miR-375 suppresses IGF1R expression and contributes to inhibition cell progression in laryngeal squamous cell carcinoma

published_or_final_versio

The impact of different DNA extraction kits and laboratories upon the assessment of human gut microbiota composition by 16S rRNA gene sequencing

Peer reviewedPublisher PD

Effects of a Water-Soluble Cinnamon Extract on Body Composition and Features of the Metabolic Syndrome in Pre-Diabetic Men and Women

Purpose: The purpose of this study was to determine the effects of supplementation with a water-soluble cinnamon extract (Cinnulin PF®) on body composition and features of the metabolic syndrome. Methods: Twenty-two subjects with prediabetes and the metabolic syndrome (mean ± SD: age, BMI, systolic blood pressure [SBP], fasting blood glucose [FBG]: 46.0 ± 9.7 y; 33.2 ± 9.3 kg/m 2; 133 ± 17 mm Hg; 114.3 ± 11.6 mg/dL) were randomly assigned to supplement their diet with either Cinnulin PF ® (500 mg/d) or a placebo for 12-weeks. Main outcome measures were changes in FBG, SBP, and body composition measured after 12-weeks of supplementation. The primary statistical analyses consisted of two factor (group x time), repeated-measures ANOVA for between group differences over time. In all analyses, an intent-to-treat approach was used and significance was accepted at P<0.05. Results: Subjects in the Cinnulin PF ® group had significant decreases in FBG (-8.4%: 116.3 ± 12.8 mg/dL [pre] to 106.5 ± 20.1 mg/dL [post], p<0.01), SBP (-3.8%: 133 ± 14 mm Hg [pre] to 128 ± 18 mm Hg [post], p<0.001), and increases in lean mass (+1.1%: 53.7 ± 11.8 kg [pre] to 54.3 ± 11.8 kg [post], p<0.002) compared with the placebo group. Additionally, within-group analyses uncovered small, but statistically significant decreases in body fat (-0.7%: 37.9 ± 9.2 % [pre] to 37.2 ± 8.9 % [post], p<0.02) in the Cinnulin PF ® group. No significant changes in clinical blood chemistries were observed betwee

Natural History, Microbes and Sequences: Shouldn't We Look Back Again to Organisms?

The discussion on the existence of prokaryotic species is reviewed. The demonstration that several different mechanisms of genetic exchange and recombination exist has led some to a radical rejection of the possibility of bacterial species and, in general, the applicability of traditional classification categories to the prokaryotic domains. However, in spite of intense gene traffic, prokaryotic groups are not continuously variable but form discrete clusters of phenotypically coherent, well-defined, diagnosable groups of individual organisms. Molecularization of life sciences has led to biased approaches to the issue of the origins of biodiversity, which has resulted in the increasingly extended tendency to emphasize genes and sequences and not give proper attention to organismal biology. As argued here, molecular and organismal approaches that should be seen as complementary and not opposed views of biology

FastTagger: an efficient algorithm for genome-wide tag SNP selection using multi-marker linkage disequilibrium

<p>Abstract</p> <p>Background</p> <p>Human genome contains millions of common single nucleotide polymorphisms (SNPs) and these SNPs play an important role in understanding the association between genetic variations and human diseases. Many SNPs show correlated genotypes, or linkage disequilibrium (LD), thus it is not necessary to genotype all SNPs for association study. Many algorithms have been developed to find a small subset of SNPs called tag SNPs that are sufficient to infer all the other SNPs. Algorithms based on the <it>r</it>²LD statistic have gained popularity because <it>r</it>²is directly related to statistical power to detect disease associations. Most of existing <it>r</it>²based algorithms use pairwise LD. Recent studies show that multi-marker LD can help further reduce the number of tag SNPs. However, existing tag SNP selection algorithms based on multi-marker LD are both time-consuming and memory-consuming. They cannot work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>Results</p> <p>We propose an efficient algorithm called FastTagger to calculate multi-marker tagging rules and select tag SNPs based on multi-marker LD. FastTagger uses several techniques to reduce running time and memory consumption. Our experiment results show that FastTagger is several times faster than existing multi-marker based tag SNP selection algorithms, and it consumes much less memory at the same time. As a result, FastTagger can work on chromosomes containing more than 100 k SNPs using length-3 tagging rules.</p> <p>FastTagger also produces smaller sets of tag SNPs than existing multi-marker based algorithms, and the reduction ratio ranges from 3%-9% when length-3 tagging rules are used. The generated tagging rules can also be used for genotype imputation. We studied the prediction accuracy of individual rules, and the average accuracy is above 96% when <it>r</it>²≥ 0.9.</p> <p>Conclusions</p> <p>Generating multi-marker tagging rules is a computation intensive task, and it is the bottleneck of existing multi-marker based tag SNP selection methods. FastTagger is a practical and scalable algorithm to solve this problem.</p

Identification of actinomycetes from plant rhizospheric soils with inhibitory activity against Colletotrichum spp., the causative agent of anthracnose disease

<p>Abstract</p> <p>Background</p> <p><it>Colletotrichum </it>is one of the most widespread and important genus of plant pathogenic fungi worldwide. Various species of <it>Colletotrichum </it>are the causative agents of anthracnose disease in plants, which is a severe problem to agricultural crops particularly in Thailand. These phytopathogens are usually controlled using chemicals; however, the use of these agents can lead to environmental pollution. Potential non-chemical control strategies for anthracnose disease include the use of bacteria capable of producing anti-fungal compounds such as actinomycetes spp., that comprise a large group of filamentous, Gram positive bacteria from soil. The aim of this study was to isolate actinomycetes capable of inhibiting the growth of <it>Colletotrichum </it>spp, and to analyze the diversity of actinomycetes from plant rhizospheric soil.</p> <p>Results</p> <p>A total of 304 actinomycetes were isolated and tested for their inhibitory activity against <it>Colletotrichum gloeosporioides </it>strains DoA d0762 and DoA c1060 and <it>Colletotrichum capsici </it>strain DoA c1511 which cause anthracnose disease as well as the non-pathogenic <it>Saccharomyces cerevisiae </it>strain IFO 10217. Most isolates (222 out of 304, 73.0%) were active against at least one indicator fungus or yeast. Fifty four (17.8%) were active against three anthracnose fungi and 17 (5.6%) could inhibit the growth of all three fungi and <it>S. cerevisiae </it>used in the test. Detailed analysis on 30 selected isolates from an orchard at Chanthaburi using the comparison of 16S rRNA gene sequences revealed that most of the isolates (87%) belong to the genus <it>Streptomyces </it>sp., while one each belongs to <it>Saccharopolyspora </it>(strain SB-2) and <it>Nocardiopsis </it>(strain CM-2) and two to <it>Nocardia </it>(strains BP-3 and LK-1). Strains LC-1, LC-4, JF-1, SC-1 and MG-1 exerted high inhibitory activity against all three anthracnose fungi and yeast. In addition, the organic solvent extracts prepared from these five strains inhibited conidial growth of the three indicator fungi. Preliminary analysis of crude extracts by high performance liquid chromatography (HPLC) indicated that the sample from strain JF-1 may contain a novel compound. Phylogenetic analysis revealed that this strain is closely related to <it>Streptomyces cavurensis </it>NRRL 2740 with 99.8% DNA homology of 16S rRNA gene (500 bp).</p> <p>Conclusion</p> <p>The present study suggests that rhizospheric soil is an attractive source for the discovery of a large number of actinomycetes with activity against <it>Colletotrichum </it>spp. An interesting strain (JF-1) with high inhibitory activity has the potential to produce a new compound that may be useful in the control of <it>Colletotrichum </it>spp.</p

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal