Analysis of the complement and molecular evolution of tRNA genes in cow

<p>Abstract</p> <p>Background</p> <p>Detailed information regarding the number and organization of transfer RNA (tRNA) genes at the genome level is becoming readily available with the increase of DNA sequencing of whole genomes. However the identification of functional tRNA genes is challenging for species that have large numbers of repetitive elements containing tRNA derived sequences, such as <it>Bos taurus</it>. Reliable identification and annotation of entire sets of tRNA genes allows the evolution of tRNA genes to be understood on a genomic scale.</p> <p>Results</p> <p>In this study, we explored the <it>B. taurus </it>genome using bioinformatics and comparative genomics approaches to catalogue and analyze cow tRNA genes. The initial analysis of the cow genome using tRNAscan-SE identified 31,868 putative tRNA genes and 189,183 pseudogenes, where 28,830 of the 31,868 predicted tRNA genes were classified as repetitive elements by the RepeatMasker program. We then used comparative genomics to further discriminate between functional tRNA genes and tRNA-derived sequences for the remaining set of 3,038 putative tRNA genes. For our analysis, we used the human, chimpanzee, mouse, rat, horse, dog, chicken and fugu genomes to predict that the number of active tRNA genes in cow lies in the vicinity of 439. Of this set, 150 tRNA genes were 100% identical in their sequences across all nine vertebrate genomes studied. Using clustering analyses, we identified a new tRNA-Gly^CCCsubfamily present in all analyzed mammalian genomes. We suggest that this subfamily originated from an ancestral tRNA-Gly^GCCgene via a point mutation prior to the radiation of the mammalian lineages. Lastly, in a separate analysis we created phylogenetic profiles for each putative cow tRNA gene using a representative set of genomes to gain an overview of common evolutionary histories of tRNA genes.</p> <p>Conclusion</p> <p>The use of a combination of bioinformatics and comparative genomics approaches has allowed the confident identification of a set of cow tRNA genes that will facilitate further studies in understanding the molecular evolution of cow tRNA genes.</p

Human Computation and Convergence

Humans are the most effective integrators and producers of information, directly and through the use of information-processing inventions. As these inventions become increasingly sophisticated, the substantive role of humans in processing information will tend toward capabilities that derive from our most complex cognitive processes, e.g., abstraction, creativity, and applied world knowledge. Through the advancement of human computation - methods that leverage the respective strengths of humans and machines in distributed information-processing systems - formerly discrete processes will combine synergistically into increasingly integrated and complex information processing systems. These new, collective systems will exhibit an unprecedented degree of predictive accuracy in modeling physical and techno-social processes, and may ultimately coalesce into a single unified predictive organism, with the capacity to address societies most wicked problems and achieve planetary homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added references to page 1 and 3, and corrected typ

Advances in Glucocorticoid-Induced Osteoporosis

Glucocorticoid-induced osteoporosis (GIOP) is one of the most important side effects of glucocorticoid use, as it leads to an increased risk of fractures. Recently, many published studies have focused on the cellular and molecular mechanisms of bone metabolism, the pathophysiology of GIOP, and the intervention options to prevent GIOP. In this review, recent advances in GIOP are summarized, particularly recent progress in our understanding of the mechanisms of GIOP resulting in improved insight that might result in the development of new treatment options in the near future

Non-standard interactions versus non-unitary lepton flavor mixing at a neutrino factory

The impact of heavy mediators on neutrino oscillations is typically described by non-standard four-fermion interactions (NSIs) or non-unitarity (NU). We focus on leptonic dimension-six effective operators which do not produce charged lepton flavor violation. These operators lead to particular correlations among neutrino production, propagation, and detection non-standard effects. We point out that these NSIs and NU phenomenologically lead, in fact, to very similar effects for a neutrino factory, for completely different fundamental reasons. We discuss how the parameters and probabilities are related in this case, and compare the sensitivities. We demonstrate that the NSIs and NU can, in principle, be distinguished for large enough effects at the example of non-standard effects in the $\mu$-$\tau$-sector, which basically corresponds to differentiating between scalars and fermions as heavy mediators as leading order effect. However, we find that a near detector at superbeams could provide very synergistic information, since the correlation between source and matter NSIs is broken for hadronic neutrino production, while NU is a fundamental effect present at any experiment.Comment: 32 pages, 5 figures. Final version published in JHEP. v3: Typo in Eq. (27) correcte

External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol.

Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management. Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests. Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia. Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349

The yeast P5 type ATPase, Spf1, regulates manganese transport into the endoplasmic reticulum

The endoplasmic reticulum (ER) is a large, multifunctional and essential organelle. Despite intense research, the function of more than a third of ER proteins remains unknown even in the well-studied model organism Saccharomyces cerevisiae. One such protein is Spf1, which is a highly conserved, ER localized, putative P-type ATPase. Deletion of SPF1 causes a wide variety of phenotypes including severe ER stress suggesting that this protein is essential for the normal function of the ER. The closest homologue of Spf1 is the vacuolar P-type ATPase Ypk9 that influences Mn2+ homeostasis. However in vitro reconstitution assays with Spf1 have not yielded insight into its transport specificity. Here we took an in vivo approach to detect the direct and indirect effects of deleting SPF1. We found a specific reduction in the luminal concentration of Mn2+ in ∆spf1 cells and an increase following it’s overexpression. In agreement with the observed loss of luminal Mn2+ we could observe concurrent reduction in many Mn2+-related process in the ER lumen. Conversely, cytosolic Mn2+-dependent processes were increased. Together, these data support a role for Spf1p in Mn2+ transport in the cell. We also demonstrate that the human sequence homologue, ATP13A1, is a functionally conserved orthologue. Since ATP13A1 is highly expressed in developing neuronal tissues and in the brain, this should help in the study of Mn2+-dependent neurological disorders

Optimisation of the RT-PCR detection of immunomagnetically enriched carcinoma cells

BACKGROUND: Immunomagnetic enrichment followed by RT-PCR (immunobead RT-PCR) is an efficient methodology to identify disseminated carcinoma cells in the blood and bone marrow. The RT-PCR assays must be both specific for the tumor cells and sufficiently sensitive to enable detection of single tumor cells. We have developed a method to test RT-PCR assays for any cancer. This has been investigated using a panel of RT-PCR markers suitable for the detection of breast cancer cells. METHODS: In the assay, a single cell line-derived tumor cell is added to 100 peripheral blood mononuclear cells (PBMNCs) after which mRNA is isolated and reverse transcribed for RT-PCR analysis. PBMNCs without added tumor cells are used as specificity controls. The previously studied markers epidermal growth factor receptor (EGFR), mammaglobin 1 (MGB1), epithelial cell adhesion molecule (EpCAM/TACSTD1), mucin 1 (MUC1), carcinoembryonic antigen (CEA) were tested. Two new epithelial-specific markers ELF3 and EphB4 were also tested. RESULTS: MUC1 was unsuitable as strong amplification was detected in 100 cell PBMNC controls. Expression of ELF3, EphB4, EpCAM, EGFR, CEA and MGB1 was found to be both specific for the tumor cell, as demonstrated by the absence of a signal in most 100 cell PBMNC controls, and sensitive enough to detect a single tumor cell in 100 PBMNCs using a single round of RT-PCR. CONCLUSIONS: ELF3, EphB4, EpCAM, EGFR, CEA and MGB1 are appropriate RT-PCR markers for use in a marker panel to detect disseminated breast cancer cells after immunomagnetic enrichment

Simultaneous Quantitation of Amino Acid Mixtures using Clustering Agents

A method that uses the abundances of large clusters formed in electrospray ionization to determine the solution-phase molar fractions of amino acids in multi-component mixtures is demonstrated. For solutions containing either four or 10 amino acids, the relative abundances of protonated molecules differed from their solution-phase molar fractions by up to 30-fold and 100-fold, respectively. For the four-component mixtures, the molar fractions determined from the abundances of larger clusters consisting of 19 or more molecules were within 25% of the solution-phase molar fractions, indicating that the abundances and compositions of these clusters reflect the relative concentrations of these amino acids in solution, and that ionization and detection biases are significantly reduced. Lower accuracy was obtained for the 10-component mixtures where values determined from the cluster abundances were typically within a factor of three of their solution molar fractions. The lower accuracy of this method with the more complex mixtures may be due to specific clustering effects owing to the heterogeneity as a result of significantly different physical properties of the components, or it may be the result of lower S/N for the more heterogeneous clusters and not including the low-abundance more highly heterogeneous clusters in this analysis. Although not as accurate as using traditional standards, this clustering method may find applications when suitable standards are not readily available

The APEX Quantitative Proteomics Tool: Generating protein quantitation estimates from LC-MS/MS proteomics results

Mass spectrometry (MS) based label-free protein quantitation has mainly focused on analysis of ion peak heights and peptide spectral counts. Most analyses of tandem mass spectrometry (MS/MS) data begin with an enzymatic digestion of a complex protein mixture to generate smaller peptides that can be separated and identified by an MS/MS instrument. Peptide spectral counting techniques attempt to quantify protein abundance by counting the number of detected tryptic peptides and their corresponding MS spectra. However, spectral counting is confounded by the fact that peptide physicochemical properties severely affect MS detection resulting in each peptide having a different detection probability. Lu et al. (2007) described a modified spectral counting technique, Absolute Protein Expression (APEX), which improves on basic spectral counting methods by including a correction factor for each protein (called O(i) value) that accounts for variable peptide detection by MS techniques. The technique uses machine learning classification to derive peptide detection probabilities that are used to predict the number of tryptic peptides expected to be detected for one molecule of a particular protein (O(i)). This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances. Results: The APEX Quantitative Proteomics Tool, introduced here, is a free open source Java application that supports the APEX protein quantitation technique. The APEX tool uses data from standard tandem mass spectrometry proteomics experiments and provides computational support for APEX protein abundance quantitation through a set of graphical user interfaces that partition thparameter controls for the various processing tasks. The tool also provides a Z-score analysis for identification of significant differential protein expression, a utility to assess APEX classifier performance via cross validation, and a utility to merge multiple APEX results into a standardized format in preparation for further statistical analysis. Conclusion: The APEX Quantitative Proteomics Tool provides a simple means to quickly derive hundreds to thousands of protein abundance values from standard liquid chromatography-tandem mass spectrometry proteomics datasets. The APEX tool provides a straightforward intuitive interface design overlaying a highly customizable computational workflow to produce protein abundance values from LC-MS/MS datasets.National Institute of Allergy and Infectious Diseases (NIAID) N01-AI15447National Institutes of HealthNational Science Foundation, the Welsh and Packard FoundationsInternational Human Frontier Science ProgramCenter for Systems and Synthetic Biolog

Chinese beliefs in luck are linked to gambling problems via strengthened cognitive biases:A mediation test

10.1007/s10899-017-9690-6Journal of gambling studies3341325-133