Implementing total quality management through total systems intervention: A creative approach to problem solving in diagnostic biotechnology (Pte) Ltd.

This paper documents the implementation of Total Quality Management employing a creative approach to problem solving called Total Systems Intervention.     

UDP-glucose ceramide glucosyltransferase activates AKT,promoted proliferation,and doxorubicin resistance in breast cancer cells

The UDP-glucose ceramide glucosyltransferase (UGCG) is a key enzyme in the synthesis of glycosylated sphingolipids, since this enzyme generates the precursor for all complex glycosphingolipids (GSL), the GlcCer. The UGCG has been associated with several cancer-related processes such as maintaining cancer stem cell properties or multidrug resistance induction. The precise mechanisms underlying these processes are unknown. Here, we investigated the molecular mechanisms occurring after UGCG overexpression in breast cancer cells. We observed alterations of several cellular properties such as morphological changes, which enhanced proliferation and doxorubicin resistance in UGCG overexpressing MCF-7 cells. These cellular effects seem to be mediated by an altered composition of glycosphingolipid-enriched microdomains (GEMs), especially an accumulation of globotriaosylceramide (Gb3) and glucosylceramide (GlcCer), which leads to an activation of Akt and ERK1/2. The induction of the Akt and ERK1/2 signaling pathway results in an increased gene expression of multidrug resistance protein 1 (MDR1) and anti-apoptotic genes and a decrease of pro-apoptotic gene expression. Inhibition of the protein kinase C (PKC) and phosphoinositide 3 kinase (PI3K) reduced MDR1 gene expression. This study discloses how changes in UGCG expression impact several cellular signaling pathways in breast cancer cells resulting in enhanced proliferation and multidrug resistance.     

Experimental design and reporting standards for metabolomics studies of mammalian cell lines

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.     

Forecast Combinations in a DSGE‐VAR Lab

We explore the benefits of forecast combinations based on forecast‐encompassing tests compared to simple averages and to Bates–Granger combinations. We also consider a new combination algorithm that fuses test‐based and Bates–Granger weighting. For a realistic simulation design, we generate multivariate time series samples from a macroeconomic DSGE‐VAR (dynamic stochastic general equilibrium–vector autoregressive) model. Results generally support Bates–Granger over uniform weighting, whereas benefits of test‐based weights depend on the sample size and on the prediction horizon. In a corresponding application to real‐world data, simple averaging performs best. Uniform averages may be the weighting scheme that is most robust to empirically observed irregularities. Copyright © 2016 John Wiley & Sons, Ltd.     

绵羊的故事

1999年,我们将庆祝应用科学中伟大的维多利亚时代的赞歌之一、由JamesCaird撰写的书籍──《自由盟为下的高农场：保护最好的代用品》出版150周年。当英国人首次进行自由贸易试验时,这场论战从19世纪中叶就开始了,人们并不鼓励农民依靠进口税收,而是鼓励农民转向科学以增强生产效率和利润,开创新技术的农业则被称为“高农场”。1997年,这一年的科学成就──多利,在苏格兰罗斯林研究所诞生了,那里是Caird的家乡,他是与高地和农业社会相关的农业改革的开拓者。在18和19世纪,这个在地貌上起伏不平的国家成了科学、技术和人类之间的…     

What causes mitochondrial DNA deletions in human cells?

Mitochondrial DNA (mtDNA) deletions are a primary cause of mitochondrial disease and are likely to have a central role in the aging of postmitotic tissues. Understanding the mechanism of the formation and subsequent clonal expansion of these mtDNA deletions is an essential first step in trying to prevent their occurrence. We review the previous literature and recent results from our own laboratories, and conclude that mtDNA deletions are most likely to occur during repair of damaged mtDNA rather than during replication. This conclusion has important implications for prevention of mtDNA disease and, potentially, for our understanding of the aging process.     

Highly effective SNP-based association mapping and management of recessive defects in livestock

The widespread use of elite sires by means of artificial insemination in livestock breeding leads to the frequent emergence of recessive genetic defects, which cause significant economic and animal welfare concerns. Here we show that the availability of genome-wide, high-density SNP panels, combined with the typical structure of livestock populations, markedly accelerates the positional identification of genes and mutations that cause inherited defects. We report the fine-scale mapping of five recessive disorders in cattle and the molecular basis for three of these: congenital muscular dystony (CMD) types 1 and 2 in Belgian Blue cattle and ichthyosis fetalis in Italian Chianina cattle. Identification of these causative mutations has an immediate translation into breeding practice, allowing marker assisted selection against the defects through avoidance of at-risk matings.     

Newly identified loci that influence lipid concentrations and risk of coronary artery disease

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.     

Loci on 20q13 and 21q22 are associated with pediatric-onset inflammatory bowel disease

Inflammatory bowel disease (IBD) is a common inflammatory disorder with complex etiology that involves both genetic and environmental triggers, including but not limited to defects in bacterial clearance, defective mucosal barrier and persistent dysregulation of the immune response to commensal intestinal bacteria. IBD is characterized by two distinct phenotypes: Crohn's disease (CD) and ulcerative colitis (UC). Previously reported GWA studies have identified genetic variation accounting for a small portion of the overall genetic susceptibility to CD and an even smaller contribution to UC pathogenesis. We hypothesized that stratification of IBD by age of onset might identify additional genes associated with IBD. To that end, we carried out a GWA analysis in a cohort of 1,011 individuals with pediatric-onset IBD and 4,250 matched controls. We identified and replicated significantly associated, previously unreported loci on chromosomes 20q13 (rs2315008[T] and rs4809330[A]; P = 6.30 x 10(-8) and 6.95 x 10(-8), respectively; odds ratio (OR) = 0.74 for both) and 21q22 (rs2836878[A]; P = 6.01 x 10(-8); OR = 0.73), located close to the TNFRSF6B and PSMG1 genes, respectively.     

Integrated detection and population-genetic analysis of SNPs and copy number variation

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.