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  • 1
    Online Resource
    Online Resource
    Virus-Like Particles Are a Superior Platform for Presenting M2e Epitopes to Prime Humoral and Cellular Immunity against Influenza Virus
    MDPI AG ; 2018
    In:  Vaccines Vol. 6, No. 4 ( 2018-09-20), p. 66-
    Details
    In: Vaccines, MDPI AG, Vol. 6, No. 4 ( 2018-09-20), p. 66-
    Abstract: Influenza virus M2 protein has a highly conserved ectodomain (M2e) as a cross-protective antigenic target. We investigated the antigenic and immunogenic properties of tandem repeat M2e (5xM2e) proteins and virus-like particles (5xM2e VLP) to better understand how VLP and protein platform vaccines induce innate and protective adaptive immune responses. Despite the high antigenic properties of 5xM2e proteins, the 5xM2e VLP was superior to 5xM2e proteins in inducing IgG2a isotype antibodies, T cell responses, plasma cells and germinal center B cells as well as in conferring cross protection. Mice primed with 5xM2e VLP were found to be highly responsive to 5xM2e protein boost, overcoming the low immunogenicity and protective efficacy of 5xM2e proteins. Immunogenic differences between VLPs and proteins in priming immune responses might be due to an intrinsic ability of 5xM2e VLP to stimulate dendritic cells secreting T helper type 1 (Th1) cytokines. We also found that 5xM2e VLP was effective in inducing inflammatory cytokines and chemokines, and in recruiting macrophages, monocytes, neutrophils, and CD11b+ dendritic cells at the injection site. Therefore, this study provides evidence that 5xM2e VLP is an effective vaccine platform, inducing cross-protection by stimulating innate and adaptive immune responses.
    Type of Medium: Online Resource
    ISSN: 2076-393X
    URL: Article
    DOI: 10.3390/vaccines6040066
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2703319-3
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  • 2
    Online Resource
    Online Resource
    Phage Display Screening of Bovine Antibodies to Foot-and-Mouth Disease Virus and Their Application in a Competitive ELISA for Serodiagnosis
    MDPI AG ; 2021
    In:  International Journal of Molecular Sciences Vol. 22, No. 9 ( 2021-04-21), p. 4328-
    Details
    In: International Journal of Molecular Sciences, MDPI AG, Vol. 22, No. 9 ( 2021-04-21), p. 4328-
    Abstract: For serodiagnosis of foot-and-mouth disease virus (FMDV), monoclonal antibody (MAb)-based competitive ELISA (cELISA) is commonly used since it allows simple and reproducible detection of antibody response to FMDV. However, the use of mouse-origin MAb as a detection reagent is questionable, as antibody responses to FMDV in mice may differ in epitope structure and preference from those in natural hosts such as cattle and pigs. To take advantage of natural host-derived antibodies, a phage-displayed scFv library was constructed from FMDV-immune cattle and subjected to two separate pannings against inactivated FMDV type O and A. Subsequent ELISA screening revealed high-affinity scFv antibodies specific to a serotype (O or A) as well as those with pan-serotype specificity. When BvO17, an scFv antibody specific to FMDV type O, was tested as a detection reagent in cELISA, it successfully detected FMDV type O antibodies for both serum samples from vaccinated cattle and virus-challenged pigs with even higher sensitivity than a mouse MAb-based commercial FMDV type O antibody detection kit. These results demonstrate the feasibility of using natural host-derived antibodies such as bovine scFv instead of mouse MAb in cELISA for serological detection of antibody response to FMDV in the susceptible animals.
    Type of Medium: Online Resource
    ISSN: 1422-0067
    URL: Article
    DOI: 10.3390/ijms22094328
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2019364-6
    SSG: 12
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  • 3
    Online Resource
    Online Resource
    Boundary Conditions for Transient and Robust Performance of a Reduced-Order Model-Based State Feedback Controller with PI Observer
    MDPI AG ; 2021
    In:  Energies Vol. 14, No. 10 ( 2021-05-17), p. 2881-
    Details
    In: Energies, MDPI AG, Vol. 14, No. 10 ( 2021-05-17), p. 2881-
    Abstract: One common technique employed in control system design to minimize system model complexity is model order reduction. However, controllers designed by using a reduced-order model have the potential to cause the closed-loop system to become unstable when applied to the original full-order system. Additionally, system performance improvement techniques such as disturbance observers produce unpredictable outcomes when augmented with reduced-order model-based controllers. In particular, the closed-loop system stability is compromised when a large value of observer gain is employed. In this paper, a boundary condition for the controller and observer design parameters in which the closed-loop system stability is maintained is proposed for a reduced-order proportional-integral observer compensated reduced-order model-based controller. The boundary condition was obtained by performing the stability analysis of the closed-loop system using the root locus method and the Routh-Hurwitz criterion. Both the observer and the state feedback controller were designed using a reduced-order system model based on the singular perturbation theory. The result of the theoretical analysis is validated through computer simulations using a DC (direct current) motor position control problem.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en14102881
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2437446-5
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  • 4
    Online Resource
    Online Resource
    Out-of-Step Prediction Using DQN-Based Disturbance Observer and Its RTDS Verification
    MDPI AG ; 2022
    In:  Energies Vol. 15, No. 7 ( 2022-04-05), p. 2652-
    Details
    In: Energies, MDPI AG, Vol. 15, No. 7 ( 2022-04-05), p. 2652-
    Abstract: Despite having extensive research dedicated towards designing methodologies for synchronous out-of-step detection, the risk posed by a large-scale power blackout still makes power system protection an active research area. In recent decades, multiple out-of-step detection techniques such as impedance-based relays and equal-area criterion-analysis-based methods have been widely adopted. However, these conventional techniques have been known to suffer from drawbacks that may be attributed to the inherent assumptions of their foundational design principles. Therefore, to alleviate some of the problems faced in the currently adopted techniques, researchers have been studying the implementation of estimation algorithms for synchronous out-of-step detection. Aiming to contribute to this research area, this paper proposes a synchronous out-of-step detection algorithm that uses a deep Q-network-based disturbance observer, robust to measurement noise. Using the disturbance estimation provided by the observer and a separately gathered critical clearing time data of the power grid, a neural network is trained to relate the magnitude of the estimation with the critical clearing time. The trained neural network is then used to provide an estimation of the critical clearing time for the algorithm, which uses the information to predict whether a fault will result in a stable power swing or a synchronous out-of-step detection. The performance of the proposed algorithm is verified through a real-time digital-simulator-based hardware-in-the-loop simulation. The results show that the proposed algorithm can detect synchronous out-of-step prediction by estimating the disturbance resulting from line fault within two cycles and predicting the critical clearing time at sample fault locations within a 3% margin of error.
    Type of Medium: Online Resource
    ISSN: 1996-1073
    URL: Article
    DOI: 10.3390/en15072652
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2437446-5
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