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Träfflista för sökning "WFRF:(Niu Hui Ling) "

Sökning: WFRF:(Niu Hui Ling)

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  • Xu, Hong-Tao, et al. (författare)
  • Effects of fucosylated milk of goat and mouse on Helicobacter pylori binding to Lewis b antigen
  • 2004
  • Ingår i: World Journal of Gastroenterology. - Beijing : WJG Press. - 1007-9327 .- 2219-2840. ; 10:14, s. 2063-2066
  • Tidskriftsartikel (refereegranskat)abstract
    • Aim:To evaluate the effects of animal milk containing fucosylated antigens on Helicobacter pylori (H pylon) binding to Lewis b antigen. Methods:A mammary gland expression vector containing human α1-3/4-fucosyltransferase cDNA sequences was constructed. Transient expression of human(α1-3/4-fucosyltransferase cDNA in goat mammary cell and establishment of transgenic mice were performed. The adhesion inhibitory properties of milk samples were analyzed by using Hpylori. Results: Goat milk samples were found to inhibit bacterial binding to Lewis b antigen. The highest inhibition was observed 42 h after injection of the plasmid. The binding activity of Hpylori to Lewis b antigen reduced mostly, by 83%, however milk samples from transgenic mice did not inhibit Hpylori binding to Lewis b antigen. Conclusion: The use of “humanized“ animal milk produced by the transgenic introduction of fucosylated antigen can perhaps provide an alternative therapy and preventive measure for Hpylori infection.
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3.
  • Kristan, Matej, et al. (författare)
  • The Ninth Visual Object Tracking VOT2021 Challenge Results
  • 2021
  • Ingår i: 2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2021). - : IEEE COMPUTER SOC. - 9781665401913 ; , s. 2711-2738
  • Konferensbidrag (refereegranskat)abstract
    • The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).
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