Large-scale inference of liver fat with neural networks on UK Biobank body MRI

The UK Biobank Imaging Study has acquired medical scans of more than 40,000 volunteer participants. The resulting wealth of anatomical information has been made available for research, together with extensive metadata including measurements of liver fat. These values play an important role in metabolic disease, but are only available for a minority of imaged subjects as their collection requires the careful work of image analysts on dedicated liver MRI. Another UK Biobank protocol is neck-to-knee body MRI for analysis of body composition. The resulting volumes can also quantify fat fractions, even though they were reconstructed with a two- instead of a three-point Dixon technique. In this work, a novel framework for automated inference of liver fat from UK Biobank neck-to-knee body MRI is proposed. A ResNet50 was trained for regression on two-dimensional slices from these scans and the reference values as target, without any need for ground truth segmentations. Once trained, it performs fast, objective, and fully automated predictions that require no manual intervention. On the given data, it closely emulates the reference method, reaching a level of agreement comparable to different gold standard techniques. The network learned to rectify non-linearities in the fat fraction values and identified several outliers in the reference. It outperformed a multi-atlas segmentation baseline and inferred new estimates for all imaged subjects lacking reference values, expanding the total number of liver fat measurements by factor six

Effects of using coding potential, sequence conservation and mRNA structure conservation for predicting pyrroly-sine containing genes

BACKGROUND: Pyrrolysine (the 22nd amino acid) is in certain organisms and under certain circumstances encoded by the amber stop codon, UAG. The circumstances driving pyrrolysine translation are not well understood. The involvement of a predicted mRNA structure in the region downstream UAG has been suggested, but the structure does not seem to be present in all pyrrolysine incorporating genes. RESULTS: We propose a strategy to predict pyrrolysine encoding genes in genomes of archaea and bacteria. We cluster open reading frames interrupted by the amber codon based on sequence similarity. We rank these clusters according to several features that may influence pyrrolysine translation. The ranking effects of different features are assessed and we propose a weighted combination of these features which best explains the currently known pyrrolysine incorporating genes. We devote special attention to the effect of structural conservation and provide further substantiation to support that structural conservation may be influential – but is not a necessary factor. Finally, from the weighted ranking, we identify a number of potentially pyrrolysine incorporating genes. CONCLUSIONS: We propose a method for prediction of pyrrolysine incorporating genes in genomes of bacteria and archaea leading to insights about the factors driving pyrrolysine translation and identification of new gene candidates. The method predicts known conserved genes with high recall and predicts several other promising candidates for experimental verification. The method is implemented as a computational pipeline which is available on request

Uncovering cis Regulatory Codes Using Synthetic Promoter Shuffling

Revealing the spectrum of combinatorial regulation of transcription at individual promoters is essential for understanding the complex structure of biological networks. However, the computations represented by the integration of various molecular signals at complex promoters are difficult to decipher in the absence of simple cis regulatory codes. Here we synthetically shuffle the regulatory architecture — operator sequences binding activators and repressors — of a canonical bacterial promoter. The resulting library of complex promoters allows for rapid exploration of promoter encoded logic regulation. Among all possible logic functions, NOR and ANDN promoter encoded logics predominate. A simple transcriptional cis regulatory code determines both logics, establishing a straightforward map between promoter structure and logic phenotype. The regulatory code is determined solely by the type of transcriptional regulation combinations: two repressors generate a NOR: NOT (a OR b) whereas a repressor and an activator generate an ANDN: a AND NOT b. Three-input versions of both logics, having an additional repressor as an input, are also present in the library. The resulting complex promoters cover a wide dynamic range of transcriptional strengths. Synthetic promoter shuffling represents a fast and efficient method for exploring the spectrum of complex regulatory functions that can be encoded by complex promoters. From an engineering point of view, synthetic promoter shuffling enables the experimental testing of the functional properties of complex promoters that cannot necessarily be inferred ab initio from the known properties of the individual genetic components. Synthetic promoter shuffling may provide a useful experimental tool for studying naturally occurring promoter shuffling

Change in maternal body mass index is associated with offspring body mass index: a 21-year prospective study

High body-mass index (BMI; defined as 25 kg/m(2) or greater) is associated with increased risk of cancer. To inform public health policy and future research, we estimated the global burden of cancer attributable to high BMI in 2012

Investigating the Host Binding Signature on the Plasmodium falciparum PfEMP1 Protein Family

The Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) family plays a central role in antigenic variation and cytoadhesion of P. falciparum infected erythrocytes. PfEMP1 proteins/var genes are classified into three main subfamilies (UpsA, UpsB, and UpsC) that are hypothesized to have different roles in binding and disease. To investigate whether these subfamilies have diverged in binding specificity and test if binding could be predicted by adhesion domain classification, we generated a panel of 19 parasite lines that primarily expressed a single dominant var transcript and assayed binding against 12 known host receptors. By limited dilution cloning, only UpsB and UpsC var genes were isolated, indicating that UpsA var gene expression is rare under in vitro culture conditions. Consequently, three UpsA variants were obtained by rosette purification and selection with specific monoclonal antibodies to create a more representative panel. Binding assays showed that CD36 was the most common adhesion partner of the parasite panel, followed by ICAM-1 and TSP-1, and that CD36 and ICAM-1 binding variants were highly predicted by adhesion domain sequence classification. Binding to other host receptors, including CSA, VCAM-1, HABP1, CD31/PECAM, E-selectin, Endoglin, CHO receptor “X”, and Fractalkine, was rare or absent. Our findings identify a category of larger PfEMP1 proteins that are under dual selection for ICAM-1 and CD36 binding. They also support that the UpsA group, in contrast to UpsB and UpsC var genes, has diverged from binding to the major microvasculature receptor CD36 and likely uses other mechanisms to sequester in the microvasculature. These results demonstrate that CD36 and ICAM-1 have left strong signatures of selection on the PfEMP1 family that can be detected by adhesion domain sequence classification and have implications for how this family of proteins is specializing to exploit hosts with varying levels of anti-malaria immunity

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

<p>Abstract</p> <p>Background</p> <p>Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized.</p> <p>Results</p> <p>We took a different approach from a straightforward extension of the Sankoff algorithm to the multiple alignments from the viewpoints of accuracy and time complexity. As a new option of the MAFFT alignment program, we developed a multiple RNA alignment framework, X-INS-i, which builds a multiple alignment with an iterative method incorporating structural information through two components: (1) pairwise structural alignments by an external pairwise alignment method such as SCARNA or LaRA and (2) a new objective function, Four-way Consistency, derived from the base-pairing probability of every sub-aligned group at every multiple alignment stage.</p> <p>Conclusion</p> <p>The BRAliBASE benchmark showed that X-INS-i outperforms other methods currently available in the sum-of-pairs score (SPS) criterion. As a basis for predicting common secondary structure, the accuracy of the present method is comparable to or rather higher than those of the current leading methods such as RNA Sampler. The X-INS-i framework can be used for building a multiple RNA alignment from any combination of algorithms for pairwise RNA alignment and base-pairing probability. The source code is available at the webpage found in the Availability and requirements section.</p

Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse

CD36 selection of 3D7 Plasmodium falciparum associated with severe childhood malaria results in reduced VAR4 expression

<p>Abstract</p> <p>Background</p> <p>A subset of the <it>Plasmodium falciparum </it>erythrocyte membrane protein 1 (PfEMP1_SM) is involved in the cytoadherence of <it>P. falciparum</it>-infected red blood cells (iRBC) contributing to the pathogenesis of severe disease among young children in malaria endemic areas. The PfEMP1_SMare encoded by group A <it>var </it>genes that are composed of a more constrained range of amino acid sequences than groups B and C <it>var </it>genes encoding PfEMP1_UMassociated with uncomplicated malaria. Also, unlike <it>var </it>genes from groups B and C, those from group A do not have sequences consistent with CD36 binding – a major cytoadhesion phenotype of <it>P. falciparum </it>isolates.</p> <p>Methods</p> <p>A 3D7 PfEMP1_SMsub-line (3D7_SM) expressing VAR4 (PFD1235w/MAL8P1.207) was selected for binding to CD36. The protein expression of this parasite line was monitored by surface staining of iRBC using VAR4-specific antibodies. The serological phenotype of the 3D7_SMparasites was determined by flow cytometry using malaria semi-immune and immune plasma and transcription of the 59 <it>var </it>genes in 3D7 were analysed by real-time quantitative reverse transcriptase-polymerase chain reaction (RT-PCR) using <it>var</it>-specific primers.</p> <p>Results</p> <p>A selection-induced increased adhesion of 3D7_SMiRBC to CD36 resulted in a reduced <it>var4 </it>transcription and VAR4 surface expression.</p> <p>Conclusion</p> <p>VAR4 is not involved in CD36 adhesion. The current findings are consistent with the notion that CD36 adhesion is not associated with particular virulent parasite phenotypes, such as those believed to be exhibited by VAR4 expressing parasites.</p

Generic Insect Repellent Detector from the Fruit Fly Drosophila melanogaster

Background: Insect repellents are prophylactic tools against a number of vector-borne diseases. There is growing demand for repellents outperforming DEET in cost and safety, but with the current technologies R&amp;D of a new product takes almost 10 years, with a prohibitive cost of $30 million dollar in part due to the demand for large-scale synthesis of thousands of test compounds of which only 1 may reach the market. R&amp;D could be expedited and cost dramatically reduced with a molecular/physiological target to streamline putative repellents for final efficacy and toxicological tests. Methodology: Using olfactory-based choice assay we show here that the fruit fly is repelled by not only DEET, but also IR3535 and picaridin thus suggesting they might have ‘‘generic repellent detector(s),’ ’ which may be of practical applications in new repellent screenings. We performed single unit recordings from all olfactory sensilla in the antennae and maxillary palps. Although the ab3A neuron in the wild type flies responded to picaridin, it was unresponsive to DEET and IR3535. By contrast, a neuron housed in the palp basiconic sensilla pb1 responded to DEET, IR3535, and picaridin, with apparent sensitivity higher than that of the DEET detectors in the mosquitoes Culex quinquefasciatus and Aedes aegypti. DmOr42a was transplanted from pb1 to the ‘‘empty neuron’ ’ and showed to be sensitive to the three insect repellents. Conclusions: For the first time we have demonstrated that the fruit fly avoids not only DEET but also IR3535 and picaridin, and identified an olfactory receptor neuron (ORN), which is sensitive to these three major insect repellents. We have als