Several iterations of the OSC were tested before arriving at

Several iterations of the OSC were tested before arriving at the design used in this article and the main research article [1]. The electrical design can be seen in Fig. 3. A custom PCB with the form factor of an Arduino shield was produced from the design seen in Fig. 4. The OSC has three main settings: LOAD, PID and FREEZE. LOAD will set the temperature of the stage to just below ambient, allowing loading without excessive condensation. FREEZE puts the Peltier unit at maximum power, which will freeze the sample within seconds. PID is the setting which is used during experimentation. A small thermistor provides the Arduino with constant temperature readings, and the Arduino in turn calculates Peltier power level from the temperature deviation from a given setpoint temperature. The setpoint temperature is related to the osmolality of the sample, as described in main article [1]. See Fig. 5 for flow chart.
Acknowledgments This work was supported by the Danish Research Council for Technology and Production Sciences, Grant #10-082261.
Data The AlloRep database (www.AlloRep.org) [1] compiles extensive sequence, mutagenesis, and structural information for the LacI/GalR family of 4EGI-1 cost regulators. Phenotypic and biochemical data on almost 6000 mutants have been compiled from an exhaustive search of the literature; citations for these data are listed in this publication [2–82]. The data can be exported to build a local copy on the user׳s computer, but the insert and import features are disabled. New data are welcome and can be submitted to the corresponding author at [email protected]. Here, we detail the organization of the 5 database modules and their components tables, and provide full descriptions for the contents of table columns. Fig. 1 overviews the structure of the database. We also present a protein structural comparison that was facilitated by compiling the information in the structural module. Fig. 2 shows a comparison of intra- and inter-molecular contacts from a comparative study of 65 structures available for the LacI/GalR homologs. Finally, the database can be searched by selecting a table from one of the modules and using the built in search fields (search tab; Fig. 3). In addition, command line queries can be executed using the SQL tab. Example command line queries are listed in supplement to this manuscript.
2. Experimental design, materials and methods
Acknowledgments This work was supported by Fundação para a Ciência e Tecnologia, SFRH/BPD/73058/2010 (FLS), NIHGM 079423 (LSK), and the University of Kansas Medical Center Biomedical Research Training Program (DJP). We thank Tina Perica for many stimulating discussions about this project.
Data Three figures are presented. Fig. 1 contains individual animal, relative ruminal microbial abundance data from rumen samples selected from feed efficient steers (ADGGreater−ADFILess), and the 3 with least variability among the 8 samples (animals) in the group [1,3]; Fig. 2 depicts the data from the calculated rarefaction curves from metagenomic DNA mapped to consensus 16S rRNA V1–V3 and V1–V8 regions; Fig. 3 contains relative ruminal microbial abundance data from rumen samples regarding the reduced PCR amplification of the 16S rRNA V1–V8 hypervariable regions and pooling of the amplification products in order to determine any effects on taxonomic classification and analysis. A complete description of the data and methods is presented elsewhere [1].
Experimental design, materials and methods
Acknowledgments We thank Bob Lee, Sue Hauver, Kelsey McClure, Renee Godtel, and Brooke Clemmons for technical assistance. This project is partially supported by Agriculture and Food Research Initiative Competitive Grant no. 2011-68004-30214 from USDA National Institute of Food and Agriculture.
Data Terpenoids are important plant secondary compounds and wine aroma compounds. Terpenoids were analysed in grapevines (Vitis vinifera cv. Shiraz) during physiological ripening, from weeks post flowering (wpf) (Table 1).