A one-dimensional numerical model for the momentum exchange in regenerative pumps

The regenerative pump is a rotor-dynamic turbomachine capable of developing high heads at low flow rates and low specific speeds. In spite of their low efficiency, usually less than 50 %, they have found a wide range of applications as compact single-stage pumps with other beneficial features. The potential of a modified regenerative pump design is presented for consideration of the performance improvements. In this paper the fluid dynamic behaviour of the novel design was predicted using a one-dimensional model developed by the authors. Unlike most one-dimensional models previously published for regenerative pumps, the momentum exchange is computed numerically. Previous one-dimensional models relied on experimental data and correction factors; the model presented in this paper demonstrates accurate prediction of the pump performance characteristics without the need for correction with experimental data. The validity of this approach is highlighted by the comparison of computed and measured results for two different regenerative pump standards. The pump performance is assessed numerically without the need of correction factors or other experimental data. This paper presents an approach for regenerative pumps using a physically valid geometry model and by resolving the circulatory velocity in peripheral direction

Cyclo­linopeptide A methanol solvate

Crystals of the title compound, C57H85N9O9·CH4O, the methanol solvate of a nine peptide polypeptide, cyclo-(Pro-Pro-Phe-Phe-Leu-Ile-Ile-Leu-Val), were obtained after separation of the cyclic peptide from flax oil. The cyclo­linopeptide A (CLP-A) mol­ecules are linked in chains along the a axis by N—H⋯O hydrogen bonds. Each methanol O atom is hydrogen bonded to one O atom and two N—H groups in the same CLP-A mol­ecule. There are a total of eight hydrogen bonds in each CLP-A–MeOH unit

Bis[2-phenyl-1-(phenyl­iminio)isoindo­line] di-μ-chlorido-bis­[dichloridopalladate(II)] benzene disolvate

In the title compound, (C20H17N2)2[Pd2Cl6]·2C6H6, the dichloride-bridged [Pd2Cl6]2− anion lies across an inversion center with each PdII ion in a slightly distorted square-planar environment. In the crystal structure, two cations and an anion are connected via N—H⋯Cl hydrogen bonds between the NH groups of the iminioisoindoline cations and terminal Cl atoms of a hexa­chloridodipalladate(II) anion. The Pd—Cl distance of the terminal chloride engaged in hydrogen bonding is slightly longer than the Pd—Cl distance of the adjacent terminal chloride which is not involved in hydrogen bonding

The galla[1]ferrocenophane {[dimeth­yl(2-pyrid­yl)sil­yl]bis­(trimethyl­silyl)methyl-κ2 C,N}(ferrocene-1,1′-di­yl)gallium(III)

The title compound, [GaFe(C5H4)2(C14H28NSi3)] or [{(2-H4C5N)Me2Si}(Me3Si)2C]Ga(C5H4)2Fe, a galla[1]ferrocenophane, crystallizes with two independent mol­ecules in the asymmetric unit. In these strained sandwich compounds, the angles between the planes of the two π-ligands are 15.4 (2) and 16.4 (2)°, with gallium in a distorted tetrahedral coordination environment

Both mitochondrial DNA and mitonuclear gene mutations cause hearing loss through cochlear dysfunction.

PFC is a Wellcome Trust Senior Fellow in Clinical Science (101876/Z/13/Z), and a UK NIHR Senior Investigator, who receives support from the Medical Research Council Mitochondrial Biology Unit (MC_UP_1501/2), the Wellcome Trust Centre for Mitochondrial Research (096919Z/11/Z), the Medical Research Council (UK) Centre for Translational Muscle Disease research (G0601943), EU FP7 TIRCON, and the National Institute for Health Research (NIHR) Biomedical Research Centre based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. PJK is a Wellcome Trust Clinical research fellow (101700/Z/13/Z). PYWM is supported by a Clinician Scientist Fellowship Award (G1002570) from the Medical Research Council (UK), and also receives funding from Fight for Sight (UK) and the UK National Institute of Health Research (NIHR) as part of the Rare Diseases Translational Research Collaboration. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. This study received support from the MRC Mitochondrial Disease Patient Cohort (http://mitocohort.ncl.ac.uk/).This is the final version of the article. It first appeared from Oxford University Press via https://doi.org/10.1093/brain/aww05

A Systematically Improved High Quality Genome and Transcriptome of the Human Blood Fluke Schistosoma mansoni

Schistosomiasis is one of the most prevalent parasitic diseases, affecting millions of people in developing countries. Amongst the human-infective species, Schistosoma mansoni is also the most commonly used in the laboratory and here we present the systematic improvement of its draft genome. We used Sanger capillary and deep-coverage Illumina sequencing from clonal worms to upgrade the highly fragmented draft 380 Mb genome to one with only 885 scaffolds and more than 81% of the bases organised into chromosomes. We have also used transcriptome sequencing (RNA-seq) from four time points in the parasite's life cycle to refine gene predictions and profile their expression. More than 45% of predicted genes have been extensively modified and the total number has been reduced from 11,807 to 10,852. Using the new version of the genome, we identified trans-splicing events occurring in at least 11% of genes and identified clear cases where it is used to resolve polycistronic transcripts. We have produced a high-resolution map of temporal changes in expression for 9,535 genes, covering an unprecedented dynamic range for this organism. All of these data have been consolidated into a searchable format within the GeneDB (www.genedb.org) and SchistoDB (www.schistodb.net) databases. With further transcriptional profiling and genome sequencing increasingly accessible, the upgraded genome will form a fundamental dataset to underpin further advances in schistosome research

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Steroid receptor coactivator-1 modulates the function of Pomc neurons and energy homeostasis

Hypothalamic neurons expressing the anorectic peptide Pro-opiomelanocortin (Pomc) regulate food intake and body weight. Here, we show that Steroid Receptor Coactivator-1 (SRC-1) interacts with a target of leptin receptor activation, phosphorylated STAT3, to potentiate Pomc transcription. Deletion of SRC-1 in Pomc neurons in mice attenuates their depolarization by leptin, decreases Pomc expression and increases food intake leading to high-fat diet-induced obesity. In humans, fifteen rare heterozygous variants in SRC-1 found in severely obese individuals impair leptin-mediated Pomc reporter activity in cells, whilst four variants found in non-obese controls do not. In a knock-in mouse model of a loss of function human variant (SRC-1L1376P), leptin-induced depolarization of Pomc neurons and Pomc expression are significantly reduced, and food intake and body weight are increased. In summary, we demonstrate that SRC-1 modulates the function of hypothalamic Pomc neurons, and suggest that targeting SRC-1 may represent a useful therapeutic strategy for weight loss.Peer reviewe