Sphingomyelin phosphodiesterase-1 (SMPD1) coding variants do not contribute to low levels of high-density lipoprotein cholesterol

<p>Abstract</p> <p>Background</p> <p>Niemann-Pick disease type A and B is caused by a deficiency of acid sphingomyelinase due to mutations in the sphingomyelin phosphodiesterase-1 (<it>SMPD1</it>) gene. In Niemann-Pick patients, <it>SMPD1 </it>gene defects are reported to be associated with a severe reduction in plasma high-density lipoprotein (HDL) cholesterol.</p> <p>Methods</p> <p>Two common coding polymorphisms in the <it>SMPD1 </it>gene, the G1522A (G508R) and a hexanucleotide repeat sequence within the signal peptide region, were investigated in 118 unrelated subjects of French Canadian descent with low plasma levels of HDL-cholesterol (< 5^thpercentile for age and gender-matched subjects). Control subjects (n = 230) had an HDL-cholesterol level > the 25^thpercentile.</p> <p>Results</p> <p>For G1522A the frequency of the G and A alleles were 75.2% and 24.8% respectively in controls, compared to 78.6% and 21.4% in subjects with low HDL-cholesterol (<it>p </it>= 0.317). The frequency of 6 and 7 hexanucleotide repeats was 46.2% and 46.6% respectively in controls, compared to 45.6% and 49.1% in subjects with low HDL-cholesterol (<it>p </it>= 0.619). Ten different haplotypes were observed in cases and controls. Overall haplotype frequencies in cases and controls were not significantly different.</p> <p>Conclusion</p> <p>These results suggest that the two common coding variants at the <it>SMPD1 </it>gene locus are not associated with low HDL-cholesterol levels in the French Canadian population.</p

NMR-Based Prostate Cancer Metabolomics

Author's accepted version (postprint).This is an Accepted Manuscript of an article published by Springer in Methods in Molecular Biology on 22 May 2018.Available online: https://doi.org/10.1007/978-1-4939-7845-8_14acceptedVersio

Texture classification of proteins using support vector machines and bio-inspired metaheuristics

6th International Joint Conference, BIOSTEC 2013, Barcelona, Spain, February 11-14, 2013[Abstract] In this paper, a novel classification method of two-dimensional polyacrylamide gel electrophoresis images is presented. Such a method uses textural features obtained by means of a feature selection process for whose implementation we compare Genetic Algorithms and Particle Swarm Optimization. Then, the selected features, among which the most decisive and representative ones appear to be those related to the second order co-occurrence matrix, are used as inputs for a Support Vector Machine. The accuracy of the proposed method is around 94 %, a statistically better performance than the classification based on the entire feature set. This classification step can be very useful for discarding over-segmented areas after a protein segmentation or identification process

Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements

<p>Abstract</p> <p>Background</p> <p>Transcription factor binding to DNA requires both an appropriate binding element and suitably open chromatin, which together help to define regulatory elements within the genome. Current methods of identifying regulatory elements, such as promoters or enhancers, typically rely on sequence conservation, existing gene annotations or specific marks, such as histone modifications and p300 binding methods, each of which has its own biases.</p> <p>Results</p> <p>Herein we show that an approach based on clustering of transcription factor peaks from high-throughput sequencing coupled with chromatin immunoprecipitation (Chip-Seq) can be used to evaluate markers for regulatory elements. We used 67 data sets for 54 unique transcription factors distributed over two cell lines to create regulatory element clusters. By integrating the clusters from our approach with histone modifications and data for open chromatin, we identified general methylation of lysine 4 on histone H3 (H3K4me) as the most specific marker for transcription factor clusters. Clusters mapping to annotated genes showed distinct patterns in cluster composition related to gene expression and histone modifications. Clusters mapping to intergenic regions fall into two groups either directly involved in transcription, including miRNAs and long noncoding RNAs, or facilitating transcription by long-range interactions. The latter clusters were specifically enriched with H3K4me1, but less with acetylation of lysine 27 on histone 3 or p300 binding.</p> <p>Conclusion</p> <p>By integrating genomewide data of transcription factor binding and chromatin structure and using our data-driven approach, we pinpointed the chromatin marks that best explain transcription factor association with different regulatory elements. Our results also indicate that a modest selection of transcription factors may be sufficient to map most regulatory elements in the human genome.</p

Pre-Fibrillar α-Synuclein Mutants Cause Parkinson's Disease-Like Non-Motor Symptoms in Drosophila

Parkinson's disease (PD) is linked to the formation of insoluble fibrillar aggregates of the presynaptic protein α-Synuclein (αS) in neurons. The appearance of such aggregates coincides with severe motor deficits in human patients. These deficits are often preceded by non-motor symptoms such as sleep-related problems in the patients. PD-like motor deficits can be recapitulated in model organisms such as Drosophila melanogaster when αS is pan-neurally expressed. Interestingly, both these deficits are more severe when αS mutants with reduced aggregation properties are expressed in flies. This indicates that that αS aggregation is not the primary cause of the PD-like motor symptoms. Here we describe a model for PD in Drosophila which utilizes the targeted expression of αS mutants in a subset of dopadecarboxylase expressing serotonergic and dopaminergic (DA) neurons. Our results show that targeted expression of pre-fibrillar αS mutants not only recapitulates PD-like motor symptoms but also the preceding non-motor symptoms such as an abnormal sleep-like behavior, altered locomotor activity and abnormal circadian periodicity. Further, the results suggest that the observed non-motor symptoms in flies are caused by an early impairment of neuronal functions rather than by the loss of neurons due to cell death

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Measurement of the tt¯tt¯ production cross section in pp collisions at √s=13 TeV with the ATLAS detector

A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb