147 research outputs found
Tumors and tumor-like lesions of the heart valves
Valvular tumors and tumor-like lesions may have similar morphological and clinical characteristics, and may place the patients at a high risk of stroke in different ways. From January 2004 to June 2008, 11 patients underwent surgery for a suspected valvular tumor. Valvular tumor and tumor-like lesions accounted for 0.32% of adult cardiac operations. Five (45.5%) valvular lesions were papillary fibroelastomas, one (9.1%) was myxoma, 2 (18.2%) were organized thrombi, and 3 (27.3%) were calcification lesions. There was a total of 5 (45.5%) atrioventricular valve lesions, 4 arising from the atrial side of the leaflets, and one from the ventricular side. All 5 (45.5%) semilunar valvular lesions were from the aortic valve. One (9.1%) lesion originated from the chorda tendinea of the mitral valve. All leaflet lesions were resected by a simple shave technique, and all the patients recovered favorably. Valvular tumor and tumor-like lesions are rare. Pre-operative differential diagnoses among these valvular lesions pose important clinical implications for appropriate treatment for the underlying diseases. Prompt therapeutic measures in view of the underlying diseases of the valvular lesions are essential to prevent potential embolic events
Accuracy of direct genomic values in Holstein bulls and cows using subsets of SNP markers
Background: At the current price, the use of high-density single nucleotide polymorphisms (SNP) genotyping assays in genomic selection of dairy cattle is limited to applications involving elite sires and dams. The objective of this study was to evaluate the use of low-density assays to predict direct genomic value (DGV) on five milk production traits, an overall conformation trait, a survival index, and two profit index traits (APR, ASI). Methods. Dense SNP genotypes were available for 42,576 SNP for 2,114 Holstein bulls and 510 cows. A subset of 1,847 bulls born between 1955 and 2004 was used as a training set to fit models with various sets of pre-selected SNP. A group of 297 bulls born between 2001 and 2004 and all cows born between 1992 and 2004 were used to evaluate the accuracy of DGV prediction. Ridge regression (RR) and partial least squares regression (PLSR) were used to derive prediction equations and to rank SNP based on the absolute value of the regression coefficients. Four alternative strategies were applied to select subset of SNP, namely: subsets of the highest ranked SNP for each individual trait, or a single subset of evenly spaced SNP, where SNP were selected based on their rank for ASI, APR or minor allele frequency within intervals of approximately equal length. Results: RR and PLSR performed very similarly to predict DGV, with PLSR performing better for low-density assays and RR for higher-density SNP sets. When using all SNP, DGV predictions for production traits, which have a higher heritability, were more accurate (0.52-0.64) than for survival (0.19-0.20), which has a low heritability. The gain in accuracy using subsets that included the highest ranked SNP for each trait was marginal (5-6%) over a common set of evenly spaced SNP when at least 3,000 SNP were used. Subsets containing 3,000 SNP provided more than 90% of the accuracy that could be achieved with a high-density assay for cows, and 80% of the high-density assay for young bulls. Conclusions: Accurate genomic evaluation of the broader bull and cow population can be achieved with a single genotyping assays containing ∼ 3,000 to 5,000 evenly spaced SNP
Comparative genomics of Escherichia coli isolated from patients with inflammatory bowel disease
<p>Abstract</p> <p>Background</p> <p>Inflammatory bowel disease (IBD) is used to describe a state of idiopathic, chronic inflammation of the gastrointestinal tract. The two main phenotypes of IBD are Crohn's disease (CD) and ulcerative colitis (UC). The major cause of IBD-associated mortality is colorectal cancer. Although both host-genetic and exogenous factors have been found to be involved, the aetiology of IBD is still not well understood. In this study we characterized thirteen <it>Escherichia coli </it>strains from patients with IBD by comparative genomic hybridization employing a microarray based on 31 sequenced <it>E. coli </it>genomes from a wide range of commensal and pathogenic isolates.</p> <p>Results</p> <p>The IBD isolates, obtained from patients with UC and CD, displayed remarkably heterogeneous genomic profiles with little or no evidence of group-specific determinants. No IBD-specific genes were evident when compared with the prototypic CD isolate, LF82, suggesting that the IBD-inducing effect of the strains is multifactorial. Several of the IBD isolates carried a number of extraintestinal pathogenic <it>E. coli </it>(ExPEC)-related virulence determinants such as the <it>pap</it>, <it>sfa</it>, <it>cdt </it>and <it>hly </it>genes. The isolates were also found to carry genes of ExPEC-associated genomic islands.</p> <p>Conclusions</p> <p>Combined, these data suggest that <it>E. coli </it>isolates obtained from UC and CD patients represents a heterogeneous population of strains, with genomic profiles that are indistinguishable to those of ExPEC isolates. Our findings indicate that IBD-induction from <it>E. coli </it>strains is multifactorial and that a range of gene products may be involved in triggering the disease.</p
Observation of Quantum Interference in Molecular Charge Transport
As the dimensions of a conductor approach the nano-scale, quantum effects
will begin to dominate its behavior. This entails the exciting possibility of
controlling the conductance of a device by direct manipulation of the electron
wave function. Such control has been most clearly demonstrated in mesoscopic
semiconductor structures at low temperatures. Indeed, the Aharanov-Bohm effect,
conductance quantization and universal conductance fluctuations are direct
manifestations of the electron wave nature. However, an extension of this
concept to more practical emperatures has not been achieved so far. As
molecules are nano-scale objects with typical energy level spacings (~eV) much
larger than the thermal energy at 300 K (~25 meV), they are natural candidates
to enable such a break-through. Fascinating phenomena including giant
magnetoresistance, Kondo effects and conductance switching, have previously
been demonstrated at the molecular level. Here, we report direct evidence for
destructive quantum interference in charge transport through two-terminal
molecular junctions at room temperature. Furthermore, we show that the degree
of interference can be controlled by simple chemical modifications of the
molecule. Not only does this provide the experimental demonstration of a new
phenomenon in quantum charge transport, it also opens the road for a new type
of molecular devices based on chemical or electrostatic control of quantum
interference
Carbohydrate metabolism of Xylella fastidiosa: Detection of glycolytic and pentose phosphate pathway enzymes and cloning and expression of the enolase gene
Seasonal dynamics of active SAR11 ecotypes in the oligotrophic Northwest Mediterranean Sea
A seven-year oceanographic time series in NW Mediterranean surface waters was combined with pyrosequencing of ribosomal RNA (16S rRNA) and ribosomal RNA gene copies (16S rDNA) to examine the environmental controls on SAR11 ecotype dynamics and potential activity. SAR11 diversity exhibited pronounced seasonal cycles remarkably similar to total bacterial diversity. The timing of diversity maxima was similar across narrow and broad phylogenetic clades and strongly associated with deep winter mixing. Diversity minima were associated with periods of stratification that were low in nutrients and phytoplankton biomass and characterised by intense phosphate limitation (turnover time80%) by SAR11 Ia. A partial least squares (PLS) regression model was developed that could reliably predict sequence abundances of SAR11 ecotypes (Q2=0.70) from measured environmental variables, of which mixed layer depth was quantitatively the most important. Comparison of clade-level SAR11 rRNA:rDNA signals with leucine incorporation enabled us to partially validate the use of these ratios as an in-situ activity measure. However, temporal trends in the activity of SAR11 ecotypes and their relationship to environmental variables were unclear. The strong and predictable temporal patterns observed in SAR11 sequence abundance was not linked to metabolic activity of different ecotypes at the phylogenetic and temporal resolution of our study
Diagnostic properties of metabolic perturbations in rheumatoid arthritis
Introduction: The aim of this study was to assess the feasibility of diagnosing early rheumatoid arthritis (RA) by measuring selected metabolic biomarkers. Methods: We compared the metabolic profile of patients with RA with that of healthy controls and patients with psoriatic arthritis (PsoA). The metabolites were measured using two different chromatography-mass spectrometry platforms, thereby giving a broad overview of serum metabolites. The metabolic profiles of patient and control groups were compared using multivariate statistical analysis. The findings were validated in a follow-up study of RA patients and healthy volunteers. Results: RA patients were diagnosed with a sensitivity of 93% and a specificity of 70% in a validation study using detection of 52 metabolites. Patients with RA or PsoA could be distinguished with a sensitivity of 90% and a specificity of 94%. Glyceric acid, D-ribofuranose and hypoxanthine were increased in RA patients, whereas histidine, threonic acid, methionine, cholesterol, asparagine and threonine were all decreased compared with healthy controls. Conclusions: Metabolite profiling (metabolomics) is a potentially useful technique for diagnosing RA. The predictive value was without regard to the presence of antibodies against cyclic citrullinated peptides
Reducing dimensionality for prediction of genome-wide breeding values
Partial least square regression (PLSR) and principal component regression (PCR) are methods designed for situations where the number of predictors is larger than the number of records. The aim was to compare the accuracy of genome-wide breeding values (EBV) produced using PLSR and PCR with a Bayesian method, 'BayesB'. Marker densities of 1, 2, 4 and 8 N(e )markers/Morgan were evaluated when the effective population size (N(e)) was 100. The correlation between true breeding value and estimated breeding value increased with density from 0.611 to 0.681 and 0.604 to 0.658 using PLSR and PCR respectively, with an overall advantage to PLSR of 0.016 (s.e = 0.008). Both methods gave a lower accuracy compared to the 'BayesB', for which accuracy increased from 0.690 to 0.860. PLSR and PCR appeared less responsive to increased marker density with the advantage of 'BayesB' increasing by 17% from a marker density of 1 to 8N(e)/M. PCR and PLSR showed greater bias than 'BayesB' in predicting breeding values at all densities. Although, the PLSR and PCR were computationally faster and simpler, these advantages do not outweigh the reduction in accuracy, and there is a benefit in obtaining relevant prior information from the distribution of gene effects
Controlling Argan Seed Quality by NIR
The suitability of using visible/near infrared spectroscopy (Vis/NIR), as a rapid and non-destructive technique for monitoring the quality of argan seeds (Argania spinosa Skeels) was studied. The analyzed parameters
were the fatty acid composition of argan seed oil, seed moisture content, seed oil content and oil stability index (OSI). The ratio between major unsaturated and saturated fatty acids (U/S) during the oxidation assay at constant temperature was studied. Values from infrared drying were used as a laboratory reference for the moisture. Argan seed oil content was determined by Soxhlet extraction. A fatty acid analysis was carried out by gas chromatography and the OSI was determined by the Rancimat test. Predictive models of argan seed moisture, ratio U/S and OSI showed good accuracy. Therefore, Vis/NIR measurements can be used for controlling several argan seed quality parameters. This procedure might be of interest to the argan oil industry, which is currently in the process of modernization and expansion.The authors are grateful to the Spanish Agency for the International Cooperation (AECID-MAE) for financing the Project A/019935/08. They also express their gratitude to the industrial plant Argan Oil Company Ltd. Morocco for the argan seed supply.Peer Reviewe
Design Parameters to Control Synthetic Gene Expression in Escherichia coli
BACKGROUND:Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles. PRINCIPAL FINDINGS:To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well. CONCLUSION:The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system
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