Computational Guided Method Applied to LSPR‐Based Biosensor for Specific Detection of the Four‐Serotypes of Dengue Virus in Seropositive Patients

In this paper, a localized surface plasmon resonance (LSPR)-based biosensor, computationally guided to detect selectively the four Dengue virus (DENVx) serotypes in seropositive patients, is presented. The behavior of gold nanoparticles in the shape of nanorods is theoretically and numerically studied as a function of induced structural variations, which are experimentally evidenced due to the bio-interaction between the target analytes and its surface during the detection process. Additionally, with the implementation of the largest Lyapunov exponent, it is possible to calculate the notion of predictability for the experimental results, observing chaotic systems with a very low probability of repetition. Due to the above, when analyzing the recurrence map associated with the obtained resonance curve generated by the LSPR system, the genetic similarity of DENV3/DENV2 and DENV4/DENV1 is evidenced. Finally, the biosensors are validated by analyzing samples of seronegative patients for DENVx and seropositive ones for other Flaviviruses such as Zika virus, Yellow Fever virus, and Saint Louis Encephalitis virus.