7 research outputs found

    Optimal latent period in a bacteriophage population model structured by infection-age

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    We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the natural death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. We consider that the length of the lysis timing (or latent period) is distributed according to a general probability distribution function. We have carried out an optimization procedure and we have found the latent period corresponding to the maximal fitness (i.e. maximal growth rate) of the bacteriophage population

    Optimal latent period in a bacteriophage population model structured by infection-age

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    We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the natural death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. We consider that the length of the lysis timing (or latent period) is distributed according to a general probability distribution function. We have carried out an optimization procedure and we have found the latent period corresponding to the maximal fitness (i.e. maximal growth rate) of the bacteriophage population

    Optimal latent period in a bacteriophage population model structured by infection-age

    No full text
    We study the lysis timing of a bacteriophage population by means of a continuously infection-age-structured population dynamics model. The features of the model are the infection process of bacteria, the death process, and the lysis process which means the replication of bacteriophage viruses inside bacteria and the destruction of them. The time till lysis (or latent period) is assumed to have an arbitrary distribution. We have carried out an optimization procedure, and we have found that the latent period corresponding to maximal fitness (i.e. maximal growth rate of the bacteriophage population) is of fixed length. We also study the dependence of the optimal latent period on the amount of susceptible bacteria and the number of virions released by a single infection. Finally, the evolutionarily stable strategy of the latent period is also determined as a fixed period taking into account that super-infections are not considere

    Preclinical evaluation of a COVID-19 vaccine candidate based on a recombinant RBD fusion heterodimer of SARS-CoV-2

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    Current COVID-19 vaccines have been associated with a decline in infection rates, prevention of severe disease and a decrease in mortality rates. However, SARS-CoV-2 variants are continuously evolving, and development of new accessible COVID-19 vaccines is essential to mitigate the pandemic. Here, we present data on preclinical studies in mice of a receptor-binding domain (RBD)-based recombinant protein vaccine (PHH-1V) consisting of an RBD fusion heterodimer comprising the B.1.351 and B.1.1.7 SARS-CoV-2 variants formulated in SQBA adjuvant, an oil-in-water emulsion. A prime-boost immunisation with PHH-1V in BALB/c and K18-hACE2 mice induced a CD4 + and CD8 + T cell response and RBD-binding antibodies with neutralising activity against several variants, and also showed a good tolerability profile. Significantly, RBD fusion heterodimer vaccination conferred 100% efficacy, preventing mortality in SARS-CoV-2 infected K18-hACE2 mice, but also reducing Beta, Delta and Omicron infection in lower respiratory airways. These findings demonstrate the feasibility of this recombinant vaccine strategy
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