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

Down, then up: non-parallel genome size changes and a descending chromosome series in a recent radiation of the Australian allotetraploid plant species, Nicotiana section Suaveolentes (Solanaceae)

Background and aims: The extent to which genome size and chromosome numbers evolve in concert is little understood, particularly after polyploidy (whole-genome duplication), when a genome returns to a diploid-like condition (diploidisation). We study this phenomenon in 46 species of allotetraploid Nicotiana section Suaveolentes (Solanaceae), which formed less than six million years ago and radiated in the arid centre of Australia.Methods: We analysed newly assessed genome sizes and chromosome numbers within the context of a restriction site-associated nuclear DNA (RADseq) phylogenetic framework.Key results: RADseq generated a well-supported phylogenetic tree, in which multiple accessions from each species formed unique genetic clusters. Chromosome numbers and genome sizes vary from n = 2x = 15-24 and 2.7-5.8 pg/1 C nucleus, respectively. Decreases in both genome size and chromosome number occur, although neither consistently nor in parallel. Species with the lowest chromosome numbers (n = 15-18) do not possess the smallest genome sizes, and although N. heterantha has retained the ancestral chromosome complement, n = 2x = 24, it nonetheless has the smallest genome size, even smaller than that of the modern representatives of ancestral diploids.Conclusions: The results indicate that decreases in genome size and chromosome number occur in parallel down to a chromosome number threshold, n = 20, below which genome size increases, a phenomenon potentially explained by decreasing rates of recombination over fewer chromosomes. We hypothesize that, more generally in plants, major decreases in genome size post-polyploidization take place while chromosome numbers are still high because in these stages elimination of retrotransposons and other repetitive elements is more efficient. Once such major genome size change has been accomplished, then dysploid chromosome reductions take place to reorganize these smaller genomes, producing species with small genomes and low chromosome numbers such as those observed in many annual angiosperms, including Arabidopsis. Mark W Chase, Rosabelle Samuel, Andrew R Leitch, Maïté S Guignard, John G Conran, Felipe Nollet, Paul Fletcher, Aljaž Jakob, Luiz A Cauz-Santos, Gabriel Vignolle, Steven Dodsworth, Maarten J M Christenhusz, Maria Teresa Buril, Ovidiu Pau

A taxonomic, genetic and ecological data resource for the vascular plants of Britain and Ireland

The vascular flora of Britain and Ireland is among the most extensively studied in the world, but the current knowledge base is fragmentary, with taxonomic, ecological and genetic information scattered across different resources. Here we present the first comprehensive data repository of native and alien species optimized for fast and easy online access for ecological, evolutionary and conservation analyses. The inventory is based on the most recent reference flora of Britain and Ireland, with taxon names linked to unique Kew taxon identifiers and DNA barcode data. Our data resource for 3,227 species and 26 traits includes existing and unpublished genome sizes, chromosome numbers and life strategy and life-form assessments, along with existing data on functional traits, species distribution metrics, hybrid propensity, associated biomes, realized niche description, native status and geographic origin of alien species. This resource will facilitate both fundamental and applied research and enhance our understanding of the flora’s composition and temporal changes to inform conservation efforts in the face of ongoing climate change and biodiversity loss

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

Stakeholder views on secondary findings in whole-genome and whole-exome sequencing:a systematic review of quantitative and qualitative studies

Purpose: As whole-exome and whole-genome sequencing (WES/WGS) move into routine clinical practice, it is timely to review data that might inform the debate around secondary findings (SF) and the development of policies that maximize participant benefit. Methods: We systematically searched for qualitative and quantitative studies that explored stakeholder views on SF in WES/WGS. Framework analysis was undertaken to identify major themes. Results: 44 articles reporting the views of 11,566 stakeholders were included. Stakeholders were broadly supportive of returning ‘actionable’ findings, but definitions of actionability varied. Stakeholder views on SF disclosure exist along a spectrum: potential WES/WGS recipients’ views were largely influenced by a sense of rights, while views of genomics professionals were informed by a sense of professional responsibility. Experience of genetic illness and testing resulted in greater caution about SF, suggesting that truly informed decisions require an understanding of the implications and limitations of WES/WGS and possible findings. Conclusion: This review suggests that bidirectional interaction during consent might best facilitate informed decision-making about SF, and that dynamic forms of consent, allowing for changing preferences, should be considered. Research exploring views from wider perspectives and from recipients who have received SF is critical if evidence-based policies are to be achieved.</p

Application of chemometric analysis to infrared spectroscopy for the identification of wood origin

Chemical characteristics of wood are used in this study for plant taxonomy classification based on the current Angiosperm Phylogeny Group classification (APG III System) for the division, class and subclass of woody plants. Infrared spectra contain information about the molecular structure and intermolecular interactions among the components in wood but the understanding of this information requires multivariate techniques for the analysis of highly dense datasets. This article is written with the purposes of specifying the chemical differences among taxonomic groups, and predicting the taxa of unknown samples with a mathematical model. Principal component analysis, t-test, stepwise discriminant analysis and linear discriminant analysis, were some of the chosen multivariate techniques. A procedure to determine the division, class, subclass and order of unknown samples was built with promising implications for future applications of Fourier Transform Infrared spectroscopy in wood taxonomy classification