Metal-Organic Framework-Based Sensor for Bacterial Trehalose in Beef Products

Objective The objective is to detect trehalose from pathogenic bacteria using an electrochemical sensor based on alkali earth metal-organic frameworks (AE-MOFS)

Chemical signals act as the main reproductive barrier between sister and mimetic Heliconius butterflies.

Colour pattern is the main trait that drives mate recognition between Heliconius species that are phylogenetically close. However, when this cue is compromised such as in cases of mimetic, sympatric and closely related species, alternative mating signals must evolve to ensure reproductive isolation and species integrity. The closely related species Heliconius melpomene malleti and H. timareta florencia occur in the same geographical region, and despite being co-mimics, they display strong reproductive isolation. In order to test which cues differ between species, and potentially contribute to reproductive isolation, we quantified differences in the wing phenotype and the male chemical profile. As expected, the wing colour pattern was indistinguishable between the two species, while the chemical profile of the androconial and genital males' extracts showed marked differences. We then conducted behavioural experiments to study the importance of these signals in mate recognition by females. In agreement with our previous results, we found that chemical blends and not wing colour pattern drive the preference of females for conspecific males. Also, experiments with hybrid males and females suggested an important genetic component for both chemical production and preference. Altogether, these results suggest that chemicals are the major reproductive barrier opposing gene flow between these two sister and co-mimic species

Accurate masses and radii of normal stars: modern results and applications

This paper presents and discusses a critical compilation of accurate, fundamental determinations of stellar masses and radii. We have identified 95 detached binary systems containing 190 stars (94 eclipsing systems, and alpha Centauri) that satisfy our criterion that the mass and radius of both stars be known to 3% or better. To these we add interstellar reddening, effective temperature, metal abundance, rotational velocity and apsidal motion determinations when available, and we compute a number of other physical parameters, notably luminosity and distance. We discuss the use of this information for testing models of stellar evolution. The amount and quality of the data also allow us to analyse the tidal evolution of the systems in considerable depth, testing prescriptions of rotational synchronisation and orbital circularisation in greater detail than possible before. The new data also enable us to derive empirical calibrations of M and R for single (post-) main-sequence stars above 0.6 M(Sun). Simple, polynomial functions of T(eff), log g and [Fe/H] yield M and R with errors of 6% and 3%, respectively. Excellent agreement is found with independent determinations for host stars of transiting extrasolar planets, and good agreement with determinations of M and R from stellar models as constrained by trigonometric parallaxes and spectroscopic values of T(eff) and [Fe/H]. Finally, we list a set of 23 interferometric binaries with masses known to better than 3%, but without fundamental radius determinations (except alpha Aur). We discuss the prospects for improving these and other stellar parameters in the near future.Comment: 56 pages including figures and tables. To appear in The Astronomy and Astrophysics Review. Ascii versions of the tables will appear in the online version of the articl

Open MS/MS spectral library search to identify unanticipated post-translational modifications and increase spectral identification rate

Motivation: Identification of post-translationally modified proteins has become one of the central issues of current proteomics. Spectral library search is a new and promising computational approach to mass spectrometry-based protein identification. However, its potential in identification of unanticipated post-translational modifications has rarely been explored. The existing spectral library search tools are designed to match the query spectrum to the reference library spectra with the same peptide mass. Thus, spectra of peptides with unanticipated modifications cannot be identified

Country-specific birth weight and length in type 1 diabetes high-risk HLA genotypes in combination with prenatal characteristics

Objective:To examine the relationship between high-risk human leukocyte antigen (HLA) genotypes for type 1 diabetes and birth size in combination with prenatal characteristics in different countries.Study Design:Four high-risk HLA genotypes were enrolled in the Environmental determinants of Diabetes in the Young study newborn babies from the general population in Finland, Germany, Sweden and the United States. Stepwise regression analyses were used to adjust for country, parental physical characteristics and environmental factors during pregnancy.Result:Regression analyses did not reveal differences in birth size between the four type 1 diabetes high-risk HLA genotypes. Compared with DQ 4/8 in each country, (1) DQ 2/2 children were heavier in the United States (P=0.028) mostly explained however, by parental weight; (2) DQ 2/8 (P=0.023) and DQ 8/8 (P=0.046) children were longer in Sweden independent of parents height and as well as (3) in the United States for DQ 2/8 (P=0.023), but again dependent on parental height.Conclusion:Children born with type 1 diabetes high-risk HLA genotypes have comparable birth size. Longitudinal follow-up of these children should reveal whether birth size differences between countries contribute to the risk for islet autoimmunity and type 1 diabetes.Journal of Perinatology advance online publication, 28 April 2011; doi:10.1038/jp.2011.26

Regioselective Access to Sultam Motifs through Cobalt-Catalyzed Annulation of Aryl Sulfonamides and Alkynes using an 8-Aminoquinoline Directing Group

The use of cobalt as catalyst in direct C[BOND]H activation protocols as a replacement for more expensive second row transition metals is currently attracting significant attention. Herein we disclose a facile cobalt-catalyzed C[BOND]H functionalization route towards sultam motifs through annulation of easily prepared aryl sulfonamides and alkynes using 8-aminoquinoline as a directing group. The reaction shows broad substrate scope with products obtained in a highly regioselective manner in good to excellent isolated yields. Mechanistic insights suggest the formation of a Co(III)-aryl key species via a rate-determining arene C[BOND]H activation during the annulation reaction

The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis

Background:To investigate small-nucleolar RNAs (snoRNAs) as reference genes when measuring miRNA expression in tumour samples, given emerging evidence for their role in cancer.Methods:Four snoRNAs, commonly used for normalisation, RNU44, RNU48, RNU43 and RNU6B, and miRNA known to be associated with pathological factors, were measured by real-time polymerase chain reaction in two patient series: 219 breast cancer and 46 head and neck squamous cell carcinoma (HNSCC). SnoRNA and miRNA were then correlated with clinicopathological features and prognosis.Results:Small-nucleolar RNA expression was as variable as miRNA expression (miR-21, miR-210, miR-10b). Normalising miRNA PCR expression data to these recommended snoRNAs introduced bias in associations between miRNA and pathology or outcome. Low snoRNA expression correlated with markers of aggressive pathology. Low levels of RNU44 were associated with a poor prognosis. RNU44 is an intronic gene in a cluster of highly conserved snoRNAs in the growth arrest specific 5 (GAS5) transcript, which is normally upregulated to arrest cell growth under stress. Low-tumour GAS5 expression was associated with a poor prognosis. RNU48 and RNU43 were also identified as intronic snoRNAs within genes that are dysregulated in cancer.Conclusion:Small-nucleolar RNAs are important in cancer prognosis, and their use as reference genes can introduce bias when determining miRNA expression. © 2011 Cancer Research UK All rights reserved

Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach

<p>Abstract</p> <p>Background</p> <p>For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or <it>in-silico </it>deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.</p> <p>Results</p> <p>Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach.</p> <p>Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.</p> <p>Conclusions</p> <p>The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.</p

Laboratory evolution of Pyrococcus furiosus alcohol dehydrogenase to improve the production of (2S,5S)-hexanediol at moderate temperatures

There is considerable interest in the use of enantioselective alcohol dehydrogenases for the production of enantio- and diastereomerically pure diols, which are important building blocks for pharmaceuticals, agrochemicals and fine chemicals. Due to the need for a stable alcohol dehydrogenase with activity at low-temperature process conditions (30°C) for the production of (2S,5S)-hexanediol, we have improved an alcohol dehydrogenase from the hyperthermophilic archaeon Pyrococcus furiosus (AdhA). A stable S-selective alcohol dehydrogenase with increased activity at 30°C on the substrate 2,5-hexanedione was generated by laboratory evolution on the thermostable alcohol dehydrogenase AdhA. One round of error-prone PCR and screening of ∼1,500 mutants was performed. The maximum specific activity of the best performing mutant with 2,5-hexanedione at 30°C was tenfold higher compared to the activity of the wild-type enzyme. A 3D-model of AdhA revealed that this mutant has one mutation in the well-conserved NADP(H)-binding site (R11L), and a second mutation (A180V) near the catalytic and highly conserved threonine at position 183

miR-22 represses cancer progression by inducing cellular senescence

The microRNA miR-22 targets CDK6, SIRT1, and Sp1—genes involved in regulation of the senescence program—to suppress cell growth and proliferation