Efficiency test data interpretation

One of the functions of Global Core Technologies R D is the analytical discipline Reactive Chemicals/ Thermal Analysis/Physical Properties (RC/TA/PP). Some of the capabilities of this discipline are testing and data interpretation for reactive chemicals hazard assessment. It is the responsibility of the owner of any chemical process to use this Dow resource to obtain the information which is necessary to design a safe and efficient operation. Information about the analytical RC Testing discipline including contact names can be obtained on the INTRAnet at Reactive Chemicals/Thermal Analysis/Physical Properties web site. 

Extensive quantum chemical calculations have been reported for sulfur-rich compounds in the past two decades. These calculations were used to investigate molecular structures and spectroscopic properties, as well as to understand the nature chemical bonding and reaction mechanism. Many high-level ab initio calculations were used for interpretation of experimental data and for providing accurate predictions of molecular structures and thermochemical data where no reliable experimental values are available. In recent years, density functional calculations have been extensively tested and used on many first- and second-row compounds. These proven DFT methods look promising for larger systems because for their computational efficiency. 

Some tests by Koshy and Rukovena (110,111) with aqueous, high-relative-volatility systems (a >2) gave much lower random packing efficiencies at high and low L/V than close to total reflux. They interpreted the results as an LfV ratio effect however, underwetting (below) can also explain these data. 

Luis Baiba has recently proposed that inexpensive spot tests, which can be done in the field, can be used as an efficient proxy for the elemental and organic analyses. He demonstrated that patterns revealed by spot test measurements of pH, carbonate, phosphate, and organic materials correspond closely to those revealed by the more sophisticated analyses. Although the data from spot tests are difficult to interpret in terms of specific activities, they are quite helpful in selecting much smaller subsets of the original samples that can then by analyzed for elements and organic molecules. 

In this chapter, we describe protocols to set up BRET-based arrestin recruitment test systems. We provide suggestions for troubleshooting and identify experimental parameters that can be varied. We also discuss potential pitfalls and, importandy, some limitations of BRET as a quantitatively comparative method. Indeed, BRET is now widely used as a proximity-based assay to detect arrestin recruitment, but it is often overlooked that, besides proximity, the relative orientations of the probes crucially determines BRET efficiency. This somewhat complicates the accurate interpretation of BRET data, but careful setup and combination of different BRET systems hold promise for the study of yet underexplored questions in chemokine receptor signaling. 

---