Fertility, Living Arrangements, Care and Mobility

There are four main interconnecting themes around which the contributions in this book are based. This introductory chapter aims to establish the broad context for the chapters that follow by discussing each of the themes. It does so by setting these themes within the overarching demographic challenge of the twenty-first century – demographic ageing. Each chapter is introduced in the context of the specific theme to which it primarily relates and there is a summary of the data sets used by the contributors to illustrate the wide range of cross-sectional and longitudinal data analysed

Intratumoural and peripheral blood lymphocyte subsets in patients with metastatic renal cell carcinoma undergoing interleukin-2 based immunotherapy: association to objective response and survival

The aim of the present study was to analyse lymphocyte subsets in consecutive peripheral blood samples and consecutive tumour tissue core needle biopsies performed before and during interleukin-2 based immunotherapy, and to correlate the findings with objective response and survival. Twenty-six patients with metastatic renal cell carcinoma were treated with low dose s.c. interleukin-2, interferon-α and histamine. A total of 250 blood samples and 62 core needle biopsies from 23 and 19 of these patients, respectively, were analysed. After 2 weeks of treatment, a significant positive correlation between absolute number of peripheral blood lymphocytes (P=0.028), CD3 (P=0.017), CD57 (P=0.041) and objective response was demonstrated. There was no correlation between any peripheral blood leukocyte subsets and survival. Cytotoxicity of peripheral blood mononuclear cells was not correlated to objective response or survival. Within the tumour tissue at baseline, a significant positive correlation between CD4 (P=0.027), CD8 (P=0.028), CD57 (P=0.007) and objective response was demonstrated. After one month of immunotherapy, a significant positive correlation between intratumoral CD3 (P=0.026), CD8 (P=0.015), CD57 (P=0.009) and objective response was demonstrated. A significant positive correlation between intratumoral baseline CD4 (P=0.047), baseline CD57 (P=0.035), CD3 at one month (P=0.049) and survival was demonstrated. These data provide novel in vivo evidence of the possible contribution of lymphocyte subsets in the tumour reduction in responding patients during interleukin-2 based immunotherapy. Confirmation of the results requires further studies including a larger number of patients

Embracing heterogeneity: coalescing the Tree of Life and the future of phylogenomics

Building the Tree of Life (ToL) is a major challenge of modern biology, requiring advances in cyberinfrastructure, data collection, theory, and more. Here, we argue that phylogenomics stands to benefit by embracing the many heterogeneous genomic signals emerging from the first decade of large-scale phylogenetic analysis spawned by high-throughput sequencing (HTS). Such signals include those most commonly encountered in phylogenomic datasets, such as incomplete lineage sorting, but also those reticulate processes emerging with greater frequency, such as recombination and introgression. Here we focus specifically on how phylogenetic methods can accommodate the heterogeneity incurred by such population genetic processes; we do not discuss phylogenetic methods that ignore such processes, such as concatenation or supermatrix approaches or supertrees. We suggest that methods of data acquisition and the types of markers used in phylogenomics will remain restricted until a posteriori methods of marker choice are made possible with routine whole-genome sequencing of taxa of interest. We discuss limitations and potential extensions of a model supporting innovation in phylogenomics today, the multispecies coalescent model (MSC). Macroevolutionary models that use phylogenies, such as character mapping, often ignore the heterogeneity on which building phylogenies increasingly rely and suggest that assimilating such heterogeneity is an important goal moving forward. Finally, we argue that an integrative cyberinfrastructure linking all steps of the process of building the ToL, from specimen acquisition in the field to publication and tracking of phylogenomic data, as well as a culture that values contributors at each step, are essential for progress

Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains

BACKGROUND: Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria. A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type 1 diabetes, described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B10) that were made to develop proteinuria by BSA overload. METHODS: Proteinuria was induced by protein overload on NON and NOD.B10 mouse strains and histology and microarray technology were used to follow the kidney response. The effects of proteinuria were assessed and subsequently compared to changes that were observed in a prior study on NOD diabetic nephropathy. RESULTS: Overload treatment significantly modified the renal phenotype and out of 5760 clones screened, 21 and 7 kidney transcripts were respectively altered in the NON and NOD.B10. Upregulated transcripts encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney. Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2 alpha 1 as being more specifically induced by proteinuria. CONCLUSION: By simulating a component of diabetes, and looking at the global response on mice resistant to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease progression. This suggests the power of this approach in unraveling multifactorial disease processes

Ribosome-Dependent ATPase Interacts with Conserved Membrane Protein in Escherichia coli to Modulate Protein Synthesis and Oxidative Phosphorylation

Elongation factor RbbA is required for ATP-dependent deacyl-tRNA release presumably after each peptide bond formation; however, there is no information about the cellular role. Proteomic analysis in Escherichia coli revealed that RbbA reciprocally co-purified with a conserved inner membrane protein of unknown function, YhjD. Both proteins are also physically associated with the 30S ribosome and with members of the lipopolysaccharide transport machinery. Genome-wide genetic screens of rbbA and yhjD deletion mutants revealed aggravating genetic interactions with mutants deficient in the electron transport chain. Cells lacking both rbbA and yhjD exhibited reduced cell division, respiration and global protein synthesis as well as increased sensitivity to antibiotics targeting the ETC and the accuracy of protein synthesis. Our results suggest that RbbA appears to function together with YhjD as part of a regulatory network that impacts bacterial oxidative phosphorylation and translation efficiency

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about “who eats whom.” Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change

Mechanisms of progression of chronic kidney disease

Chronic kidney disease (CKD) occurs in all age groups, including children. Regardless of the underlying cause, CKD is characterized by progressive scarring that ultimately affects all structures of the kidney. The relentless progression of CKD is postulated to result from a self-perpetuating vicious cycle of fibrosis activated after initial injury. We will review possible mechanisms of progressive renal damage, including systemic and glomerular hypertension, various cytokines and growth factors, with special emphasis on the renin–angiotensin–aldosterone system (RAAS), podocyte loss, dyslipidemia and proteinuria. We will also discuss possible specific mechanisms of tubulointerstitial fibrosis that are not dependent on glomerulosclerosis, and possible underlying predispositions for CKD, such as genetic factors and low nephron number