Homogeneous analysis of a sample of Open Clusters in the context of the BOCCE project and the Gaia-ESO Survey

The open clusters (OC) are gravitationally bound systems of a few tens or hundreds of stars. In our Galaxy, the Milky Way, we know about 3000 open clusters, of very different ages in the range of a few millions years to about 9 Gyr. OCs are mainly located in the Galactic thin disc, with distances from the Galactic centre in the range 4-22 kpc and a height scale on the disc of about 200 pc. Their chemical properties trace those of the environment in which they formed and the metallicity is in the range -0.5<[Fe/H]<+0.5 dex. Through photometry and spectroscopy it is possible to study relatively easily the properties of the OCs and estimate their age, distance, and chemistry. For these reasons they are considered primary tracers of the chemical properties and chemical evolution of the Galactic disc. The main subject of this thesis is the comprehensive study of several OCs. The research embraces two different projects: the Bologna Open Cluster Chemical Evolution project (BOCCE) and the Gaia-ESO Survey. The first is a long-term programme, aiming at studying the chemical evolution of the Milky Way disc by means of a homogeneous sample of OCs. The latter is a large public spectroscopy survey, conducted with the high-resolution spectrograph FLAMES@VLT and targeting about 10^5 stars in different part of the Galaxy and 10^4 stars in about 100 OCs. The common ground between the two projects is the study of the properties of the OCs as tracers of the disc's characteristics. The impressive scientific outcome of the Gaia-ESO Survey and the unique framework of homogeneity of the BOCCE project can propose, especially once combined together, a much more accurate description of the properties of the OCs. In turn, this will give fundamental constraints for the interpretation of the properties of the Galactic disc.

Radio halos in a mass-selected sample of galaxy clusters

A fraction of galaxy clusters host Mpc-scale Radio Halos (RH), generated by ultrarelativistic electrons in the magnetized intra cluster medium (ICM). In the current view they trace turbulent regions in merging clusters, where relativistic particles are trapped and accelerated. This model has clear expectations about the statistical properties of RHs. To test these expectations large mass-selected samples of galaxy clusters with adequate radio and X-ray data are necessary. We used the Planck SZ cluster catalogue as suitable starting point of our investigation, selecting clusters with M500>6x10^14 Msun at 0.08sample with the NVSS for clusters at z<0.2 and with the Extended GMRT RH Survey for 0.2

Species specific nitrogen isotope analysis by NanoSIMS

Der atmosphärische Kreislauf reaktiver Stickstoffverbindungen beschäftigt sowohl die Naturwissenschaftler als auch die Politik. Dies ist insbesondere darauf zurückzuführen, dass reaktive Stickoxide die Bildung von bodennahem Ozon kontrollieren. Reaktive Stickstoffverbindungen spielen darüber hinaus als gasförmige Vorläufer von Feinstaubpartikeln eine wichtige Rolle und der Transport von reaktivem Stickstoff über lange Distanzen verändert den biogeochemischen Kohlenstoffkreislauf des Planeten, indem er entlegene Ökosysteme mit Stickstoff düngt. Die Messungen von stabilen Stickstoffisotopenverhältnissen (15N/14N) bietet ein Hilfsmittel, welches es erlaubt, die Quellen von reaktiven Stickstoffverbindungen zu identifizieren und die am Stickstoffkeislauf beteiligten Reaktionen mithilfe ihrer reaktionsspezifischen Isotopenfraktionierung genauer zu untersuchen. rnIn dieser Doktorarbeit demonstriere ich, dass es möglich ist, mit Hilfe von Nano-Sekundärionenmassenspektrometrie (NanoSIMS) verschiedene stickstoffhaltige Verbindungen, die üblicherweise in atmosphärischen Feinstaubpartikeln vorkommen, mit einer räumlichen Auflösung von weniger als einem Mikrometer zu analysieren und zu identifizieren. Die Unterscheidung verschiedener stickstoffhaltiger Verbindungen erfolgt anhand der relativen Signalintensitäten der positiven und negativen Sekundärionensignale, die beobachtet werden, wenn die Feinstaubproben mit einem Cs+ oder O- Primärionenstrahl beschossen werden. Die Feinstaubproben können direkt auf dem Probenahmesubstrat in das Massenspektrometer eingeführt werden, ohne chemisch oder physikalisch aufbereited zu werden. Die Methode wurde Mithilfe von Nitrat, Nitrit, Ammoniumsulfat, Harnstoff, Aminosären, biologischen Feinstaubproben (Pilzsporen) und Imidazol getestet. Ich habe gezeigt, dass NO2 Sekundärionen nur beim Beschuss von Nitrat und Nitrit (Salzen) mit positiven Primärionen entstehen, während NH4+ Sekundärionen nur beim Beschuss von Aminosäuren, Harnstoff und Ammoniumsalzen mit positiven Primärionen freigesetzt werden, nicht aber beim Beschuss biologischer Proben wie z.B. Pilzsporen. CN- Sekundärionen werden beim Beschuss aller stickstoffhaltigen Verbindungen mit positiven Primärionen beobachtet, da fast alle Proben oberflächennah mit Kohlenstoffspuren kontaminiert sind. Die relative Signalintensität der CN- Sekundärionen ist bei kohlenstoffhaltigen organischen Stickstoffverbindungen am höchsten.rnDarüber hinaus habe ich gezeigt, dass an reinen Nitratsalzproben (NaNO3 und KNO3), welche auf Goldfolien aufgebracht wurden speziesspezifische stabile Stickstoffisotopenverhältnisse mithilfe des 15N16O2- / 14N16O2- - Sekundärionenverhältnisses genau und richtig gemessen werden können. Die Messgenauigkeit auf Feldern mit einer Rastergröße von 5×5 µm2 wurde anhand von Langzeitmessungen an einem hausinternen NaNO3 Standard als ± 0.6 ‰ bestimmt. Die Differenz der matrixspezifischen instrumentellen Massenfraktionierung zwischen NaNO3 und KNO3 betrug 7.1 ± 0.9 ‰. 23Na12C2- Sekundärionen können eine ernst zu nehmende Interferenz darstellen wenn 15N16O2- Sekundärionen zur Messung des nitratspezifischen schweren Stickstoffs eingesetzt werden sollen und Natrium und Kohlenstoff im selben Feinstaubpartikel als interne Mischung vorliegt oder die natriumhaltige Probe auf einem kohlenstoffhaltigen Substrat abgelegt wurde. Selbst wenn, wie im Fall von KNO3, keine derartige Interferenz vorliegt, führt eine interne Mischung mit Kohlenstoff im selben Feinstaubpartikel zu einer matrixspezifischen instrumentellen Massenfraktionierung die mit der folgenden Gleichung beschrieben werden kann: 15Nbias = (101 ± 4) ∙ f − (101 ± 3) ‰, mit f = 14N16O2- / (14N16O2- + 12C14N-). rnWird das 12C15N- / 12C14N- Sekundärionenverhältnis zur Messung der stabilen Stickstoffisotopenzusammensetzung verwendet, beeinflusst die Probematrix die Messungsergebnisse nicht, auch wenn Stickstoff und Kohlenstoff in den Feinstaubpartikeln in variablen N/C–Verhältnissen vorliegen. Auch Interferenzen spielen keine Rolle. Um sicherzustellen, dass die Messung weiterhin spezifisch auf Nitratspezies eingeschränkt bleibt, kann eine 14N16O2- Maske bei der Datenauswertung verwendet werden. Werden die Proben auf einem kohlenstoffhaltigen, stickstofffreien Probennahmesubstrat gesammelt, erhöht dies die Signalintensität für reine Nitrat-Feinstaubpartikel.

Informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography and high-resolution mass spectrometry (GCxGC-HRMS)

This paper describes informatics for cross-sample analysis with comprehensive two-dimensional gas chromatography (GCxGC) and high-resolution mass spectrometry (HRMS). GCxGC-HRMS analysis produces large data sets that are rich with information, but highly complex. The size of the data and volume of information requires automated processing for comprehensive cross-sample analysis, but the complexity poses a challenge for developing robust methods. The approach developed here analyzes GCxGC-HRMS data from multiple samples to extract a feature template that comprehensively captures the pattern of peaks detected in the retention-times plane. Then, for each sample chromatogram, the template is geometrically transformed to align with the detected peak pattern and generate a set of feature measurements for cross-sample analyses such as sample classification and biomarker discovery. The approach avoids the intractable problem of comprehensive peak matching by using a few reliable peaks for alignment and peak-based retention-plane windows to define comprehensive features that can be reliably matched for cross-sample analysis. The informatics are demonstrated with a set of 18 samples from breast-cancer tumors, each from different individuals, six each for Grades 1-3. The features allow classification that matches grading by a cancer pathologist with 78% success in leave-one-out cross-validation experiments. The HRMS signatures of the features of interest can be examined for determining elemental compositions and identifying compounds.

Sample size estimation: an overview with applications to orthodontic clinical trial designs

Proper sample size estimation is an important part of clinical trial methodology and closely related to the precision and power of the trial's results. Trials with sufficient sample sizes are scientifically and ethically justified and more credible compared with trials with insufficient sizes. Planning clinical trials with inadequate sample sizes might be considered as a waste of time and resources, as well as unethical, since patients might be enrolled in a study in which the expected results will not be trusted and are unlikely to have an impact on clinical practice. Because of the low emphasis of sample size calculation in clinical trials in orthodontics, it is the objective of this article to introduce the orthodontic clinician to the importance and the general principles of sample size calculations for randomized controlled trials to serve as guidance for study designs and as a tool for quality assessment when reviewing published clinical trials in our specialty. Examples of calculations are shown for 2-arm parallel trials applicable to orthodontics. The working examples are analyzed, and the implications of design or inherent complexities in each category are discussed.

Levels and determinants of inflammatory biomarkers in a Swiss population-based sample (CoLaus study)

Objective to assess the levels and determinants of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) in a healthy Caucasian population. Methods population sample of 2884 men and 3201 women aged 35 to 75. IL-1β, IL-6 and TNF-α were assessed by a multiplexed particle-based flow cytometric assay and CRP by an immunometric assay. Results Spearman rank correlations between duplicate cytokine measurements (N = 80) ranged between 0.89 and 0.96; intra-class correlation coefficients ranged between 0.94 and 0.97, indicating good reproducibility. Among the 6085 participants, 2289 (37.6%), 451 (7.4%) and 43 (0.7%) had IL-1β, IL-6 and TNF-α levels below detection limits, respectively. Median (interquartile range) for participants with detectable values were 1.17 (0.48–3.90) pg/ml for IL-1β; 1.47 (0.71–3.53) pg/ml for IL-6; 2.89 (1.82–4.53) pg/ml for TNF-α and 1.3 (0.6–2.7) ng/ml for CRP. On multivariate analysis, greater age was the only factor inversely associated with IL-1β levels. Male sex, increased BMI and smoking were associated with greater IL-6 levels, while no relationship was found for age and leisure-time PA. Male sex, greater age, increased BMI and current smoking were associated with greater TNF-α levels, while no relationship was found with leisure-time PA. CRP levels were positively related to age, BMI and smoking, and inversely to male sex and physical activity. Conclusion Population-based levels of several cytokines were established. Increased age and BMI, and to a lesser degree sex and smoking, significantly and differentially impact cytokine levels, while leisure-time physical activity has little effect.

Associations between alcohol consumption and selected cytokines in a Swiss population-based sample (CoLaus study)

To assess the associations between alcohol consumption and cytokine levels (interleukin-1beta - IL-1β; interleukin-6 - IL-6 and tumor necrosis factor-α - TNF-α) in a Caucasian population.

Association between circulating cytokine levels, diabetes and insulin resistance in a population-based sample (CoLaus study)

OBJECTIVE: The associations between inflammation, diabetes and insulin resistance remain controversial. Hence, we assessed the associations between diabetes, insulin resistance (using HOMA-IR) and metabolic syndrome with the inflammatory markers high sensitivity C-reactive protein (hs-CRP), interleukin-1beta (IL-1β), interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α). DESIGN: CROSS-SECTIONAL STUDY: PARTICIPANTS: 2884 MEN AND 3201 WOMEN AGED 35 TO 75: METHODS: CRP was assessed by immunoassay and cytokines by multiplexed flow cytometric assay. In a subgroup of 532 participants an oral glucose tolerance test was performed to screen for impaired glucose tolerance (IGT). RESULTS: IL-6, TNF-α and hs-CRP were significantly and positively correlated with fasting plasma glucose, insulin and HOMA-IR. Participants with diabetes had higher IL-6, TNF-α and hs-CRP levels than participants without diabetes; this difference persisted for hs-CRP after multivariate adjustment. Participants with metabolic syndrome had increased IL-6, TNF-α and hs-CRP levels; these differences persisted after multivariate adjustment. Participants in the highest quartile of HOMA-IR had increased IL-6, TNF-α and hs-CRP levels; these differences persisted for TNF-α and hs-CRP after multivariate adjustment. No association was found between IL-1β levels and all diabetes and insulin resistance markers studied. Finally, participants with IGT had higher hs-CRP levels than participants with a normal OGTT, but this difference disappeared after controlling for body mass index (BMI). CONCLUSION: subjects with diabetes, metabolic syndrome and increased insulin resistance present with increased levels of IL6, TNF-α and hs-CRP, while no association was found with IL-1β. The increased inflammatory state of subjects with IGT is partially explained by increased BMI. © 2012 Blackwell Publishing Ltd.