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Antigenic lateral flow immunoassays (LFIAs) rely on the non-competitive sandwich format, including a detection (labelled) antibody and a capture antibody immobilised onto the analytical membrane. When the same antibody is used for the capture and the detection (single epitope immunoassay), the saturation of analyte epitopes by the probe compromises the capture and lowers the sensitivity. Hence, several factors, including the amount of the probe, the antibody-to-label ratio, and the contact time between the probe and the analyte before reaching the capture antibody, must be adjusted. We explored different designs of experiments (full-factorial, optimal, sub-optimal models) to optimise a multiplex sandwich-type LFIA for the diagnosis and serotyping of two Southern African Territory (SAT) serotypes of the foot-and-mouth disease virus, and to evaluate the reduction of the number of experiments in the development. Both assays employed single epitope sandwich, so most influencing variables on the sensitivity were studied and individuated. We upgraded a previous device increasing the sensitivity by a factor of two and reached the visual limit of detection of 10 and 10 (TCID/mL) for SAT 1 and SAT 2, respectively. The positioning of the capture region along the LFIA strip was the most influent variable to increase the detectability. Furthermore, we confirmed that the 13-optimal DoE was the most convenient approach for designing the device.
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http://dx.doi.org/10.1007/s00604-023-06090-6 | DOI Listing |
Microbiol Spectr
September 2025
Institute for Medical Laboratory Diagnostics, Helios University Hospital, Witten/Herdecke University, Wuppertal, Germany.
Carbapenem-resistant organisms (CRO) have rapidly spread worldwide in recent years, posing a significant challenge to both human health and healthcare systems. Timely and accurate detection of CRO, especially carbapenemase-producing and non-fermenters, is crucial for clinical prevention and treatment of these infections. In the present study, we subjected more than 114 multidrug-resistant Gram-negative and non-fermenters to two tests for the timely detection of carbapenemases.
View Article and Find Full Text PDFOpen Forum Infect Dis
September 2025
Department of Epidemiology, University of Washington, Seattle, Washington, USA.
Accurate point-of-care tools are needed to detect early nonadherence to daily HIV regimens and support timely transitions to long-acting options. Emerging evidence suggests that females may require higher adherence than males to achieve equivalent protection. Our next-generation urine tenofovir assay showed high accuracy across sexes but lower urine drug levels among female participants.
View Article and Find Full Text PDFVet World
July 2025
Laboratory of Immunochemistry and Immunobiotechnology, National Center for Biotechnology, 010000, Astana, Kazakhstan.
Background And Aim: Bovine babesiosis, caused by , poses significant economic challenges to Kazakhstan's cattle industry. Early and accurate detection is crucial for interrupting transmission cycles, particularly in regions lacking advanced diagnostic infrastructure. This study aimed to develop a rapid lateral flow immunoassay (LFIA) using a recombinant C-terminal fragment of the recombinant rhoptry-associated protein 1 (rRap1) antigen for the serodiagnosis of bovine babesiosis.
View Article and Find Full Text PDFJ Vet Diagn Invest
September 2025
Biology Department; Faculty of Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
Lumpy skin disease (LSD) is a viral disease that affects livestock and is caused by the lumpy skin disease virus (LSDV). An outbreak of LSD in any country can lead to acute economic damage for livestock owners. The significance of prompt and accurate diagnosis in managing this viral disease cannot be overstated.
View Article and Find Full Text PDFMed Eng Phys
October 2025
Department of Engineering Science, University of Oxford, United Kingdom. Electronic address:
Traditionally, clinical devices are designed, tested and improved through lengthy and expensive laboratory experiments and clinical trials [1]. More recently, computational methods have allowed for rapid testing, speeding up the design process and enabling far more complete searches of design space. While computational models cannot fully capture the complexities of biological systems, they provide valuable insights into crucial underlying mechanisms, such as the effects of fluid-structure interactions (FSIs).
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