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Sökning: WFRF:(Cox Peter) > Örebro universitet

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1.
  • Gulati, Sunita, et al. (författare)
  • Utilizing CMP-Sialic Acid Analogs to Unravel Neisseria gonorrhoeae Lipooligosaccharide-Mediated Complement Resistance and Design Novel Therapeutics
  • 2015
  • Ingår i: PLoS Pathogens. - : Public Library of Science (PLoS). - 1553-7366 .- 1553-7374. ; 11:12
  • Tidskriftsartikel (refereegranskat)abstract
    • Neisseria gonorrhoeae deploys a novel immune evasion strategy wherein the lacto-N-neotetraose (LNnT) structure of lipooligosaccharide (LOS) is capped by the bacterial sialyltransferase, using host cytidine-5'-monophosphate (CMP)-activated forms of the ninecarbon nonulosonate (NulO) sugar N-acetyl-neuraminic acid (Neu5Ac), a sialic acid (Sia) abundant in humans. This allows evasion of complement-mediated killing by recruiting factor H (FH), an inhibitor of the alternative complement pathway, and by limiting classical pathway activation ("serum-resistance"). We utilized CMP salts of six additional natural or synthetic NulOs, Neu5Gc, Neu5Gc8Me, Neu5Ac9Ac, Neu5Ac9Az, legionaminic acid (Leg5Ac7Ac) and pseudaminic acid (Pse5Ac7Ac), to define structural requirements of Sia-mediated serum-resistance. While all NulOs except Pse5Ac7Ac were incorporated into the LNnT-LOS, only Neu5Gc incorporation yielded high-level serum-resistance and FH binding that was comparable to Neu5Ac, whereas Neu5Ac9Az and Leg5Ac7Ac incorporation left bacteria fully serum-sensitive and did not enhance FH binding. Neu5Ac9Ac and Neu5Gc8Me rendered bacteria resistant only to low serum concentrations. While serum-resistance mediated by Neu5Ac was associated with classical pathway inhibition (decreased IgG binding and C4 deposition), Leg5Ac7Ac and Neu5Ac9Az incorporation did not inhibit the classical pathway. Remarkably, CMP-Neu5Ac9Az and CMP-Leg5Ac7Ac each prevented serum-resistance despite a 100-fold molar excess of CMP-Neu5Ac in growth media. The concomitant presence of Leg5Ac7Ac and Neu5Ac on LOS resulted in uninhibited classical pathway activation. Surprisingly, despite near-maximal FH binding in this instance, the alternative pathway was not regulated and factor Bb remained associated with bacteria. Intravaginal administration of CMP-Leg5Ac7Ac to BALB/c mice infected with gonorrhea (including a multidrug-resistant isolate) reduced clearance times and infection burden. Bacteria recovered from CMP-Leg5Ac7Ac-treated mice were sensitive to human complement ex vivo, simulating in vitro findings. These data reveal critical roles for the Sia exocyclic side-chain in gonococcal serum-resistance. Such CMP-NulO analogs may provide a novel therapeutic strategy against the global threat of multidrug-resistant gonorrhea.
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2.
  • Lowry, Stephanie, 1979-, et al. (författare)
  • Visual Place Recognition : A Survey
  • 2016
  • Ingår i: IEEE Transactions on robotics. - : IEEE Robotics and Automation Society. - 1552-3098 .- 1941-0468. ; 32:1, s. 1-19
  • Tidskriftsartikel (refereegranskat)abstract
    • Visual place recognition is a challenging problem due to the vast range of ways in which the appearance of real-world places can vary. In recent years, improvements in visual sensing capabilities, an ever-increasing focus on long-term mobile robot autonomy, and the ability to draw on state-of-the-art research in other disciplines - particularly recognition in computer vision and animal navigation in neuroscience - have all contributed to significant advances in visual place recognition systems. This paper presents a survey of the visual place recognition research landscape. We start by introducing the concepts behind place recognition - the role of place recognition in the animal kingdom, how a "place" is defined in a robotics context, and the major components of a place recognition system. Long-term robot operations have revealed that changing appearance can be a significant factor in visual place recognition failure; therefore, we discuss how place recognition solutions can implicitly or explicitly account for appearance change within the environment. Finally, we close with a discussion on the future of visual place recognition, in particular with respect to the rapid advances being made in the related fields of deep learning, semantic scene understanding, and video description.
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