Canvass: a crowd-sourced, natural-product screening library for exploring biological space

NCATS thanks Dingyin Tao for assistance with compound characterization. This research was supported by the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH). R.B.A. acknowledges support from NSF (CHE-1665145) and NIH (GM126221). M.K.B. acknowledges support from NIH (5R01GM110131). N.Z.B. thanks support from NIGMS, NIH (R01GM114061). J.K.C. acknowledges support from NSF (CHE-1665331). J.C. acknowledges support from the Fogarty International Center, NIH (TW009872). P.A.C. acknowledges support from the National Cancer Institute (NCI), NIH (R01 CA158275), and the NIH/National Institute of Aging (P01 AG012411). N.K.G. acknowledges support from NSF (CHE-1464898). B.C.G. thanks the support of NSF (RUI: 213569), the Camille and Henry Dreyfus Foundation, and the Arnold and Mabel Beckman Foundation. C.C.H. thanks the start-up funds from the Scripps Institution of Oceanography for support. J.N.J. acknowledges support from NIH (GM 063557, GM 084333). A.D.K. thanks the support from NCI, NIH (P01CA125066). D.G.I.K. acknowledges support from the National Center for Complementary and Integrative Health (1 R01 AT008088) and the Fogarty International Center, NIH (U01 TW00313), and gratefully acknowledges courtesies extended by the Government of Madagascar (Ministere des Eaux et Forets). O.K. thanks NIH (R01GM071779) for financial support. T.J.M. acknowledges support from NIH (GM116952). S.M. acknowledges support from NIH (DA045884-01, DA046487-01, AA026949-01), the Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program (W81XWH-17-1-0256), and NCI, NIH, through a Cancer Center Support Grant (P30 CA008748). K.N.M. thanks the California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board for support. B.T.M. thanks Michael Mullowney for his contribution in the isolation, elucidation, and submission of the compounds in this work. P.N. acknowledges support from NIH (R01 GM111476). L.E.O. acknowledges support from NIH (R01-HL25854, R01-GM30859, R0-1-NS-12389). L.E.B., J.K.S., and J.A.P. thank the NIH (R35 GM-118173, R24 GM-111625) for research support. F.R. thanks the American Lebanese Syrian Associated Charities (ALSAC) for financial support. I.S. thanks the University of Oklahoma Startup funds for support. J.T.S. acknowledges support from ACS PRF (53767-ND1) and NSF (CHE-1414298), and thanks Drs. Kellan N. Lamb and Michael J. Di Maso for their synthetic contribution. B.S. acknowledges support from NIH (CA78747, CA106150, GM114353, GM115575). W.S. acknowledges support from NIGMS, NIH (R15GM116032, P30 GM103450), and thanks the University of Arkansas for startup funds and the Arkansas Biosciences Institute (ABI) for seed money. C.R.J.S. acknowledges support from NIH (R01GM121656). D.S.T. thanks the support of NIH (T32 CA062948-Gudas) and PhRMA Foundation to A.L.V., NIH (P41 GM076267) to D.S.T., and CCSG NIH (P30 CA008748) to C.B. Thompson. R.E.T. acknowledges support from NIGMS, NIH (GM129465). R.J.T. thanks the American Cancer Society (RSG-12-253-01-CDD) and NSF (CHE1361173) for support. D.A.V. thanks the Camille and Henry Dreyfus Foundation, the National Science Foundation (CHE-0353662, CHE-1005253, and CHE-1725142), the Beckman Foundation, the Sherman Fairchild Foundation, the John Stauffer Charitable Trust, and the Christian Scholars Foundation for support. J.W. acknowledges support from the American Cancer Society through the Research Scholar Grant (RSG-13-011-01-CDD). W.M.W.acknowledges support from NIGMS, NIH (GM119426), and NSF (CHE1755698). A.Z. acknowledges support from NSF (CHE-1463819). (Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health (NIH); CHE-1665145 - NSF; CHE-1665331 - NSF; CHE-1464898 - NSF; RUI: 213569 - NSF; CHE-1414298 - NSF; CHE1361173 - NSF; CHE1755698 - NSF; CHE-1463819 - NSF; GM126221 - NIH; 5R01GM110131 - NIH; GM 063557 - NIH; GM 084333 - NIH; R01GM071779 - NIH; GM116952 - NIH; DA045884-01 - NIH; DA046487-01 - NIH; AA026949-01 - NIH; R01 GM111476 - NIH; R01-HL25854 - NIH; R01-GM30859 - NIH; R0-1-NS-12389 - NIH; R35 GM-118173 - NIH; R24 GM-111625 - NIH; CA78747 - NIH; CA106150 - NIH; GM114353 - NIH; GM115575 - NIH; R01GM121656 - NIH; T32 CA062948-Gudas - NIH; P41 GM076267 - NIH; R01GM114061 - NIGMS, NIH; R15GM116032 - NIGMS, NIH; P30 GM103450 - NIGMS, NIH; GM129465 - NIGMS, NIH; GM119426 - NIGMS, NIH; TW009872 - Fogarty International Center, NIH; U01 TW00313 - Fogarty International Center, NIH; R01 CA158275 - National Cancer Institute (NCI), NIH; P01 AG012411 - NIH/National Institute of Aging; Camille and Henry Dreyfus Foundation; Arnold and Mabel Beckman Foundation; Scripps Institution of Oceanography; P01CA125066 - NCI, NIH; 1 R01 AT008088 - National Center for Complementary and Integrative Health; W81XWH-17-1-0256 - Office of the Assistant Secretary of Defense for Health Affairs through the Peer Reviewed Medical Research Program; P30 CA008748 - NCI, NIH, through a Cancer Center Support Grant; California Department of Food and Agriculture Pierce's Disease and Glassy Winged Sharpshooter Board; American Lebanese Syrian Associated Charities (ALSAC); University of Oklahoma Startup funds; 53767-ND1 - ACS PRF; PhRMA Foundation; P30 CA008748 - CCSG NIH; RSG-12-253-01-CDD - American Cancer Society; RSG-13-011-01-CDD - American Cancer Society; CHE-0353662 - National Science Foundation; CHE-1005253 - National Science Foundation; CHE-1725142 - National Science Foundation; Beckman Foundation; Sherman Fairchild Foundation; John Stauffer Charitable Trust; Christian Scholars Foundation)Published versionSupporting documentatio

Transformation of UML Activity Diagram for Enhanced Reasoning

IT industry has adopted the unified modelling language activity diagram (UML-AD) as a de facto standard. UML AD facilitates modellers to graphically represent and document business processes to show the flow of activities and behaviour of a system. However, UML AD has many drawbacks such as lack of formal semantics i.e. ontology used for the constructs based on intuition, that vaguely describes processes and no provision for verifiability. Petri Net (PN) has been around for decades and used to model the workflow systems but PNs and its variants are too complex for business process modellers with no prior experience. A logical foundation is desirable to construct a business process with a precision that facilitates in transforming UML AD into a formal mechanism supported by verifiability capabilities for enhanced reasoning. Therefore, in this paper, we will provide a framework that will provide formal definitions for UML AD core terms and constructs used for modelling, and subsequently transform them to formal representation called point graph(PG). This will provide an insight into UML AD and will improve the overall functionality required from a modelling tool. A case study is conducted at King’s College Hospital trust’ to improve their patient flows of an accident and emergency (A&E) department

Systematic Development of the YouRAction program, a computer-tailored Physical Activity promotion intervention for Dutch adolescents, targeting personal motivations and environmental opportunities

Background. Increasing physical activity (PA) among adolescents is an important health promotion goal. PA has numerous positive health effects, but the majority of Dutch adolescents do not meet PA requirements. The present paper describes the systematic development of a theory-based computer-tailored intervention, YouRAction, which targets individual and environmental factors determining PA among adolescents. Design. The intervention development was guided by the Intervention Mapping protocol, in order to define clear program objectives, theoretical methods and practical strategies, ensure systematic program planning and pilot-testing, and anticipate on implementation and evaluation. Two versions of YouRAction were developed: one that targets individual determinants and an extended version that also provides feedback on opportunities to be active in the neighbourhood. Key determinants that were targeted included: knowledge and awareness, attitudes, self-efficacy and subjective norms. The extended version also addressed perceived availability of neighbourhood PA facilities. Both versions aimed to increase levels of moderate-to-vigorous PA among adolescents. The intervention structure was based on self-regulation theory, comprising of five steps in the process of successful goal pursuit. Monitoring of PA behaviour and behavioural and normative feedback were used to increase awareness of PA behaviour; motivation was enhanced by targeting self-efficacy and attitudes, by means of various interactive strategies, such as web movies; the perceived environment was targeted by visualizing opportunities to be active in an interactive geographical map of the home environment; in the goal setting phase, the adolescents were guided in setting a goal and developing an action plan to achieve this goal; in the phase of active goal pursuit adolescents try to achieve their goal and in the evaluation phase the achievements are evaluated. Based on the results of the evaluation adolescents could revise their goal or choose another behaviour to focus on. The intervention is delivered in a classroom setting in three lessons. YouRAction will be evaluated in a cluster-randomized trial, with classes as unit of randomization. Evaluation will focus on PA outcomes, cognitive mediators/moderators and process measures. Discussion. The planned development of YouRAction resulted in two computer-tailored interventions aimed at the promotion of PA in a Dutch secondary school setting. Trial registration. NTR1923

Passive smoking in babies: The BIBE study (Brief Intervention in babies. Effectiveness)

Background: There is evidence that exposure to passive smoking in general, and in babies in particular, is an important cause of morbimortality. Passive smoking is related to an increased risk of pediatric diseases such as sudden death syndrome, acute respiratory diseases, worsening of asthma, acute-chronic middle ear disease and slowing of lung growth. The objective of this article is to describe the BIBE study protocol. The BIBE study aims to determine the effectiveness of a brief intervention within the context of Primary Care, directed to mothers and fathers that smoke, in order to reduce the exposure of babies to passive smoking (ETS). Methods/Design: Cluster randomized field trial (control and intervention group), multicentric and open. Subject: Fathers and/or mothers who are smokers and their babies (under 18 months) that attend pediatric services in Primary Care in Catalonia. The measurements will be taken at three points in time, in each of the fathers and/or mothers who respond to a questionnaire regarding their baby's clinical background and characteristics of the baby's exposure, together with variables related to the parents' tobacco consumption. A hair sample of the baby will be taken at the beginning of the study and at six months after the initial visit (biological determination of nicotine). The intervention group will apply a brief intervention in passive smoking after specific training and the control group will apply the habitual care. Discussion: Exposure to ETS is an avoidable factor related to infant morbimortality. Interventions to reduce exposure to ETS in babies are potentially beneficial for their health. The BIBE study evaluates an intervention to reduce exposure to ETS that takes advantage of pediatric visits. Interventions in the form of advice, conducted by pediatric professionals, are an excellent opportunity for prevention and protection of infants against the harmful effects of ETS

Family support for physical activity in girls from 8th to 12th grade in South Carolina

Objective - To examine the relationship between perceived family support and other selected correlates of physical activity (PA) with changes in PA over time. Methods - A total of 421 girls in South Carolina completed questionnaires at 8th, 9th and 12th grades (1998-2003). Family support for PA, PA self-efficacy, perceived behavioral control, attitudes, availability of equipment, and PA were measured. Results - Growth curve analysis showed that family support, perceived behavioral control, and self-efficacy were independently related to age-related changes in PA as reflected by a total METs. Girls who reported lower family support at the 8th grade measure had more rapid declines in PA, and a unit change in family support was related to approximately 1/3 of a standard deviation change in total METs. Conclusions - Maintenance of support from family members may reduce the decline in PA independent of girl\u27s self-efficacy and perceived behavioral control

Nonlinear Jacobi and E-Relaxation Methods for Parallel Network Optimization

In this thesis we develop an efficient decomposition method for large-scale convex cost multi-commodity network flow problems. The coupling constraints are moved to the objective function via augmented Lagrangian terms. A nonlinear Jacobi algorithm is then used to solve the resulting program in parallel in a fork-join manner. Several approaches to solving the coordination problem (corresponding to the join phase are investigated. In particular, a coordination method is developed that combines excellent parallel efficiency and low communication overhead with good empirical rate of convergence. parallel implementations of the algorithm on the Thinking Machines CM-5 supercomputer and a cluster of workstations running PVM demonstrate that it is competitive or superior to the best known methods. We are able to solve linear multi-commodity problems with over 200,000 variables in less that 15 minutes. The specific form of the non-strictly-convex subproblems (corresponding to the fork phase) motivates us to develop a relaxation method for separable convex network flow problems that is well-suited for problems with large variations in the magnitude of the nonlinear cost terms. The arcs are partitioned into two sets, one of which contains only arcs corresponding to strictly convex costs. The algorithm adjusts flows on the other arcs whenever possible, and terminates with primal dual pairs that satisfy complementary slackness on the strictly convex arc set and E-complementary slackness on the remaining arcs. An asynchronous parallel variant of the method is also developed. Computational results demonstrate that the method is significantly more efficient on quadratic ill-conditioned networks than existing methods, solving problems with several thousand nonlinear arcs in one second or less