Binocular interaction:Contrast matching and contrast discrimination are predicted by the same model

How do signals from the 2 eyes combine and interact? Our recent work has challenged earlier schemes in which monocular contrast signals are subject to square-law transduction followed by summation across eyes and binocular gain control. Much more successful was a new 'two-stage' model in which the initial transducer was almost linear and contrast gain control occurred both pre- and post-binocular summation. Here we extend that work by: (i) exploring the two-dimensional stimulus space (defined by left- and right-eye contrasts) more thoroughly, and (ii) performing contrast discrimination and contrast matching tasks for the same stimuli. Twenty-five base-stimuli made from 1 c/deg patches of horizontal grating, were defined by the factorial combination of 5 contrasts for the left eye (0.3-32%) with five contrasts for the right eye (0.3-32%). Other than in contrast, the gratings in the two eyes were identical. In a 2IFC discrimination task, the base-stimuli were masks (pedestals), where the contrast increment was presented to one eye only. In a matching task, the base-stimuli were standards to which observers matched the contrast of either a monocular or binocular test grating. In the model, discrimination depends on the local gradient of the observer's internal contrast-response function, while matching equates the magnitude (rather than gradient) of response to the test and standard. With all model parameters fixed by previous work, the two-stage model successfully predicted both the discrimination and the matching data and was much more successful than linear or quadratic binocular summation models. These results show that performance measures and perception (contrast discrimination and contrast matching) can be understood in the same theoretical framework for binocular contrast vision. © 2007 VSP.

Domain and nucleotide dependence of the interaction between Saccharomyces cerevisiae translation elongation factors 3 and 1A

Eukaryotic translation elongation factor 3 (eEF3) is a fungal-specific ATPase proposed to catalyze the release of deacylated-tRNA from the ribosomal E-site. In addition, it has been shown to interact with the aminoacyl-tRNA binding GTPase elongation factor 1A (eEF1A), perhaps linking the E and A sites. Domain mapping demonstrates that amino acids 775-980 contain the eEF1A binding sites. Domain III of eEF1A, which is also involved in actin-related functions, is the site of eEF3 binding. The binding of eEF3 to eEF1A is enhanced by ADP, indicating the interaction is favored post-ATP hydrolysis but is not dependent on the eEF1A-bound nucleotide. A temperature-sensitive P915L mutant in the eEF1A binding site of eEF3 has reduced ATPase activity and affinity for eEF1A. These results support the model that upon ATP hydrolysis, eEF3 interacts with eEF1A to help catalyze the delivery of aminoacyl-tRNA at the A-site of the ribosome. The dynamics of when eEF3 interacts with eEF1A may be part of the signal for transition of the post to pre-translocational ribosomal state in yeast.

Working with the public sector:SME medical device innovation and pre-procurement

Healthcare providers are under ever increasing pressure to deliver more technologically advanced care without increasing costs. Innovation is essential (Darzi, 2008), and for this healthcare providers rely on innovation within commercial companies. SMEs have an important part to play in this sector (NHS Supply Chain Parliamentary Brief, 2013). Collaboration between SME suppliers and the NHS for innovation forms the focus of this paper. We examine the academic literature on interorganizational innovation including academic insights from the areas of forward commitment procurement (Environmental Innovation Advisory Group, 2003-2008), pre-commercial procurement (Bos & Corvers, 2007), innovation and SMEs. We then explore practice, first from a policy and business sector perspective. Second, we present evidence from fifteen cases of interorganizational innovation projects involving SMEs and UK healthcare providers. Our findings show much effort is being put into creating opportunities for more interorganizational innovation of medical devices. Working across organizational boundaries presents added complexity to the innovation environment and process, and the challenge of developing high-quality cross-boundary group interaction.