Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
Abstract:
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.
This dataset contains all the data, model and MATLAB codes used to generate the figures and data reported in the article (DOI: 10.1002/2014JD022278). The data was generated during September 2013 and February 2014 using the Ocean-Land-Atmosphere Model also provided with this package. The data was generated using the computational resources supported by the PICSciE OIT High Performance Computing Center and Visualization Laboratory at Princeton University. The dataset contains a pdf Readme file which explains in detail how the data can be used. Users are recommended to go through this file before using the data.
Protein sequence space is vast; nature uses only an infinitesimal fraction of possible sequences to sustain life. Are there solutions to biological problems other than those provided by nature? Can we create artificial proteins that sustain life? To investigate this question, the Hecht lab has created combinatorial collections, or libraries, of novel sequences with no homology to those found in living organisms. These libraries were subjected to screens and selections, leading to the identification of sequences with roles in catalysis, modulating gene regulation, and metal homeostasis. However, the resulting functional proteins formed dynamic rather than well-ordered structures. This impeded structural characterization and made it difficult to ascertain a mechanism of action.
To address this, Christina Karas's thesis work focuses on developing a new model of libraries based on the de novo protein S-824, a four-helix bundle with a very stable three-dimensional structure. The first part of this research focused on mutagenesis of S-824 and characterization of the resulting proteins, revealing that this scaffold tolerates amino acid substitutions, including buried polar residues and the removal of hydrophobic side chains to create a putative cavity.
Distinct from previous libraries, Karas targeted variability to a specific region of the protein, seeking to create a cavity and potential active site. The second part of this work details the design and creation of a library encoding 1.7 x 10^6 unique proteins, assembled from degenerate oligonucleotides. The third and fourth parts of this work cover the screening effort for a range of activities, both in vitro and in vivo. I found that this collection binds heme readily, leading to abundant peroxidase activity. Hits for lipase and phosphatase activity were also detected.
This work details the development of a new strategy for creating de novo sequences geared toward function rather than structure.
