Extraction of the πNN\pi NN coupling constant from NN scattering data

We reexamine Chew's method for extracting the $\pi NN$ coupling constant from np differential cross section measurements. Values for this coupling are extracted below 350 MeV, in the potential model region, and up to 1 GeV. The analyses to 1~GeV have utilized 55 data sets. We compare these results to those obtained via $\chi^2$ mapping techniques. We find that these two methods give consistent results which are in agreement with previous Nijmegen determinations.Comment: 12 pages of text plus 2 figures. Revtex file and postscript figures available via anonymous FTP at ftp://clsaid.phys.vt.edu/pub/n

Assessing the Potential of Untargeted SWATH Mass Spectrometry-Based Metabolomics to Differentiate Closely Related Exposures in Observational Studies

Mass spectrometry (MS) is increasingly used in clinical studies to obtain molecular evidence of chemical exposures, such as tobacco smoke, alcohol, and drugs. This evidence can help verify clinical data retrieved through anamnesis or questionnaires and may provide insights into unreported exposures, for example those classified as the same despite small but possibly relevant chemical differences or due to contaminants in reported exposure compounds. Here, we aimed to explore the potential of untargeted SWATH metabolomics to differentiate such closely related exposures. This data-independent acquisition MS-based profiling technique was applied to urine samples of 316 liver and 570 kidney transplant recipients from the TransplantLines Biobank and Cohort Study (NCT03272841), where we focused on the immunosuppressive drug mycophenolate, which is either supplied as a morpholino-ester prodrug or as an enteric-coated product, the illicit drug cocaine, which is usually supplied as an adulterated product, and the proton pump inhibitors omeprazole and esomeprazole. Based on these examples, we found that untargeted SWATH metabolomics has considerable potential to identify different (unreported) exposure or co-exposure metabolites and may determine variations in their abundances. We also found that these signals alone may sometimes be unable to distinguish closely related exposures, and enhancement of differentiation, for example by integration with pharmacogenomics data, is needed

Mapping differential interactomes by affinity purification coupled with data independent mass spectrometry acquisition

Characterizing changes in protein-protein interactions associated with sequence variants (e.g. disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies where cost and time are major considerations. To this end, we have coupled AP to data-independent mass spectrometric acquisition (SWATH), and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. Here, we use AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes, and propose a scalable pipeline for systems biology studies

SWATH acquisition mode for drug metabolism and metabolomics investigations

Aim: Sequential window acquisition of all theoretical fragment-ion spectra (SWATH) has recently emerged as a powerful high resolution mass spectrometric data independent acquisition technique. In the present work, the potential and challenges of an integrated strategy based on LC-SWATH/MS for simultaneous drug metabolism and metabolomics studies was investigated. Methodology: The richness of SWATH data allows numerous data analysis approaches, including: detection of metabolites by prediction; metabolite detection by mass defect filtering; quantification from high-resolution MS precursor chromatograms or fragment chromatograms. Multivariate analysis can be applied to the data from the full scan or SWATH windows and allows changes in endogenous metabolites as well as xenobiotic metabolites, to be detected. Principal component variable grouping detects intersample variable correlation and groups variables with similar profiles which simplifies interpretation and highlights related ions and fragments. Principal component variable grouping can extract product ion spectra from the data collected by fragmenting a wide precursor ion window. Conclusion: It was possible to characterize 28 vinpocetine metabolites in urine, mostly mono- and di-hydroxylated forms, and detect endogenous metabolite expression changes in urine after the administration of a single dose of a model drug (vinpocetine) to rats. </jats:p

SWATH data independent acquisition mass spectrometry for metabolomics

Systems Biology and ‘Omics’ require reproducible identification and quantitation of many compounds, preferably in large sample cohorts. Liquid chromatography-mass spectrometry is important since data generated can be used for structure elucidation and highly specific targeted quantitation. Despite great success, the technique has limitations such as: compound coverage in one analysis, method development time and single sample analysis time which determines throughput. New instrument capabilities have led to improved methods, including ‘Data Independent Acquisition’ so-called because acquisition is not changed by acquired data. SWATH-MS is a specific example that has quickly become prominent in proteomics because of increased peptide coverage, high quantitation accuracy, excellent reproducibility and the generation of a ‘digital map’. These capabilities are important in small molecules analyses although uptake in these applications has been slower. We describe the SWATH-MS technique, review its use in applications such as metabolomics and forensics, and summarize on-going improvements and future prospects

Controlled Formation of Protonated and Radical Cation Precursor Ions by Atmospheric Pressure Photoionization with μLC-MS Enables Electron Ionization and MS/MS Library Search

Atmospheric pressure photoionization (APPI) was developed as an alternative to electrospray ionization (ESI) for the generation of protonated molecules using liquid chromatography and optimized using dopants such as toluene, which predominantly forms protonated molecules, and chlorobenzene, which favors the formation of radical cations, although the latter has not been fully exploited. Based on 40 diverse low-molecular-weight compounds and micro liquid chromatography (μLC) coupled with APPI tandem mass spectrometry (APPI- MS/MS), the potential of radical cations was investigated. Chromatographic and ionization conditions were decoupled by post-column addition of methanol, allowing separate study and optimization. Due to the mass flow sensitive behavior of APPI, sensitivity is not affected by post-column dilution, and for 8 of 35 analytes, the radical cation response with μLC-APPI is better than for protonated molecules using μLC-ESI. Collision-induced fragmentation (CID) of radical cations produced within a collision energy range from 10−115 eV have, in the median, 65% of the fragments found in electron ionization (EI) spectra. This similarity allowed identification of 86% of the analytes using data-dependent acquisition (DDA) of radical cations and NIST EI library searches. We propose a workflow that uses multimodal DDA of protonated precursor molecules using ESI or APPI with toluene as a dopant, and radical cations produced by chlorobenzene-assisted μLC-APPI with post-column addition of methanol. This increases the confidence of molecular identification by allowing orthogonal library searches using MS/MS libraries for protonated precursor CID spectra and EI libraries for radical cation CID spectra.</p

Hybrid SWATH/MS and HR-SRM/MS acquisition for phospholipidomics using QUAL/QUANT data processing

A hybrid SWATH/MS and HR-SRM/MS acquisition approach using multiple unit mass windows and 100 u precursor selection windows has been developed to interface with a chromatographic lipid class separation. The method allows for the simultaneous monitoring of sum compositions in MS1 and up to 48 lipids in MS2 per lipid class. A total of 240 lipid sum compositions from five phospholipid classes could be monitored in MS2 (HR-SRM/MS) while there was no limitation in the number of analytes in MS1 (HR-SIM/MS). On average, 92 lipid sum compositions and 75 lipid species could be quantified in human plasma samples. The robustness and precision of the workflow has been assessed using technical triplicates of the subject samples. Lipid identification was improved using a combined qualitative and quantitative data processing based on prediction instead of library search. Lipid class specific extracted ion currents of precursors and the corresponding molecular species fragments were extracted based on the information obtained from lipid building blocks and a combinatorial strategy. The SWATH/MS approach with the post-acquisition processing is not limited to the analyzed phospholipid classes and can be applied to other analytes and samples of interest

Determinants of National R&D and Patenting: Application to a Small, Distant Country

We analyse the determinants of national R&D expenditure and patenting activity. In contrast to most related studies, we account for factors that impact on small, distant countries. These factors include country size, firm size, distance from major economic centres, and industrial structure. We apply the results to New Zealand, which has a low rate of privately funded R&D. We find that R&D expenditure and patenting activity are negatively affected by having a preponderance of small firms, having a heavy reliance on agriculture and also by distance of a country from major world centres. Population size is found to have no impact on either R&D or patenting. Greater R&D increases patenting, with an elasticity that indicates moderately increasing returns to scale in the relationship between R&D inputs and patent outcomes. Better intellectual property protection within a country also increases patenting activity. Once we control for these factors, New Zealand is not an outlier with respect to its R&D expenditures; it is a positive outlier with regard to patenting.R&D; patents; economic geography