warm-up Effects on Maximal Aerobic Exercise Performance in Children

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Simulating the Multi-Epoch Direct Detection Technique to Isolate the Thermal Emission of the Non-Transiting Hot Jupiter HD187123B

We report the 6.5$\sigma$ detection of water from the hot Jupiter HD187123b with a Keplerian orbital velocity $K_p$ of 53 $\pm$ 13 km/s. This high confidence detection is made using a multi-epoch, high resolution, cross correlation technique, and corresponds to a planetary mass of 1.4$^{+0.5}_{-0.3}$ $M_J$ and an orbital inclination of 21 $\pm$ 5$^{\circ}$. The technique works by treating the planet/star system as a spectroscopic binary and obtaining high signal-to-noise, high resolution observations at multiple points across the planet's orbit to constrain the system's binary dynamical motion. All together, seven epochs of Keck/NIRSPEC $L$-band observations were obtained, with five before the instrument upgrade and two after. Using high resolution SCARLET planetary and PHOENIX stellar spectral models, along with a line-by-line telluric absorption model, we were able to drastically increase the confidence of the detection by running simulations that could reproduce, and thus remove, the non-random structured noise in the final likelihood space well. The ability to predict multi-epoch results will be extremely useful for furthering the technique. Here, we use these simulations to compare three different approaches to combining the cross correlations of high resolution spectra and find that the Zucker 2003 log(L) approach is least affected by unwanted planet/star correlation for our HD187123 data set. Furthermore, we find that the same total S/N spread across an orbit in many, lower S/N epochs rather than fewer, higher S/N epochs could provide a more efficient detection. This work provides a necessary validation of multi-epoch simulations which can be used to guide future observations and will be key to studying the atmospheres of further separated, non-transiting exoplanets.Comment: Accepted to AJ, 14 pages, 10 figure

Low-Background gamma counting at the Kimballton Underground Research Facility

The next generation of low-background physics experiments will require the use of materials with unprecedented radio-purity. A gamma-counting facility at the Kimballton Underground Research Facility (KURF) has been commissioned to perform initial screening of materials for radioactivity primarily from nuclides in the 238U and 232Th decay chains, 40K and cosmic-ray induced isotopes. The facility consists of two commercial low-background high purity germanium (HPGe) detectors. A continuum background reduction better than a factor of 10 was achieved by going underground. This paper describes the facility, detector systems, analysis techniques and selected assay results.Comment: 7 pages, 7 figures. Submitted to NIM

The Human Behaviour-Change Project: Harnessing the power of Artificial Intelligence and Machine Learning for evidence synthesis and interpretation

Background Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support. The Human Behaviour-Change Project (HBCP) will use Artificial Intelligence and Machine Learning to (i) develop and evaluate a ‘Knowledge System’ that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness and (ii) allow users, such as practitioners, policy makers and researchers, to easily and efficiently query the system to get answers to variants of the question ‘What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what settings and why?’. Methods The HBCP will: a) develop an ontology of BCI evaluations and their reports linking effect sizes for given target behaviours with intervention content and delivery and mechanisms of action, as moderated by exposure, populations and settings; b) develop and train an automated feature extraction system to annotate BCI evaluation reports using this ontology; c) develop and train machine learning and reasoning algorithms to use the annotated BCI evaluation reports to predict effect sizes for particular combinations of behaviours, interventions, populations and settings; d) build user and machine interfaces for interrogating and updating the knowledge base; and e) evaluate all the above in terms of performance and utility. Discussion The HBCP aims to revolutionise our ability to synthesise, interpret and deliver evidence on behaviour change interventions that is up-to-date and tailored to user need and context. This will enhance the usefulness, and support the implementation of, that evidence.The project is funded by a Wellcome Trust collaborative award [The Human Behaviour-Change Project: Building the science of behaviour change for complex intervention development’, 201,524/Z/16/Z]. During the preparation of the manuscript RW’s salary was funded by Cancer Research UK