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Fetal supply with long-chain PUFA (LC-PUFA) during pregnancy is important for brain growth and visual and cognitive development and is provided by materno–fetal placental transfer. We recently showed that maternal fatty acid desaturase (FADS) genotypes modulate the amounts of LC-PUFA in maternal blood. Whether FADS genotypes influence the amounts of umbilical cord fatty acids has not been investigated until now. The aim of the present study was to investigate the influence of maternal and child FADS genotypes on the amounts of LC-PUFA in umbilical cord venous plasma as an indicator of fetal fatty acid supply during pregnancy. A total of eleven cord plasma n-6 and n-3 fatty acids were analysed for association with seventeen FADS gene cluster SNP in over 2000 mothers and children from the Avon Longitudinal Study of Parents and Children. In a multivariable analysis, the maternal genotype effect was adjusted for the child genotype and vice versa to estimate which of the two has the stronger influence on cord plasma fatty acids. Both maternal and child FADS genotypes and haplotypes influenced amounts of cord plasma LC-PUFA and fatty acid ratios. Specifically, most analysed maternal SNP were associated with cord plasma levels of the precursor n-6 PUFA, whereas the child genotypes were mainly associated with more highly desaturated n-6 LC-PUFA. This first study on FADS genotypes and cord fatty acids suggests that fetal LC-PUFA status is determined to some extent by fetal fatty acid conversion. Associations of particular haplotypes suggest specific effects of SNP rs498793 and rs968567 on fatty acid metabolism.
MicroRNAs (miRNAs) are small endogenous molecules that are involved in a diverse of cellular process. However, little is known about their abundance in bovine oocytes and their surrounding cumulus cells during oocyte development. To elucidate this situation, we investigated the relative expression pattern of sets of miRNAs between bovine oocyte and the surrounding cumulus cells during in vitro maturation using miRNA polymerase chain reaction (PCR) array. Results revealed that a total of 47 and 51 miRNAs were highly abundant in immature and matured oocytes, respectively, compared with their surrounding cumulus cells. Furthermore, expression analysis of six miRNAs enriched in oocyte miR-205, miR-150, miR-122, miR-96, miR-146a and miR-146b-5p at different maturation times showed a dramatic decrease in abundance from 0 h to 22 h of maturation. The expression of the same miRNAs in preimplantation stage embryos was found to be highly abundant in early stages of embryo development and decreased after the 8-cell stage to the blastocyst stage following a typical maternal transcript profile. Similar results were obtained by localization of miR-205 in preimplantation stage embryos, in which signals were higher up to the 4-cell stage and reduced thereafter. miR-205 and miR-210 were localized in situ in ovarian follicles and revealed a spatio-temporal expression during follicular development. Interestingly, the presence or absence of oocytes or cumulus cells during maturation was found to affect the expression of miRNAs in each of the two cell types. Hence, our results showed the presence of distinct sets of miRNAs in oocytes or cumulus cells and the presence of their dynamic degradation during bovine oocyte maturation.
Solid materials in subambient gaseous environments have been imaged using in situ transmission electron microscopy (TEM), for example to study dynamic effects: carbon nanotube growth, nanoparticle changes during redox reactions, and phase transitions in nanoscale systems. In these studies the vacuum level in the specimen region of the electron microscope was increased to pressures of up to 10 mbar using pump-limiting apertures that separated the specimen region from the rest of the high-vacuum electron column, but it has not been possible to achieve the higher pressures that are desirable for catalysis research. TEM imaging at atmospheric pressure and at elevated temperature was achieved with 0.2-nm resolution by enclosing a gaseous environment several micrometers thick between ultra-thin, electron transparent silicon nitride windows. Although Ångström-level resolution in situ TEM has been demonstrated with aberration-corrected systems, the key difficulty with TEM imaging is its dependence on phase contrast, which requires ultra-thin specimens, limiting the choice of experiments.
Our goal in producing this book is to provide a broad overview of the most important approaches used in protein- and ligand-structure-based drug design. Beyond this we aim to illustrate how these approaches are currently being applied in drug discovery efforts. We hope this book will be a useful resource to practitioners in the field, as well as a good introduction for researchers or students who are new to the field. We believe it provides a snapshot of the most important trends and capabilities in the application of modeling and structural data in drug discovery.
Since the 1990s the role of structure and modeling in drug discovery has grown enormously. There have been remarkable scientific advances in both the experimental and computational fields that are the underpinnings of modern drug design. For example, x-ray capabilities have improved to the point that protein structures are now routinely available for a wide range of protein targets. One only need look at the exponential growth of the Protein Databank (RCSB) for evidence. Tremendous strides have been made in all aspects of protein structure determination, including crystallization, data acquisition, and structure refinement. Modeling has made similar gains. Recent years have brought more realistic force fields, new and more robust free-energy methods, computational models for absorption/distribution/metabolism/excretion (ADME)-toxicity, faster and better docking algorithms, automated 3D pharmacophore detection and searching, and very-large-scale quantum calculations.
Structure-based (SBDD) and ligand-based (LBDD) drug design are extremely important and active areas of research in both the academic and commercial realms. This book provides a complete snapshot of the field of computer-aided drug design and associated experimental approaches. Topics covered include X-ray crystallography, NMR, fragment-based drug design, free energy methods, docking and scoring, linear-scaling quantum calculations, QSAR, pharmacophore methods, computational ADME-Tox, and drug discovery case studies. A variety of authors from academic and commercial institutions all over the world have contributed to this book, which is illustrated with more than 200 images. This is the only book to cover the subject of structure and ligand-based drug design, and it provides the most up-to-date information on a wide range of topics for the practising computational chemist, medicinal chemist, or structural biologist. Professor Kenneth Merz has been selected as the recipient of the 2010 ACS Award for Computers in Chemical & Pharmaceutical Research that recognizes the advances he has made in the use of quantum mechanics to solve biological and drug discovery problems.
To examine the effect of time on suicide after bereavement among widowed persons.
The data were extracted from Swiss mortality statistics for the period 1987–2005. The time between bereavement and subsequent death, specifically by suicide, was determined by linkage of individual records of married persons. The suicide rates and the standardized mortality ratios in the first week/month/year of widowhood were calculated based on person-year calculations.
The annualized suicide rates in widowed persons were highest in the first week after bereavement: 941 males and 207 females per 100 000. The corresponding standardized mortality ratios were approximately 34 and 19 respectively. In the first month(s) after bereavement, the rates and the ratios decreased, first rapidly, then gradually. Except in older widows, they did not reach the baseline levels during the first year after bereavement.
The suicide risk of widowed persons is increased in the days, weeks and months after bereavement. Widowed persons are a clear-cut risk group under the aegis of undertakers, priests and general practitioners.
The role of gene suppression technologies in pharmaceutical drug development
The completion of the human genome sequence (International Human Genome Sequencing Consortium, 2001; Venter et al., 2001) has ushered in a new era for the pharmaceutical industry. With access to a comprehensive list of candidate drug targets, together with a growing understanding of their association to signalling and metabolic pathways and human disease, there would seem to be endless opportunity for novel drug development. From a clinical perspective, this most basic of genetic insights should enhance the efficacy of existing drugs, while at the same time bring new drugs to market for many new therapeutic indications. From a corporate vantage, utilising the information embedded in the human genome for improved target validation should effectively reduce the attrition of candidate drug targets and therefore translate to a “competitive advantage.”
With thousands of candidate drug targets to select from, it is necessary to invest in strategic methods in order to navigate the complex maze of genetic information. Indeed, the identification and validation of targets that map to chemically tractable gene families (the ‘druggable’ genome, or ‘pharmome’) is now recognised as a fundamental challenge to the entire pharmaceutical industry (Figure 25.1). In an effort to achieve this goal, molecular technologies that suppress the expression of a candidate drug target (either in cis- or trans-) have become fixtures in most pharmaceutical R&D programmes, and there are many examples where this has been successful.
Studies in psychophysiology and behavioral medicine have uncovered
associations among psychological processes, behavior, and lung
function. However, methodological issues specific to the
measurement of mechanical lung function have rarely been discussed.
This report presents an overview of the physiology, techniques,
and experimental methods of mechanical lung function measurements
relevant to this research context. Techniques to measure lung
volumes, airflow, airway resistance, respiratory resistance,
and airflow perception are introduced and discussed. Confounding
factors such as ventilation, medication, environmental factors,
physical activity, and instructional and experimenter effects
are outlined, and issues specific to children and clinical groups
are discussed. Recommendations are presented to increase the
degree of standardization in the research application and
publication of mechanical lung function measurements in