OCSANA+: optimal control and simulation of signaling networks from network analysis.

SUMMARY: OCSANA+ is a Cytoscape app for identifying nodes to drive the system toward a desired long-term behavior, prioritizing combinations of interventions in large-scale complex networks, and estimating the effects of node perturbations in signaling networks, all based on the analysis of the network's structure. OCSANA+ includes an update to optimal combinations of interventions from network analysis software tool with cutting-edge and rigorously tested algorithms, together with recently developed structure-based control algorithms for non-linear systems and an algorithm for estimating signal flow. All these algorithms are based on the network's topology. OCSANA+ is implemented as a Cytoscape app to enable a user interface for running analyses and visualizing results. AVAILABILITY AND IMPLEMENTATION: OCSANA+ app and its tutorial can be downloaded from the Cytoscape App Store or https://veraliconaresearchgroup.github.io/OCSANA-Plus/. The source code and computations are available in https://github.com/VeraLiconaResearchGroup/OCSANA-Plus_SourceCode. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Setting a Standard for Chemistry Education in the Next Generation: A Retrosynthetic Analysis.

A diverse and highly qualified chemistry teaching workforce is critical for preparing equally diverse, qualified STEM professionals. Here, we analyze National Center for Education Statistics (NCES) Schools and Staffing Survey (SASS) data to provide a demographic comparison of the U.S. secondary chemistry teaching population in high-needs and non-high-needs public schools as well as private schools during the 2011-2012 academic year. Our analysis reveals that the chemistry teaching workforce is predominantly white and significantly lacks in-field degrees or certification across school types, though high-needs and private schools are most affected by this lack of teacher qualification. Given these results, we attempt to retrosynthetically identify the pathway yielding a qualified chemistry teaching workforce to draw attention to the various steps in this scheme where reform efforts on the part of individual faculty, academic institutions, and organizations can be concentrated.

Moral disengagement and associated processes in performance-enhancing drug use: a national qualitative investigation.

This study investigated psychosocial processes associated with avoidance of health- and morality-based deterrents to performance-enhancing drug (PED) use. In-depth semi-structured interviews were conducted with 64 English male bodybuilders with experience of doping. Resultant data were content analysed deductively using definitions for the eight mechanisms of moral disengagement (MD; Bandura, A. (1991). Social cognitive theory of moral thought and action. In W. M. Kurtines & J. L. Gewirtz (Eds.), Handbook of moral behavior and development: Theory research and applications (pp. 71-129). Hillsdale, NJ: Lawrence Erlbaum Associates.), and three further themes from Boardley and Grix (2013. Doping in bodybuilders: A qualitative investigation of facilitative psychosocial processes. Qualitative Research in Sport, Exercise, and Health. Advance online publication, doi 10.1080/2159676X.2013.766809). These analyses evidenced six MD mechanisms, and all three of the themes from Boardley and Grix (2013. Doping in bodybuilders: A qualitative investigation of facilitative psychosocial processes. Qualitative Research in Sport, Exercise, and Health. Advance online publication). Subsequent frequency analyses revealed six of the eight MD mechanisms, and two of the three additional themes, were common across the sample. Overall, the findings suggest MD may help athletes circumvent health- and morality-based deterrents to doping, describe a process linking supplement and PED use and detail how some athletes may actively avoid social censure for doping by only discussing PED use with other PED users from within their training environment.

Photoluminescent gold-copper nanoparticle alloys with composition-tunable near-infrared emission.

Discrete gold nanoparticles with diameters between 2 and 3 nm show remarkable properties including enhanced catalytic behavior and photoluminescence. However, tunability of these properties is limited by the tight size range within which they are observed. Here, we report the synthesis of discrete, bimetallic gold-copper nanoparticle alloys (diameter ≅ 2-3 nm) which display photoluminescent properties that can be tuned by changing the alloy composition. Electron microscopy, X-ray photoelectron spectroscopy, inductively coupled plasma mass spectrometry, and pulsed-field gradient stimulated echo (1)H NMR measurements show that the nanoparticles are homogeneous, discrete, and crystalline. Upon varying the composition of the nanoparticles from 0% to 100% molar ratio copper, the photoluminescence maxima shift from 947 to 1067 nm, with excitation at 360 nm. The resulting particles exhibit brightness values (molar extinction coefficient (ε) × quantum yield (Φ)) that are more than an order of magnitude larger than the brightest near-infrared-emitting lanthanide complexes and small-molecule probes evaluated under similar conditions.