Nanotechnology and global energy demand: challenges and prospects for a paradigm shift in the oil and gas industry.

The exploitation of new hydrocarbon discoveries in meeting the present global energy demand is a function of the availability and application of new technologies. The relevance of new technologies is borne out of the complex subsurface architecture and conditions of offshore petroleum plays. Conventional techniques, from drilling to production, for exploiting these discoveries may require adaption for such subsurface conditions as they fail under conditions of high pressure and high temperature. The oil and gas industry over the past decades has witnessed increased research into the use of nanotechnology with great promise for drilling operations, enhanced oil recovery, reservoir characterization, production, etc. The prospect for a paradigm shift towards the application of nanotechnology in the oil and gas industry is constrained by evolving challenges with its progression. This paper gave a review of developments from nano-research in the oil and gas industry, challenges and recommendations

Convergent algorithms for protein structural alignment

<p>Abstract</p> <p>Background</p> <p>Many algorithms exist for protein structural alignment, based on internal protein coordinates or on explicit superposition of the structures. These methods are usually successful for detecting structural similarities. However, current practical methods are seldom supported by convergence theories. In particular, although the goal of each algorithm is to maximize some scoring function, there is no practical method that theoretically guarantees score maximization. A practical algorithm with solid convergence properties would be useful for the refinement of protein folding maps, and for the development of new scores designed to be correlated with functional similarity.</p> <p>Results</p> <p>In this work, the maximization of scoring functions in protein alignment is interpreted as a Low Order Value Optimization (LOVO) problem. The new interpretation provides a framework for the development of algorithms based on well established methods of continuous optimization. The resulting algorithms are convergent and <it>increase the scoring functions at every iteration</it>. The solutions obtained are critical points of the scoring functions. Two algorithms are introduced: One is based on the maximization of the scoring function with Dynamic Programming followed by the continuous maximization of <it>the same </it>score, with respect to the protein position, using a smooth Newtonian method. The second algorithm replaces the Dynamic Programming step by a fast procedure for computing the correspondence between C<it>α </it>atoms. The algorithms are shown to be very effective for the maximization of the STRUCTAL score.</p> <p>Conclusion</p> <p>The interpretation of protein alignment as a LOVO problem provides a new theoretical framework for the development of convergent protein alignment algorithms. These algorithms are shown to be very reliable for the maximization of the STRUCTAL score, and other distance-dependent scores may be optimized with same strategy. The improved score optimization provided by these algorithms provide means for the refinement of protein fold maps and also for the development of scores designed to match biological function. The LOVO strategy may be also used for more general structural superposition problems such as flexible or non-sequential alignments. The package is available on-line at http://www.ime.unicamp.br/~martinez/lovoalign.</p

Using Multiple Microenvironments to Find Similar Ligand-Binding Sites: Application to Kinase Inhibitor Binding

The recognition of cryptic small-molecular binding sites in protein structures is important for understanding off-target side effects and for recognizing potential new indications for existing drugs. Current methods focus on the geometry and detailed chemical interactions within putative binding pockets, but may not recognize distant similarities where dynamics or modified interactions allow one ligand to bind apparently divergent binding pockets. In this paper, we introduce an algorithm that seeks similar microenvironments within two binding sites, and assesses overall binding site similarity by the presence of multiple shared microenvironments. The method has relatively weak geometric requirements (to allow for conformational change or dynamics in both the ligand and the pocket) and uses multiple biophysical and biochemical measures to characterize the microenvironments (to allow for diverse modes of ligand binding). We term the algorithm PocketFEATURE, since it focuses on pockets using the FEATURE system for characterizing microenvironments. We validate PocketFEATURE first by showing that it can better discriminate sites that bind similar ligands from those that do not, and by showing that we can recognize FAD-binding sites on a proteome scale with Area Under the Curve (AUC) of 92%. We then apply PocketFEATURE to evolutionarily distant kinases, for which the method recognizes several proven distant relationships, and predicts unexpected shared ligand binding. Using experimental data from ChEMBL and Ambit, we show that at high significance level, 40 kinase pairs are predicted to share ligands. Some of these pairs offer new opportunities for inhibiting two proteins in a single pathway

Mathematical Model of Plasmid-Mediated Resistance to Ceftiofur in Commensal Enteric Escherichia coli of Cattle

Antimicrobial use in food animals may contribute to antimicrobial resistance in bacteria of animals and humans. Commensal bacteria of animal intestine may serve as a reservoir of resistance-genes. To understand the dynamics of plasmid-mediated resistance to cephalosporin ceftiofur in enteric commensals of cattle, we developed a deterministic mathematical model of the dynamics of ceftiofur-sensitive and resistant commensal enteric Escherichia coli (E. coli) in the absence of and during parenteral therapy with ceftiofur. The most common treatment scenarios including those using a sustained-release drug formulation were simulated; the model outputs were in agreement with the available experimental data. The model indicated that a low but stable fraction of resistant enteric E. coli could persist in the absence of immediate ceftiofur pressure, being sustained by horizontal and vertical transfers of plasmids carrying resistance-genes, and ingestion of resistant E. coli. During parenteral therapy with ceftiofur, resistant enteric E. coli expanded in absolute number and relative frequency. This expansion was most influenced by parameters of antimicrobial action of ceftiofur against E. coli. After treatment (>5 weeks from start of therapy) the fraction of ceftiofur-resistant cells among enteric E. coli, similar to that in the absence of treatment, was most influenced by the parameters of ecology of enteric E. coli, such as the frequency of transfer of plasmids carrying resistance-genes, the rate of replacement of enteric E. coli by ingested E. coli, and the frequency of ceftiofur resistance in the latter

Cancer Treatment and Bone Health

Considerable advances in oncology over recent decades have led to improved survival, while raising concerns about long-term consequences of anticancer treatments. In patients with breast or prostate malignancies, bone health is a major issue due to the high risk of bone metastases and the frequent prolonged use of hormone therapies that alter physiological bone turnover, leading to increased fracture risk. Thus, the onset of cancer treatment-induced bone loss (CTIBL) should be considered by clinicians and recent guidelines should be routinely applied to these patients. In particular, baseline and periodic follow-up evaluations of bone health parameters enable the identification of patients at high risk of osteoporosis and fractures, which can be prevented by the use of bone-targeting agents (BTAs), calcium and vitamin D supplementation and modifications of lifestyle. This review will focus upon the pathophysiology of breast and prostate cancer treatment-induced bone loss and the most recent evidence about effective preventive and therapeutic strategies

Updated measurements of exclusive J/ψ and ψ(2S) production cross-sections in pp collisions at √s = 7 TeV

The differential cross-section as a function of rapidity has been measured for the exclusive production of J/ψ and ψ(2S) mesons in proton–proton collisions at √s = 7 TeV, using data collected by the LHCb experiment, corresponding to an integrated luminosity of 930 pb−1. The cross-sections times branching fractions to two muons having pseudorapidities between 2.0 and 4.5 are measured to be where the first uncertainty is statistical and the second is systematic. The measurements agree with next-to-leading order QCD predictions as well as with models that include saturation effects

Studies of beauty baryon decays to D0ph− and Λ+ch− final states

Decays of beauty baryons to the D0ph− and Λ+ch− final states (where h indicates a pion or a kaon) are studied using a data sample of pp collisions, corresponding to an integrated luminosity of 1.0  fb−1, collected by the LHCb detector. The Cabibbo-suppressed decays Λ0b→D0pK− and Λ0b→Λ+cK− are observed, and their branching fractions are measured with respect to the decays Λ0b→D0pπ− and Λ0b→Λ+cπ−. In addition, the first observation is reported of the decay of the neutral beauty-strange baryon Ξ0b to the D0pK− final state, and a measurement of the Ξ0b mass is performed. Evidence of the Ξ0b→Λ+cK− decay is also reported