Advances in structure elucidation of small molecules using mass spectrometry

The structural elucidation of small molecules using mass spectrometry plays an important role in modern life sciences and bioanalytical approaches. This review covers different soft and hard ionization techniques and figures of merit for modern mass spectrometers, such as mass resolving power, mass accuracy, isotopic abundance accuracy, accurate mass multiple-stage MS(n) capability, as well as hybrid mass spectrometric and orthogonal chromatographic approaches. The latter part discusses mass spectral data handling strategies, which includes background and noise subtraction, adduct formation and detection, charge state determination, accurate mass measurements, elemental composition determinations, and complex data-dependent setups with ion maps and ion trees. The importance of mass spectral library search algorithms for tandem mass spectra and multiple-stage MS(n) mass spectra as well as mass spectral tree libraries that combine multiple-stage mass spectra are outlined. The successive chapter discusses mass spectral fragmentation pathways, biotransformation reactions and drug metabolism studies, the mass spectral simulation and generation of in silico mass spectra, expert systems for mass spectral interpretation, and the use of computational chemistry to explain gas-phase phenomena. A single chapter discusses data handling for hyphenated approaches including mass spectral deconvolution for clean mass spectra, cheminformatics approaches and structure retention relationships, and retention index predictions for gas and liquid chromatography. The last section reviews the current state of electronic data sharing of mass spectra and discusses the importance of software development for the advancement of structure elucidation of small molecules

Integrated data base for 1993: US spent fuel and radioactive waste inventories, projections, and characteristics. Revision 9

The Integrated Data Base (IDB) Program has compiled historic data on inventories and characteristics of both commercial and DOE spent fuel; also, commercial and U.S. government-owned radioactive wastes through December 31, 1992. These data are based on the most reliable information available from government sources, the open literature, technical reports, and direct contacts. The information forecasted is consistent with the latest U.S. Department of Energy/Energy Information Administration (DOE/EIA) projections of U.S. commercial nuclear power growth and the expected DOE-related and private industrial and institutional (I/I) activities. The radioactive materials considered, on a chapter-by-chapter basis, are spent nuclear fuel, high-level waste (HLW), transuranic (TRU), waste, low-level waste (LLW), commercial uranium mill tailings, environmental restoration wastes, commercial reactor and fuel-cycle facility decommissioning wastes, and mixed (hazardous and radioactive) LLW. For most of these categories, current and projected inventories are given through the calendar-year (CY) 2030, and the radioactivity and thermal power are calculated based on reported or estimated isotopic compositions. In addition, characteristics and current inventories are reported for miscellaneous radioactive materials that may require geologic disposal

Congruent strategies for carbohydrate sequencing. 3. OSCAR: An algorithm for assigning oligosaccharide topology from MSn data

This is the third in a sequence of reports devoted to the development of congruent strategies for carbohydrate sequencing. Two previous reports outlined the strategies for observing structural detail from MSn data and introduced tools that compile, search, and compare fragment spectra in a bottom-up approach to oligosaccharide sequencing. In this third report, we. introduce the operational details of an algorithm that we define as the Oligosaccharide Subtree Constraint Algorithm (OSCAR). This algorithm assimilates analyst-selected MSn ion fragmentation pathways into oligosaccharide topology (branching and linkage) using what may be considered a top-down sequencing strategy. Guided by a series of logical constraints, this de novo algorithm provides molecular topology without presumed biosynthetic constraints or external comparisons. In this introductory study, OSCAR is applied to a series of permethylated oligomers and isomeric glycans, and topologies are assigned in a few hundredths of a second