Stability constants for some divalent metal ion/crown ether complexes in methanol determined by polarography and conductometry

Stability constants in methanol at 25.0°C were evaluated for the complexes of the divalent cations Ca2+, Ni2+, Zn2+, Pb2+, Mg2+, Co2+ and Cu2+ with the macrocyclic polyethers 15-crown-5 (15C5), 18-crown-6 (18C6), dicyclohexyl-18-crown-6 (DC18C6) and dibenzo-24-crown-8 (DB24C8). The log K values of the 1:1 complexes were generally in the range 2.1–4.2, which is low in comparison to the values of the corresponding crown ether/alkali metal ion complexes. M2L complexes were observed for the systems Pb2+/18C6, Pb2+/DC18C6, Ca2+/DC18C6 and Cu2+/D18C6, whereas ML2 complexes were found for Ca2+/18C6 and Cu2+/18C6. Within the series of complexes studied, there was no clear relationship between cation diameter and hole size

Computerized conductometric determination of stability constants of complexes of crown ethers with alkali metal salts and with neutral molecules in polar solvents

A computerized conductometric procedure for the determination of stability constants of the complexes of crown ethers (15-crown-5, benzo-15-crown-5 and 12-crown-4) with alkali metal salts in polar solvents is described, based on a microcomputer-controlled titration system. For the control of the experiments from software, a modular computer program was written in FORTH computer language. The procedure is especially suitable for the study of 1:2 metal ion/ligand complexes, which occur frequently with the compounds used. For the study of the interaction between crown ethers and neutral molecules, an indirect procedure is outlined

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European Red List of Lycopods and Ferns

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Potential of herbariomics for studying repetitive DNA in angiosperms

Repetitive DNA has an important role in angiosperm genomes and is relevant to our understanding of genome size variation, polyploidisation and genome dynamics more broadly. Much recent work has harnessed the power of high-throughput sequencing (HTS) technologies to advance the study of repetitive DNA in flowering plants. Herbarium collections provide a useful historical perspective on genome diversity through time, but their value for the study of repetitive DNA has not yet been explored. We propose that herbarium DNA may prove as useful for studies of repetitive DNA content as it has for reconstructed organellar genomes and low-copy nuclear sequence data. Here we present a case study in the tobacco genus (Nicotiana; Solanaceae), showing that herbarium specimens can provide accurate estimates of the repetitive content of angiosperm genomes by direct comparison with recently-collected material. We show a strong correlation between the abundance of repeat clusters, e.g., different types of transposable elements and satellite DNA, in herbarium collections versus recent material for four sets of Nicotiana taxa. These results suggest that herbarium specimen genome sequencing (herbariomics) holds promise for both repeat discovery and analyses that aim to investigate the role of repetitive DNAs in genomic evolution, particularly genome size evolution and/or contributions of repeats to the regulation of gene space

Returning genome sequences to research participants:Policy and practice

Despite advances in genomic science stimulating an explosion of literature around returning health-related findings, the possibility of returning entire genome sequences to individual research participants has not been widely considered. Through direct involvement in large-scale translational genomics studies, we have identified a number of logistical challenges that would need to be overcome prior to returning individual genome sequence data, including verifying that the data belong to the requestor and providing appropriate informatics support. In addition, we identify a number of ethico-legal issues that require careful consideration, including returning data to family members, mitigating against unintended consequences, and ensuring appropriate governance. Finally, recognising that there is an opportunity cost to addressing these issues, we make some specific pragmatic suggestions for studies that are considering whether to share individual genomic datasets with individual study participants. If data are shared, research should be undertaken into the personal, familial and societal impact of receiving individual genome sequence data

Assessing Recent Smoking Status by Measuring Exhaled Carbon Monoxide Levels

The main expectations of applying proteomics technologies to clinical questions are the discovery of disease related biomarkers. Despite technological advancement to increase proteome coverage and depth to meet these expectations the number of generated biomarkers for clinical use is small. One of the reasons is that found potential biomarkers often are false discoveries. Small sample sizes, in combination with patient sample heterogeneity increase the risk of false discoveries. To be able to extract relevant biological information from such data, high demands are put on the experimental design and the use of sensitive and quantitatively accurate technologies. The overall aim of this thesis was to apply quantitative proteomics methods for biomarker discovery in clinical samples. A method for reducing bias by controlling for individual variation in smoking habits is described in paper I. The aim of the method was objective assessment of recent smoking in clinical studies on inflammatory responses. In paper II, the proteome of alveolar macrophages obtained from smoking subjects with and without the inflammatory lung disease chronic obstructive pulmonary disease (COPD) were quantified by two-dimensional gel-electrophoresis (2-DE). A gender focused analysis showed protein level differences within the female group, with down-regulation of lysosomal pathway and up-regulation of oxidative pathway in COPD patients. Paper III, a mass spectrometry based proteomics analysis of tumour samples, contributes to the molecular understanding of vulvar squamous cell carcinoma (VSCC) and we identified a high risk patient subgroup of HPV-negative tumours based on the expression of four proteins, further suggesting that this subgroup is characterized by an altered ubiquitin-proteasome signalling pathway. Paper III describes a data analysis workflow for the extraction of biological information from quantitative mass spectrometry based proteomics data. High patient-to-patient tumour proteome variability was addressed by using pathway profiling on individual tumour data, followed by comparison of pathway association ranks in a multivariate analysis. We show that pathway data on individual tumour level can detect subpopulations of patients and identify pathways of specific importance in pre-defined clinical groups by the use of multivariate statistics. In paper IV, the potentials and limits of quantitative mass spectrometry on clinical samples was evaluated by defining the quantitative accuracy of isobaric labels and label-free quantification. Quantification by isobaric labels in combination with pI pre-fractionation showed a lower limit of quantification (LOQ) than a label-free analysis without pI pre-fractionation, and 6-plex TMT were more sensitive than 8-plex iTRAQ. Precursor mixing measured by isolation interference (MS1 interference) is more linked to the quantitative accuracy of isobaric labels than reporter ion interference (MS2 interference). Based on that we could define recommendations for how much isolation interference that can be accepted; in our data <30% isolation interference had little effect the quantitative accuracy. In conclusion, getting biological knowledge from proteomics studies requires a careful study design, control of possible confounding factors and the use of clinical data to identify disease subtypes. Further, to be able to draw conclusions from the data, the analysis requires accurate quantitative data and robust statistical tools to detect significant protein alterations. Methods around these issues are developed and discussed in this thesis