Showing 441 - 460 results of 19,727 for search 'sample three detection', query time: 0.27s Refine Results
  1. 441

    Development of a Multiplex Real-Time PCR Assay for the Detection of Eight Pathogens Associated with Bovine Respiratory Disease Complex from Clinical Samples by Fuxing Hao, Chunhao Tao, Ruilong Xiao, Ying Huang, Weifeng Yuan, Zhen Wang, Hong Jia

    Published 2025-07-01
    “…The targeted pathogens included the following: bovine viral diarrhea virus (BVDV), bovine parainfluenza virus type 3 (BPIV3), bovine respiratory syncytial virus (BRSV), bovine coronavirus (BcoV), <i>Mycoplasma bovis</i> (M.bovis), <i>Pasteurella multocida</i> (PM), <i>Mannheimia haemolytica</i> (MH), and infectious bovine rhinotracheitis virus (IBRV). …”
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  2. 442

    Development, Characterisation and Application of Monoclonal Antibodies for the Detection and Quantification of Infectious Salmon Anaemia Virus in Plasma Samples Using Luminex Bead... by R Hoare, K D Thompson, T Herath, B Collet, J E Bron, A Adams

    Published 2016-01-01
    “…Monoclonal antibodies (mAbs) were developed against Segment 3 (encoding the viral nucleoprotein, NP) of the virus. …”
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    Comparison of Nose Wipes, Stall Sponges, and Air Samples with Nasal Secretions for the Molecular Detection of Equine Influenza Virus in Clinically and Subclinically Infected Horses by Nicola Pusterla, Kaila Lawton, Samantha Barnum, K. Gary Magdesian

    Published 2025-03-01
    “…In recent years, the use of non-invasive host and environmental samples for the detection and monitoring of equine respiratory pathogens has shown promise and a high overall agreement with the gold standard of nasal secretions. …”
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    Article
  5. 445

    Diagnostic accuracy of real-time polymerase chain reaction assay for the detection of Trichomonas vaginalis in clinical samples: A systematic review and meta-analysis by Emmanuel O. Babafemi, Benny P. Cherian, Khalid Rahman, Gilbert M. Mogoko, Oluwatoyin O. Abiola

    Published 2025-04-01
    “…The ‘gold standard’ for its diagnosis requires 3–7 days to detect by culture. Rapid and accurate diagnosis, such as by nucleic acid amplification testing, is key to manage the disease, and control and prevent its transmission. …”
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    Robust co-immunoprecipitation with mass spectrometry for Caenorhabditis elegans using solid-phase enhanced sample preparation by Gülkiz Baytek, Oliver Popp, Philipp Mertins, Baris Tursun

    Published 2022-05-01
    “…The authors optimized co-immunoprecipitation with mass spectrometry by combining a native co-immunoprecipitation procedure with single-pot, solid-phase enhanced sample preparation. The authors' results for the highly conserved chromatin regulator FACT subunits HMG-3 and HMG-4 demonstrated that single-pot, solid-phase enhanced sample preparation-integrated co-immunoprecipitation with mass spectrometry procedures for C. elegans samples are highly robust. …”
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  17. 457

    A Simple Blind Sampling Frequency Offset Estimation Scheme for Short-Reach DD-OFDM Systems by Hong Wen, Kang Geng, Qinghui Chen, Rui Deng, Ming Chen, Tiezhu Zong, Kunping Luo, Fengnian Liu

    Published 2020-01-01
    “…In this paper, a simple and overhead-free sampling frequency offset (SFO) blind estimation and compensation scheme is proposed and experimentally demonstrated in a short-reach direct detection orthogonal frequency division multiplexing (DD-OFDM) transmission system. …”
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  18. 458

    Quantifying the Sensitivity of Targeted eDNA Surveys to Improve Detection of Invasive Cane Toads (Rhinella marina) by Ewen K. Lawler, Simon Clulow, Alejandro Trujillo‐González, Paul G. Nevill, Richard P. Duncan

    Published 2025-05-01
    “…We sampled waterbodies across the invasion front and showed that both eDNA and visual surveys had similar performance in detecting cane toads. …”
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    Mobile malware detection method using improved GhostNetV2 with image enhancement technique by Yao Du, CaiXia Gao, Xi Chen, MengTian Cui, LiLi Xu, AoJi Ning

    Published 2025-07-01
    “…However, recent studies reveal that adversarial sample generation techniques pose significant challenges to malware detection models, as their effectiveness significantly declines when identifying adversarial samples. …”
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