1,338 research outputs found

    Molecular Characterization of Isoniazid and Rifampin Resistance of Mycobacterium tuberculosis Clinical Isolates from Malatya, Turkey

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    Molecular characterization of drug resistance of Mycobacterium tuberculosis strains of different origins can generate information useful for developing molecular methods that are widely applicable for rapid drug resistance detection. Using DNA sequencing and allele-specific polymerase chain reaction (AS-PCR), we investigated genetic mutations associated with isoniazid (INH) and rifampin (RIF) resistance among 29 drug-resistant clinical isolates of M. tuberculosis collected from Malatya, Turkey, including 19 multi-drug-resistant (MDR) isolates. Point mutations were detected at codons 531, 516, 526, and 513 of the RNA polymerase β- subunit gene (rpoB) in 10 (47.6%), five (23.8%), three (14.3%), and three (14.3%) of the 21 RIF-resistant isolates, respectively. Of the five isolates having mutations in codon 516, three also had mutations at codon 527; one had a concurrent mutation at codon 572. Mutations at codon 315 of the catalase-peroxidase-encoding gene (katG) were found in 17 (63.0%) of the 27 INH-resistant isolates. Interestingly, the katG codon 315 mutation was observed at a much higher frequency in MDR isolates than in INH-mono-resistant isolates (∼79% vs. 25%). This study provided the first molecular characterization of INH and RIF resistance of M. tuberculosis clinical isolates from Eastern Turkey, and extended our knowledge of molecular basis of M. tuberculosis drug resistance.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63182/1/mdr.2005.11.94.pd

    Spin Polarized and Valley Helical Edge Modes in Graphene Nanoribbons

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    Inspired by recent progress in fabricating precisely zigzag-edged graphene nanoribbons and the observation of edge magnetism, we find that spin polarized edge modes with well-defined valley index can exist in a bulk energy gap opened by a staggered sublattice potential such as that provided by a hexagonal Boron-Nitride substrate. Our result is obtained by both tight-binding model and first principles calculations. These edge modes are helical with respect to the valley degree of freedom, and are robust against scattering, as long as the disorder potential is smooth over atomic scale, resulting from the protection of the large momentum separation of the valleys.Comment: 4 pages, 4 figure

    Adaptive Backstepping-based H∞ Robust controller for Photovoltaic Grid-connected Inverter

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    To improve the robustness and stability of the photovoltaic grid-connected inverter system, a nonlinear backstepping-based H∞ controller is proposed. A generic dynamical model of grid-connected inverters is built with the consideration of uncertain parameters and external disturbances that cannot be accurately measured. According to this, the backstepping H∞ controller is designed by combining techniques of adaptive backstepping control and L2-gain robust control. The Lyapunov function is used to design the backstepping controller, and the dissipative inequality is recursively designed. The storage functions of the DC capacitor voltage and grid current are constructed, respectively, and the nonlinear H∞ controller and the parameter update law are obtained. Experimental results show that the proposed controller has the advantage of strong robustness to parameter variations and external disturbances. The proposed controller can also accurately track the references to meet the requirements of high-performance control of grid-connected inverters

    Using epitope predictions to evaluate efficacy and population coverage of the Mtb72f vaccine for tuberculosis

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    <p>Abstract</p> <p>Background</p> <p>The Mtb72f subunit vaccine for tuberculosis, currently in clinical trials, is hoped to provide improved protection compared to the current BCG vaccine. It is not clear, however, whether Mtb72f would be equally protective in the different human populations suffering from a high burden of tuberculosis. Previous work by Hebert and colleagues demonstrated that the PPE18 protein of Mtb72f had significant variability in a sample of clinical <it>M. tuberculosis </it>isolates. However, whether this variation might impact the efficacy of Mtb72f in the context of the microbial and host immune system interactions remained to be determined. The present study assesses Mtb72f's predicted efficacy in people with different DRB1 genotypes to predict whether the vaccine will protect against diverse clinical strains of <it>M. tuberculosis </it>in a diverse host population.</p> <p>Results</p> <p>We evaluated the binding of epitopes in the vaccine to different alleles of the human DRB1 Class II MHC protein using freely available epitope prediction programs and compared protein sequences from clinical isolates to the sequences included in the Mtb72f vaccine. This analysis predicted that the Mtb72f vaccine would be less effective for several DRB1 genotypes, due either to limited vaccine epitope binding to the DRB1 proteins or to binding primarily by unconserved PPE18 epitopes. Furthermore, we found that these less-protective DRB1 alleles are found at a very high frequency in several populations with a high burden of tuberculosis.</p> <p>Conclusion</p> <p>Although the Mtb72f vaccine candidate has shown promise in animal and clinical trials thus far, it may not be optimally effective in some genotypic backgrounds. Due to variation in both <it>M. tuberculosis </it>protein sequences and epitope-binding capabilities of different HLA alleles, certain human populations with a high burden of tuberculosis may not be optimally protected by the Mtb72f vaccine. The efficacy of the Mtb72f vaccine should be further examined in these particular populations to determine whether additional protective measures might be necessary for these regions.</p

    Depth classification of underwater targets based on complex acoustic intensity of normal modes

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    In order to solve the problem of depth classification of the underwater target in a very low frequency acoustic field, the active component of cross spectra of particle pressure and horizontal velocity (ACCSPPHV) is adopted to distinguish the surface vessel and the underwater target. According to the effective depth of a Pekeris waveguide, the placing depth forecasting equations of passive vertical double vector hydrophones are proposed. Numerical examples show that when the sum of depths of two hydrophones is the effective depth, the sign distribution of ACCSPPHV has nothing to do with horizontal distance; in addition, the sum of the first critical surface and the second critical surface is equal to the effective depth. By setting the first critical surface less than the difference between the effective water depth and the actual water depth, that is, the second critical surface is greater than the actual depth, the three positive and negative regions of the whole ocean volume are equivalent to two positive and negative regions and therefore the depth classification of the underwater target is obtained. Besides, when the 20 m water depth is taken as the first critical surface in the simulation of underwater targets (40 Hz, 50 Hz, and 60 Hz respectively), the effectiveness of the algorithm and the correctness of relevant conclusions are verified, and the analysis of the corresponding forecasting performance is conducted.National Natural Science Foundation (China) (Grants 1404406, 51179034, 41072176 and 11204109)Public Science and Technology Research Funds Projects of Ocean (Grant 201405036-4)China Postdoctoral Science Foundation (Grant 2013M531015)Defense Technology Research (Grant JSJC2013604C012
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