Quantitative biases in the abundance of precursor and product ions due to mass discrimination in RF-only ion guides results in inaccurate collision induced dissociation (CID) spectra. We evaluated the effects of collision cell RF voltage and collision energy on CID spectra using ten singly protonated compounds (46–854 Da) in an orthogonal acceleration time-of-flight mass spectrometer. The relative ion transfer efficiency, i.e. the relative amount of ions transferred through the ion guide at any particular RF voltage was shown to be dependent on the ion’s m/z. We developed an algorithm to correct for the mass discriminating effects of RF voltage on CID spectra. The algorithm was tested for both precursor and product ions at multiple RF voltages and collision energies in order to ensure reliability. Our results suggest that compounds that generate major product ions with m/z values <150 have peak intensities that deviate substantially from their actual abundance. This has implications for small molecule metabolomics research, particularly for studies that rely on CID spectra matching methods for structure identification.
Metabolite structure identification remains a significant challenge in nontargeted metabolomics research. One commonly used strategy relies on searching biochemical databases using exact mass. However, this approach fails when the database does not contain the unknown metabolite (i.e., for unknown-unknowns). For these cases, constrained structure generation with combinatorial structure generators provides a potential option. Here we evaluated structure generation constraints based on the specification of: (1) substructures required (i.e., seed structures); (2) substructures not allowed; and (3) filters to remove incorrect structures. Our approach (database assisted structure identification, DASI) used predictive models in MolFind to find candidate structures with chemical and physical properties similar to the unknown. These candidates were then used for seed structure generation using eight different structure generation algorithms. One algorithm was able to generate correct seed structures for 21/39 test compounds. Eleven of these seed structures were large enough to constrain the combinatorial structure generator to fewer than 100,000 structures. In 35/39 cases, at least one algorithm was able to generate a correct seed structure. The DASI method has several limitations and will require further experimental validation and optimization. At present, it seems most useful for identifying the structure of unknown-unknowns with molecular weights <200 Da.
Employee retention has been a buzzword for quiet sometime now. Companies across the globe are facing challenges vis-à-vis retaining their high potential or key employees. Many a practitioners have tried to device ways and means to counter the menace of attrition. With globalization, reaching its zenith coupled with opportunities emanating from otherwise considered the defensive sectors (like health and education) have only added to the agony of many enterprises. Presented below is the attrition rate in BPO industry in 2007 Attrition rates* US 42% Australia 29% Europe 24% India 18% Global Average 24%
* Source-Times News New YorkAlthough there has been a recent resurgence of interest in attrition, it is an underreported and understudied phenomenon despite its potential to introduce bias. This paper is an attempt to answer the question of retaining the Key Result Employees (KRE). An attempt has also been made to identify the areas where special emphasis and strategies has to be deployed in order to effectively counter the menace of attrition
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