The reactions of the molecular nitrogen doubly charged ion with neutral molecules of relevance to planetary ionospheres

Diatomic dications (e.g. C02+) have been known to exist for several decades and are believed to be important components of energised media. Molecular dications possess significant internal energy due to the Coulombic repulsion of their two positive charges, meaning that many possible reaction channels are available to dications in a collision with a neutral molecule. Modellers have recently predicted that N22+ is present in the ionosphere of Earth and Titan as well as the dications C>22+ and 02+ in the ionosphere of Earth and CC>22+ in the ionosphere of Mars. These recent predictions, of dications in planetary ionospheres, imply that dications, and processes involving dication-neutral collisions, may have more significance than previously thought in the upper atmospheres of planets. Therefore this thesis describes a study of the reactions between N2 dications and neutrals, potentially of relevance to the ionosphere of Earth and Titan. A position sensitive coincidence (PSCO) time-of flight (TOF) mass spectrometer is used to probe the reactivity, energetics and dynamics of the bimolecular reactions of N22 . Dication-neutrals reactions often result in a pair of singly charged ions. The PSCO experiment is used to collect these pairs of singly-charged ions in coincidence. From the position-sensitive data we extract the velocity vectors of the product ions, and if the reaction of interest involves the formation of a third, undetected, neutral species, its velocity can be determined via conservation of momentum. The electron transfer reactions between dications and neutrals have been well rationalized 2+ previously, so only the electron transfer reactions of N2 with Ne and NO are discussed in this thesis. This thesis concentrates on probing the less well rationalized, bond- forming reactions between dications and neutrals. The bond-forming reactions of N22+ with O2, CO2, H2O, C2H2, CH4, H2 and Ar have been investigated and discussed. Several new bond-forming reactions mechanisms are derived for example, the bond-forming reactions of N22+ with O2 proceed via a 'long' lived complex which dissociates via loss of a neutral and then charge separation, a mechanism which is also operating for one of the bond-forming reactions of N2 with CO2 and N2 with H2O. Additional bond-forming reactions are detected for N22+ with CO2 and H2O, which proceed via shorter lived collision complexes. The reactions of N22+ with C2H2, CH4, H2 and Ar all proceed via a variety of mechanisms involving short-lived collision complexes or H and electron stripping

Modelling the role of tissue heterogeneity in epileptic rhythms

Epileptic seizure activity manifests as complex spatio-temporal dynamics on the clinically relevant macroscopic scale. These dynamics are known to arise from spatially heterogeneous tissue, but the relationship between specific spatial abnormalities and epileptic rhythm generation is not well understood. We formulate a simplified macroscopic modelling framework with which to study the role of spatial heterogeneity in the generation of epileptiform spatio-temporal rhythms. We characterize the overall model dynamics in terms of spontaneous activity and excitability and demonstrate normal and abnormal spreading of activity. We introduce a means to systematically investigate the topology of abnormal sub-networks and explore its impact on spontaneous and stimulus-evoked rhythmic dynamics. This computationally efficient framework complements results from detailed biophysical models, and allows the testing of specific hypotheses about epileptic dynamics on the macroscopic scale

Additional file 13: of Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants

Triple quadrupole LC-MS/MS chromatographs representing 20 BIA-accumulating plant species. Peak annotation was performed manually based on comparison with retention times (Rt) and collision-induced dissociation (CID) spectra (Additional file 14) of authentic standards. Identified peaks are numbered in correspondence with those listed in Additional file 14. Species abbreviations are defined in Table 1. (PDF 1561 kb

Additional file 5: of Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants

Two-dimensional principal component analysis (PCA) of metabolite quantities obtained using LC/DFI-MS/MS-based profiling. Results are presented as scores (A) and loadings (B) plots. The percent variance accounted for by each principal component (PC) is indicated. For the scores plot, each dot represents a one of four replicates analyzed per plant species. Areas enclosed by 95 % confidence ellipses, containing dots of the same color, define statistically significant class separations [34]. Species abbreviations are defined in Table 1. Loadings representing individual metabolites are shown as black dots (B). Metabolites are indicated for select loadings. A complete listing of loadings data is found in Additional file 16. Abbreviations: C, acylcarnitine; SM, sphingomyelin; PC, phosphatidylcholine; aa, diacyl; ae, acyl-ester. A complete listing of full compound names and abbreviations is available online: http://www.biocrates.com/products/research-products/absoluteidq-p150-kit . (PDF 1591 kb

COPD Exacerbation Biomarkers Validated Using Multiple Reaction Monitoring Mass Spectrometry

<div><p>Background</p><p>Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) result in considerable morbidity and mortality. However, there are no objective biomarkers to diagnose AECOPD.</p><p>Methods</p><p>We used multiple reaction monitoring mass spectrometry to quantify 129 distinct proteins in plasma samples from patients with COPD. This analytical approach was first performed in a biomarker cohort of patients hospitalized with AECOPD (Cohort A, n = 72). Proteins differentially expressed between AECOPD and convalescent states were chosen using a false discovery rate <0.01 and fold change >1.2. Protein selection and classifier building were performed using an elastic net logistic regression model. The performance of the biomarker panel was then tested in two independent AECOPD cohorts (Cohort B, n = 37, and Cohort C, n = 109) using leave-pair-out cross-validation methods.</p><p>Results</p><p>Five proteins were identified distinguishing AECOPD and convalescent states in Cohort A. Biomarker scores derived from this model were significantly higher during AECOPD than in the convalescent state in the discovery cohort (p<0.001). The receiver operating characteristic cross-validation area under the curve (CV-AUC) statistic was 0.73 in Cohort A, while in the replication cohorts the CV-AUC was 0.77 for Cohort B and 0.79 for Cohort C.</p><p>Conclusions</p><p>A panel of five biomarkers shows promise in distinguishing AECOPD from convalescence and may provide the basis for a clinical blood test to diagnose AECOPD. Further validation in larger cohorts is necessary for future clinical translation.</p></div

Biomarker Score Intercept and Specific Protein Weights.

<p>Biomarker Score Intercept and Specific Protein Weights.</p

Biomarker Scores Comparing AECOPD to Non-AECOPD States.

<p>Biomarker scores for Cohorts A, B, and C are shown as box-and-whisker plots. Biomarker scores were significantly elevated during the time of AECOPD (red) but fell during the convalescent phase (yellow) (Wilcoxon rank sum p-value <0.001 for Cohorts A, B, and C). The convalescent phase scores for Cohorts A, B, and C showed no statistically significant differences.</p