Rocket-UV Spectrometer

This is a report of the second three months (March-May 1961) of a program to design and fabricate an ultraviolet spectrometer and fine guidance control for use in an Aerobee-Hi rocket. The work is being done under Subcontract No. 1 under Contract NASr-3 between Princeton University and the National Aeronautical and Space Administration. The design goals for this instrument are described in the report for the first three month period (Perkin-Elmer Engineering Report No. 5906). The accomplishments of the second three month period include the solution of certain design problems, the establishment of an effective liaison system with personnel at Goddard Space Flight Center, and the completion of certain design and fabrication tasks

MetaboCraft: building a Minecraft plugin for metabolomics

Motivation: The rapid advances in metabolomics pose a significant challenge in presentation and interpretation of results. Development of new, engaging visual aids is crucial to advancing our understanding of new findings. Results: We have developed MetaboCraft, a Minecraft plugin which creates immersive visualisations of metabolic networks and pathways in a 3-D environment and allows the results of user experiments to be viewed in this context, presenting a novel approach to exploring the metabolome

Multidimensional liquid chromatographic separations for proteomics

Sample complexity is one of the key challenges facing contemporary proteomic analysis. A variety of methods is commonly employed to reduce this complexity, both at an intact protein and digested peptide level. For complex lysates containing many thousands of proteins, orthogonal (mutually independent), multidimensional separation methods must be employed to provide sufficient resolution to characterize the appropriate number of different species. The most common of these methods are two dimensional gel electrophoresis (2DGE) of proteins and multidimensional liquid chromatographic separation (MuDPIT) of peptides, which rely on isoelectric focusing followed by mass separation in the former, and ion exchange followed by reversed phase separation in the latter. These methods have significant drawbacks in terms of sample bias, sample preparation and reproducibility, and therefore a new methodology that combines the positive aspects of both separation technologies in an automatable, reproducible form is highly desirable. New developments in column technology have allowed rapid improved-resolution separation of intact proteins in complex samples, coupled to improved methodology for peptide and protein identification. The separation of complex protein mixtures using both on- and off-line 2D liquid chromatography using derivitized polystyrene-divinylbenzene (PS-DVB) pellicular ion-exchange resins and PS-DVB monolithic reversed-phase columns is described. Proteolytic digestion of the fractions followed by rapid liquid chromatography - tandem mass spectrometry was used to complete the analysis. An alternative methodology, relying on direct analysis of the second dimension eluents by top-down (mass spectrometric analysis of intact proteins) methodology, using an Apex IV 12 T Fourier-transform ion cyclotron resonance mass spectrometer (Bruker Daltonics) and an HCT ion trap (Bruker Daltonics) equipped with electron transfer dissociation has allowed in-depth analysis of intact proteins. Sample types investigated to establish the utility of the methodology include bacterial lysates (Bordetella parapertusis, and Escherichia coli), a eukaryotic parasite (Leishmania donovani), and transformed human cell lines. These developments lead to a multidimensional intact protein separation methodology suitable for small-sample proteomics (minimum effective protein load of 200 μg) and good reproducibility (1.5% variation in the ion exchange dimension, 0.5% variation in the reversed phase dimension). Analysis of the digested fractions gave good coverage of the proteome as well as a high predicted dynamic range, capable of detecting proteins with codon adaptation index scores ranging from 0.22 to 0.99, out of a logarithmic scale from 0 to 1. Proteins representing low (8 kDa) and high (500 kDa) molecular mass and extremes of predicted pI were identified, as well as a number of membrane proteins. Resolution of the overall protein separation was such that single protein species often occurred in one or two fractions for both the ion-exchange and reversed phase separations, with the fractions varying in complexity. Separation of modified proteins in the ion-exchange dimension demonstrated separation of isoforms. Most analyses coupled anion-exchange chromatography in the first dimension to monolithic reversed phase separation in the second dimension. To provide alternative first dimension methodologies for specific sample types, external gradient chromatofocussing (based on separation by isoelectric point) and high-pH ion-pair reversed phase were evaluated as additional techniques. In particular the pISEP (CryoBioPhysica) technique for chromatofocussing constituted an effective orthogonal separation methodology for separation, and its use in a proteomics context was compared to that of the original anion-exchange, reversed phase technology. To rapidly analyse the large number of fractions generated by the technique, bottom-up protocols required improvements in the throughput of peptide separations. PS-DVB monoliths were employed for rapid peptide separations and conditions for analysis were evaluated and optimized. The implementation of a parallel 200 μm monolith system for tryptic peptide separations ensured minimal sample loss and improved sample throughput with little loss of sensitivity. For simple mixtures, reversed-phase separation times could be reduced to a few minutes without significantly affecting data content, although rapid scanning capability is essential due to the very narrow peak widths. Quantitation is of paramount importance to any proteomic technique, and liquid chromatographic separation of intact proteins provides flexibility for differential analysis of complex samples. Three categories of quantitative analysis were evaluated for two dimensional intact protein separation by liquid chromatography: ultraviolet-absorbance maps, isotopic labeling and label-free computational analyses. UV-absorbance maps of wild-type and pentamidine resistant Leishmania donovani were compared using standard two dimensional gel electrophoresis analysis software and resulted in the identification of a small number of quantitiative differences. Modifications to the isotope coded affinity tag (ICAT) and isotope tags for relative and absolute quantitation (ITRAQ) protocols were developed to allow protein labeling prior to separation, and the related methodologies ExacTag, isotope coded protein label (ICPL) and stable isotope labels for amino acids in culture (SILAC) were evaluated. Finally, label-free techniques have been employed for protein quantitation by liquid chromatography (LC)/Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). A particular niche for liquid chromatographic separation of intact proteins is in top-down analysis, in which mass spectrometric analysis of intact proteins is performed. The separation technology was directly coupled to high-resolution FT-ICR MS for analysis of standards, mixtures, and cellular lysates, leading to the identification of an intact Leishmania protein and post-translational modification (PTM) mapping of histone H4. In addition, the recently developed electron transfer dissociation (ETD) fragmentation methods coupled with proton transfer reaction (PTR) for charge reduction allowed analysis of standards and isotopically labeled cellular lysates using an ion trap instrument. In summary, we have developed a general proteomic methodology with unique flexibility as well as applicability to top-down analysis. It has been applied to multiple complex samples in a variety of analysis conditions including quantitation methodologies and state-of-the-art mass spectrometric techniques. In general, the method equals other separation methods in terms of protein identification rates, is substantially more reproducible and automated, but is more time-consuming. Currently, two dimensional intact protein separation by liquid chromatography using polystyrene-divinylbenzene-based columns is particularly applicable to top-down analysis of heavily modified proteins. However, there is considerable remaining room for optimization and improvement of methodologies, and further development will enhance the technique for general use

MetAssign: probabilistic annotation of metabolites from LC–MS data using a Bayesian clustering approach

Motivation: The use of liquid chromatography coupled to mass spectrometry (LC–MS) has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This paper looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.<p></p> Results: The Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations.<p></p> Availability: The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/

Minimal Structure and Motion Problems for TOA and TDOA Measurements with Collinearity Constraints

Structure from sound can be phrased as the problem of determining the position of a number of microphones and a number of sound sources given only the recorded sounds. In this paper we study minimal structure from sound problems in both TOA (time of arrival) and TDOA (time difference of arrival) settings with collinear constraints on e.g. the microphone positions. Three such minimal cases are analyzed and solved with efficient and numerically stable techniques. An experimental validation of the solvers are performed on both simulated and real data. In the paper we also show how such solvers can be utilized in a RANSAC framework to perform robust matching of sound features and then used as initial estimates in a robust non-linear leastsquares optimization

Smoking and stroke: A mendelian randomization study

Whether smoking is causally associated with risk of ischemic stroke and intracerebral hemorrhage is unknown. We used the Mendelian randomization design to explore the associations of genetic predisposition to smoking with ischemic stroke and its subtypes as well as intracerebral hemorrhage. Up to 372 single-nucleotide polymorphisms were used as instrumental variables for smoking initiation. We used summary statistics data for 438 847 individuals in the analyses of ischemic stroke (34 217 cases and 404 630 non-cases) and 3026 individuals in analyses of intracerebral hemorrhage (1545 cases and 1481 non-cases). Genetic predisposition to smoking initiation was statistically significantly positively associated with any ischemic stroke, large artery stroke, and small vessel stroke but not cardioembolic stroke or intracerebral hemorrhage. The odds ratios per one standard deviation higher log-odds of ever smoking regularly (smoking initiation) were 1.24 (95% CI 1.16-1.32; p = 1.310-10) for any ischemic stroke, 1.64 (95% CI 1.40-1.91; p = 2.810-10) for large artery stroke, 1.47 (95% CI 1.26-1.71; p = 1.110-6) for small vessel stroke, 1.12 (95% CI 0.99-1.27; p = 0.08) for cardioembolic stroke, and 1.13 (95% CI 0.81-1.58; p = 0.47) for intracerebral hemorrhage. This study provides genetic support for a causal association of smoking with ischemic stroke, particularly large artery and small vessel stroke.his work was supported by the Swedish Research Council for Health, Working Life and Welfare (Forskningsrådet för hälsa, arbetsliv och välfärd) and the Swedish Research Council. S.B. is supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 204623/Z/16/Z)

Serum magnesium levels and risk of coronary artery disease: Mendelian randomisation study.

Background. Observational studies have shown that serum magnesium levels are inversely associated risk of cardiovascular disease, but whether this association is causal is unknown. We conducted a Mendelian randomization study to investigate whether serum magnesium levels may be causally associated with coronary artery disease (CAD). Methods: This Mendelian randomization analysis is based on summary-level data from the CARDIoGRAMplusC4D consortium’s 1000 Genomes-based genome-wide association meta-analysis of 48 studies with a total 60,801 CAD cases and 123,504 non-cases. Six single nucleotide polymorphisms (SNPs) associated with serum magnesium levels at genome-wide significance were used as instrumental variables. Results: A genetic predisposition to higher serum magnesium levels was inversely associated with CAD. In conventional Mendelian randomization analysis, the odds ratio of CAD was 0.88 (95% confidence interval [CI]: 0.78 to 0.99; P = 0.03) per 0.1 mmol/L (about 1 standard deviation) increase in genetically predicted serum magnesium levels. Results were consistent in sensitivity analyses using the weighted median and heterogeneity-penalized model averaging methods, with odds ratios of 0.84 (95% CI: 0.72 to 0.98; P = 0.03) and 0.83 (95% CI: 0.71 to 0.96; P = 0.02), respectively. Conclusions: This study based on genetics provides evidence that serum magnesium levels are inversely associated with risk of CAD. Randomized controlled trials elucidating whether magnesium supplementation lowers the risk of CAD, preferably in a setting at higher risk of hypomagnesemia, are warranted

IGF-1 and cardiometabolic diseases: a Mendelian randomisation study

AIMS/HYPOTHESIS: Abnormal serum IGF-1 levels are associated with an increased risk of type 2 diabetes and cardiovascular disease. However, the causal role of IGF-1 levels within the normal range in cardiometabolic disease remains unclear. We employed Mendelian randomisation to explore the associations between genetically predicted serum IGF-1 levels and cardiometabolic diseases. METHODS: Serum IGF-1 levels were predicted using 416 SNPs associated with IGF-1 levels among 358,072 individuals in UK Biobank. Genetic association estimates for the outcomes were obtained from consortia of type 2 diabetes (74,124 cases, 824,006 controls), coronary artery disease (60,801 cases, 123,504 controls), heart failure (47,309 cases, 930,014 controls), atrial fibrillation (65,446 cases, 522,744 controls), and ischaemic stroke (60,341 cases, 454,450 controls). RESULTS: Genetic predisposition to elevated serum IGF-1 levels was associated with higher risk of type 2 diabetes and coronary artery disease. The OR (95% CI) per SD increment in IGF-1 level was 1.14 (1.05, 1.24) for type 2 diabetes and 1.09 (1.02, 1.16) for coronary artery disease. The association between IGF-1 and coronary artery disease was attenuated after adjustment for type 2 diabetes (OR 1.06 [95% CI 1.00, 1.13]), suggesting that the association may be partly mediated via type 2 diabetes. There was limited evidence of associations between IGF-1 levels and heart failure, atrial fibrillation and ischaemic stroke. CONCLUSIONS/INTERPRETATION: This study found evidence that increased IGF-1 levels may be causally associated with higher risk of type 2 diabete

The emergence of proton nuclear magnetic resonance metabolomics in the cardiovascular arena as viewed from a clinical perspective

The ability to phenotype metabolic profiles in serum has increased substantially in recent years with the advent of metabolomics. Metabolomics is the study of the metabolome, defined as those molecules with an atomic mass less than 1.5 kDa. There are two main metabolomics methods: mass spectrometry (MS) and proton nuclear magnetic resonance (1H NMR) spectroscopy, each with its respective benefits and limitations. MS has greater sensitivity and so can detect many more metabolites. However, its cost (especially when heavy labelled internal standards are required for absolute quantitation) and quality control is sub-optimal for large cohorts. 1H NMR is less sensitive but sample preparation is generally faster and analysis times shorter, resulting in markedly lower analysis costs. 1H NMR is robust, reproducible and can provide absolute quantitation of many metabolites. Of particular relevance to cardio-metabolic disease is the ability of 1H NMR to provide detailed quantitative data on amino acids, fatty acids and other metabolites as well as lipoprotein subparticle concentrations and size. Early epidemiological studies suggest promise, however, this is an emerging field and more data is required before we can determine the clinical utility of these measures to improve disease prediction and treatment. This review describes the theoretical basis of 1H NMR; compares MS and 1H NMR and provides a tabular overview of recent 1H NMR-based research findings in the atherosclerosis field, describing the design and scope of studies conducted to date. 1H NMR metabolomics-CVD related research is emerging, however further large, robustly conducted prospective, genetic and intervention studies are needed to advance research on CVD risk prediction and to identify causal pathways amenable to intervention