The Genome of Anopheles darlingi, the main neotropical malaria vector

Anopheles darlingi is the principal neotropical malaria vector, responsible for more than a million cases of malaria per year on the American continent. Anopheles darlingi diverged from the African and Asian malaria vectors ∼100 million years ago (mya) and successfully adapted to the New World environment. Here we present an annotated reference A. darlingi genome, sequenced from a wild population of males and females collected in the Brazilian Amazon. A total of 10 481 predicted protein-coding genes were annotated, 72% of which have their closest counterpart in Anopheles gambiae and 21% have highest similarity with other mosquito species. In spite of a long period of divergent evolution, conserved gene synteny was observed between A. darlingi and A. gambiae. More than 10 million single nucleotide polymorphisms and short indels with potential use as genetic markers were identified. Transposable elements correspond to 2.3% of the A. darlingi genome. Genes associated with hematophagy, immunity and insecticide resistance, directly involved in vectorhuman and vectorparasite interactions, were identified and discussed. This study represents the first effort to sequence the genome of a neotropical malaria vector, and opens a new window through which we can contemplate the evolutionary history of anopheline mosquitoes. It also provides valuable information that may lead to novel strategies to reduce malaria transmission on the South American continent. The A. darlingi genome is accessible at www.labinfo.lncc.br/index.php/anopheles- darlingi. © 2013 The Author(s).

Computations of Vector-Valued Siegel Modular Forms

We carry out some computations of vector-valued Siegel modular forms of degree two, weight (k, 2) and level one, and highlight three experimental results: (1) we identify a rational eigenform in a three-dimensional space of cusp forms; (2) we observe that non-cuspidal eigenforms of level one are not always rational; (3) we verify a number of cases of conjectures about congruences between classical modular forms and Siegel modular forms. Our approach is based on Satoh's description of the module of vector-valued Siegel modular forms of weight (k, 2) and an explicit description of the Hecke action on Fourier expansions. (C) 2013 Elsevier Inc. All rights reserved.

Local targeting of malignant gliomas by the diffusible peptidic vector 1,4,7,10-tetraazacyclododecane-1-glutaric acid-4,7,10-triacetic acid-substance p

PURPOSE: Malignant glial brain tumors consistently overexpress neurokinin type 1 receptors. In classic seed-based brachytherapy, one to several rigid (125)I seeds are inserted, mainly for the treatment of small low-grade gliomas. The complex geometry of rapidly proliferating high-grade gliomas requires a diffusible system targeting tumor-associated surface structures to saturate the tumor, including its margins. EXPERIMENTAL DESIGN: We developed a new targeting vector by conjugating the chelator 1,4,7,10-tetraazacyclododecane-1-glutaric acid-4,7,10-triacetic acid to Arg(1) of substance P, generating a radiopharmaceutical with a molecular weight of 1,806 Da and an IC(50) of 0.88 +/- 0.34 nmol/L. Cell biological studies were done with glioblastoma cell lines. neurokinin type-1 receptor (NK1R) autoradiography was done with 58 tumor biopsies. For labeling, (90)Y was mostly used. To reduce the "cross-fire effect" in critically located tumors, (177)Lut and (213)Bi were used instead. In a pilot study, we assessed feasibility, biodistribution, and early and long-term toxicity following i.t. injection of radiolabeled 1,4,7,10-tetraazacyclododecane-1-glutaric acid-4,7,10-triacetic acid substance P in 14 glioblastoma and six glioma patients of WHO grades 2 to 3. RESULTS: Autoradiography disclosed overexpression of NK1R in 55 of 58 gliomas of WHO grades 2 to 4. Internalization of the peptidic vector was found to be specific. Clinically, the radiopharmeutical was distributed according to tumor geometry. Only transient toxicity was seen as symptomatic radiogenic edema in one patient (observation period, 7-66 months). Disease stabilization and/or improved neurologic status was observed in 13 of 20 patients. Secondary resection disclosed widespread radiation necrosis with improved demarcation. CONCLUSIONS: Targeted radiotherapy using diffusible peptidic vectors represents an innovative strategy for local control of malignant gliomas, which will be further assessed as a neoadjuvant approach.

Incorporating equity into transport planning: utility, priority and sufficiency approaches

The analysis addresses the issue of transport equity and explores three different approaches to equity in transport: utilitarianism, sufficientarianism and prioritarianism. Each approach calls for a different treatment of the benefits reaped by different population groups in the assessment of transport investments or policies. In utilitarianism, which underlies much of the current practice of transport project appraisal, all benefits receive the same weight, irrespective of the recipient of the benefits. In both sufficientarianism and prioritarianism, benefits are weighed in distinct ways, depending on the characteristics of the recipients. The three approaches are illustrated using a fictive case study, in which three different transport investment are assessed and compared to each other. Finally, the assessment of transport investments will be explored using the cost-effectiveness analysis (CEA). The CEA assesses the distributional effects of transport investments for utilitarism, sufficientarism and prioritarism approaches and addresses distinct needs associated with different population groups in respect to their transport

Stable transfer of intact high molecular weight DNA into plant chromosomes.

In conjunction with an enhanced system for Agrobacterium-mediated plant transformation, a new binary bacterial artificial chromosome (BIBAC) vector has been developed that is capable of transferring at least 150 kb of foreign DNA into a plant nuclear genome. The transferred DNA appears to be intact in the majority of transformed tobacco plants analyzed and is faithfully inherited in the progeny. The ability to introduce high molecular weight DNA into plant chromosomes should accelerate gene identification and genetic engineering of plants and may lead to new approaches in studies of genome organization.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Tracking the states of a nonlinear and nonstationary system in the weight-space of artificial neural networks

We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.

On the Weight Distribution of the Coset Leaders of Constacyclic Codes

Constacyclic codes with one and the same generator polynomial and distinct length are considered. We give a generalization of the previous result of the first author [4] for constacyclic codes. Suitable maps between vector spaces determined by the lengths of the codes are applied. It is proven that the weight distributions of the coset leaders don’t depend on the word length, but on generator polynomials only. In particular, we prove that every constacyclic code has the same weight distribution of the coset leaders as a suitable cyclic code.

Efficient Computing of some Vector Operations over GF(3) and GF(4)

The problem of efficient computing of the affine vector operations (addition of two vectors and multiplication of a vector by a scalar over GF (q)), and also the weight of a given vector, is important for many problems in coding theory, cryptography, VLSI technology etc. In this paper we propose a new way of representing vectors over GF (3) and GF (4) and we describe an efficient performance of these affine operations. Computing weights of binary vectors is also discussed.

Extended Energy Vector Prediction of Ambisonically Reproduced Image Direction at Off-Centre Listening Positions

This paper presents an extension to the energy vector, well known in the Ambisonics literature, to improve its predictions of localisation at off-centre listening positions. In determining the source direction, a perceptual weight is assigned to each loudspeaker gain, taking into account the relative arrival times, levels, and directions of the loudspeaker signals. The proposed model is evaluated alongside the original energy vector and two binaural models through comparison with the results of recent perceptual studies. The extended version was found to provide results that were at least 50% more accurate than the second best predictor for two experiments involving off-centre listeners with first- and third-order Ambisonics systems.

The £ for lb challenge – a lose – win – win scenario. Results from a novel workplace-based, peer-led weight management programme

Title: The £ for lb. Challenge – A lose - win – win scenario. Results from a novel workplace-based, peer-led weight management programme in 2016.

Names: Damien Bennett, Declan Bradley, Angela McComb, Amy Kiernan, Tracey Owen

Background: Tackling obesity is a public health priority. The £ for lb. Challenge is the first country wide, workplace-based peer-led weight management programme in the UK or Ireland with participants from a range of private and public businesses in Northern Ireland (NI).
Intervention: The intervention was workplace-based, led by workplace Champions and based on the NHS Choices 12 week weight loss guide. It operated from January to April 2016. Overweight and obese adult workers were eligible. Training of Peer Champions (staff volunteers) involved two half day workshops delivered by dieticians and physical activity professionals.
Outcome measurement: Weight was measured at enrolment and 12 weekly intervals. Changes in weight, % weight, BMI and % BMI were determined for the whole cohort and sex and deprivation subgroups.
Results: There were 1513 eligible participants from 35 companies. Engagement rate was 98%. 75% of participants completed the programme. Mean weight loss was 2.4 kg or 2.7%. Almost a quarter (24%) lost at least 5% initial bodyweight. Male participants were over twice as likely to complete the programme and three times more likely to lose 5% body weight or more. Over £17,000 was raised for NI charities.
Discussion: The £ for lb. Challenge is a successful health improvement programme with important weight loss for many participants, particularly male workers. With high levels of user engagement and ownership and successful multidisciplinary collaboration between public health, voluntary bodies, private and public companies it is a novel workplace based model with potential to expand.