Assessing the influence of dopamine and mindfulness on the formation of routines in visual search

Given experience in cluttered but stable visual environments, our eye‐movements form stereotyped routines that sample task‐relevant locations, while not mixing‐up routines between similar task‐settings. Both dopamine signaling and mindfulness have been posited as factors that influence the formation of such routines, yet quantification of their impact remains to be tested in healthy humans. Over two sessions, participants searched through grids of doors to find hidden targets, using a gaze‐contingent display. Within each session, door scenes appeared in either one of two colors, with each color signaling a differing set of likely target locations. We derived measures for how well target locations were learned (target‐accuracy), how routine were sets of eye‐movements (stereotypy), and the extent of interference between the two scenes (setting‐accuracy). Participants completed two sessions, where they were administered either levodopa (dopamine precursor) or placebo (vitamin C), under double‐blind counterbalanced conditions. Dopamine and trait mindfulness (assessed by questionnaire) interacted to influence both target‐accuracy and stereotypy. Increasing dopamine improved accuracy and reduced stereotypy for high mindfulness scorers, but induced the opposite pattern for low mindfulness scorers. Dopamine also disrupted setting‐accuracy invariant to mindfulness. Our findings show that mindfulness modulates the impact of dopamine on the target‐accuracy and stereotypy of eye‐movement routines, whereas increasing dopamine promotes interference between task‐settings, regardless of mindfulness. These findings provide a link between non‐human and human models regarding the influence of dopamine on the formation of task‐relevant eye‐movement routines and provide novel insights into behavior‐trait factors that modulate the use of experience when building adaptive repertoires

Adenovirus type 5 E4 Orf3 protein targets promyelocytic leukaemia (PML) protein nuclear domains for disruption via a sequence in PML isoform II that is predicted as a protein interaction site by bioinformatic analysis

Human adenovirus type 5 infection causes the disruption of structures in the cell nucleus termed promyelocytic leukaemia (PML) protein nuclear domains or ND10, which contain the PML protein as a critical component. This disruption is achieved through the action of the viral E4 Orf3 protein, which forms track-like nuclear structures that associate with the PML protein. This association is mediated by a direct interaction of Orf3 with a specific PML isoform, PMLII. We show here that the Orf3 interaction properties of PMLII are conferred by a 40 aa residue segment of the unique C-terminal domain of the protein. This segment was sufficient to confer interaction on a heterologous protein. The analysis was informed by prior application of a bioinformatic tool for the prediction of potential protein interaction sites within unstructured protein sequences (predictors of naturally disordered region analysis; PONDR). This tool predicted three potential molecular recognition elements (MoRE) within the C-terminal domain of PMLII, one of which was found to form the core of the Orf3 interaction site, thus demonstrating the utility of this approach. The sequence of the mapped Orf3-binding site on PML protein was found to be relatively poorly conserved across other species; however, the overall organization of MoREs within unstructured sequence was retained, suggesting the potential for conservation of functional interactions

The impact of supportive nursing care on the needs of men with prostate cancer: a study across seven European countries

Background: prostate cancer is for many men a chronic disease with a long life expectancy after treatment. The impact of prostate cancer therapy on men has been well defined, however, explanation of the consequences of cancer treatment has not been modelled against the wider variables of long-term health-care provision. The aim of this study was to explore the parameters of unmet supportive care needs in men with prostate cancer in relation to the experience of nursing care. Methods: a survey was conducted among a volunteer sample of 1001 men with prostate cancer living in seven European countries. Results: at the time of the survey, 81% of the men had some unmet supportive care needs including psychological, sexual and health system and information needs. Logistic regression indicated that lack of post-treatment nursing care significantly predicted unmet need. Critically, men's contact with nurses and/or receipt of advice and support from nurses, for several different aspects of nursing care significantly had an impact on men's outcomes. Conclusion: Unmet need is related not only to disease and treatment factors but is also associated with the supportive care men received. Imperative to improving men's treatment outcomes is to also consider the access to nursing and the components of supportive care provided, especially after therapy

Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models

The regional and global significance of nitrogen removal in lakes and reservoirs

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Biogeochemistry 93 (2009): 143-157, doi:10.1007/s10533-008-9272-x.Human activities have greatly increased the transport of biologically available N through watersheds to potentially sensitive coastal ecosystems. Lentic water bodies (lakes and reservoirs) have the potential to act as important sinks for this reactive N as it is transported across the landscape because they offer ideal conditions for N burial in sediments or permanent loss via denitrification. However, the patterns and controls on lentic N removal have not been explored in great detail at large regional to global scales. In this paper we describe, evaluate, and apply a new, spatially explicit, annual-scale, global model of lentic N removal called NiRReLa (Nitrogen Retention in Reservoirs and Lakes). The NiRReLa model incorporates small lakes and reservoirs than have been included in previous global analyses, and also allows for separate treatment and analysis of reservoirs and natural lakes. Model runs for the mid-1990s indicate that lentic systems are indeed important sinks for N and are conservatively estimated to remove 19.7 Tg N yr-1 from watersheds globally. Small lakes (< 50 km2) were critical in the analysis, retaining almost half (9.3 Tg N yr-1) of the global total. In model runs, capacity of lakes and reservoirs to remove watershed N varied substantially (0-100%) both as a function of climate and the density of lentic systems. Although reservoirs occupy just 6% of the global lentic surface area, we estimate they retain approximately 33% of the total N removed by lentic systems, due to a combination of higher drainage ratios (catchment surface area : lake or reservoir surface area), higher apparent settling velocities for N, and greater N loading rates in reservoirs than in lakes. Finally, a sensitivity analysis of NiRReLa suggests that, on-average, N removal within lentic systems will respond more strongly to changes in land use and N loading than to changes in climate at the global scale.The NSF26 Research Coordination Network on denitrification for support for collaboration (award number DEB0443439 to S.P. Seitzinger and E.A. Davidson). This project was also supported by grants to J.A. Harrison from California Sea Grant (award number RSF8) and from the U.S. Geological Survey 104b program and R. Maranger (FQRNT Strategic Professor)

Multiscale multiphysics data-informed modeling for three-dimensional ocean acoustic simulation and prediction

Author Posting. © Acoustical Society of America, 2019. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 146(3), (2019): 1996-2015, doi:10.1121/1.5126012.Three-dimensional (3D) underwater sound field computations have been used for a few decades to understand sound propagation effects above sloped seabeds and in areas with strong 3D temperature and salinity variations. For an approximate simulation of effects in nature, the necessary 3D sound-speed field can be made from snapshots of temperature and salinity from an operational data-driven regional ocean model. However, these models invariably have resolution constraints and physics approximations that exclude features that can have strong effects on acoustics, example features being strong submesoscale fronts and nonhydrostatic nonlinear internal waves (NNIWs). Here, work to predict NNIW fields to improve 3D acoustic forecasts using an NNIW model nested in a tide-inclusive data-assimilating regional model is reported. The work was initiated under the Integrated Ocean Dynamics and Acoustics project. The project investigated ocean dynamical processes that affect important details of sound-propagation, with a focus on those with strong intermittency (high kurtosis) that are challenging to predict deterministically. Strong internal tides and NNIW are two such phenomena, with the former being precursors to NNIW, often feeding energy to them. Successful aspects of the modeling are reported along with weaknesses and unresolved issues identified in the course of the work.This work was supported by Department of Defense Multidisciplinary University Initiative (MURI) Grant No. N00014-11-1-0701, managed by the Office of Naval Research Ocean Acoustics Program, and National Science Foundation Grant No. OCE-1060430. Final manuscript preparation was supported by ONR Ocean Acoustics Grant Nos. N00014-17-1-2624 and N00014-17-1-2692. P.F.J.L. also thanks ONR and NSF for research support under Grant Nos. N00014-13-1-0518 (Multi-DA) and OCE-1061160 (ShelfIT) to MIT, respectively. The MSEAS-based series of simulations for the New Jersey shelf region examined here was accelerated toward completion by the interest in realistic 3D acoustic fields expressed by Dr. Ivars Kirsteins at the Naval Undersea Warfare Center.2020-03-3

Smaller classes promote equitable student participation in STEM

Under embargo until: 2020-07-24As science, technology, engineering, and mathematics (STEM) classrooms in higher education transition from lecturing to active learning, the frequency of student interactions in class increases. Previous research documents a gender bias in participation, with women participating less than would be expected on the basis of their numeric proportions. In the present study, we asked which attributes of the learning environment contribute to decreased female participation: the abundance of in-class interactions, the diversity of interactions, the proportion of women in class, the instructor's gender, the class size, and whether the course targeted lower division (first and second year) or upper division (third or fourth year) students. We calculated likelihood ratios of female participation from over 5300 student–instructor interactions observed across multiple institutions. We falsified several alternative hypotheses and demonstrate that increasing class size has the largest negative effect. We also found that when the instructors used a diverse range of teaching strategies, the women were more likely to participate after small-group discussions.acceptedVersio