5 research outputs found
Insectes : une filière d’avenir pour les biotechnologies des Insectes
Insectes : une filière d’avenir pour les biotechnologies des Insectes. Insectinov - Insectes : une filière d'avenir pour les biotechnologie
Insectes : une filière d’avenir pour les biotechnologies des Insectes
Insectes : une filière d’avenir pour les biotechnologies des Insectes. Insectinov - Insectes : une filière d'avenir pour les biotechnologie
Microheterogeneity of the oligosaccharides carried by the recombinant bovine lactoferrin expressed in Mamestra brassicae
Development and validation of a pen side test for Rift Valley fever
International audienceBackground Rift Valley fever (RVF) is one of the main vector borne zoonotic diseases that affects a wide range of ruminants and human beings in Africa and the Arabian Peninsula. A rapid and specific test for RVF diagnosis at the site of a suspected outbreak is crucial for the implementation of control measures. Methodology/Principal findings A first-line lateral flow immunochromatographic strip test (LFT) was developed for the detection of the nucleoprotein (N) of the RVF virus (RVFV). Its diagnostic performance characteristics were evaluated using reference stocks isolates recovered from different hosts and in geographic regions mimicking clinical specimens and from known RVF negative serum samples. A high level of diagnostic accuracy (DSe (35/35), DSp (167/169)) was observed, including the absence of cross-reactivity with viruses belonging to different genera. Author summary Rift Valley fever (RVF) is a viral disease that affects a wide range of animals and human beings in Africa and the Arabian Peninsula involving low case fatality rates. A rapid and specific test for RVF diagnosis at the site of a suspected outbreak is crucial for the implementation of control measures. Here, we report the development and the evaluation of the diagnostic performance characteristics of a pen-side test found to be a highly accurate and valuable first-line diagnostic tool for on-site RVF detection