OBJECTIVES: This paper focused on how the refractive index based nanobio-sensoring gold platform can produce more efficient, adaptable and more practical detection techniques to observe molecular interactions at high degree of sensitivity. It discusses surface chemistry approach, optimisation of the refractive index of gold platform and manipulation of gold geometry augmenting signal quality.
METHODS: In a normal-incidence reflectivity, r0 can be calculated using the Fresnel equation. Particularly at λ = 470 nm the ratio of r / r0 showed significant amplitude reduction mainly stemmed from the imaginary part of the Au refractive index. Hence, the fraction of reduction, Δr = 1 - r / r0. Experimentally, in a common reference frame reflectivity of a bare gold surface, R0 is compared with the reflectivity of gold surface in the presence of biolayer, R. The reduction rate (%) of reflectivity, ΔR = 1 - R / R0 is denoted as the AR signal. The method therefore enables quantitative measurement of the surface-bound protein by converting ΔR to the thickness, d, and subsequently the protein mass. We discussed four strategies to improve the AR signal by changing the effective refractive index of the biosensing platform. They are; a) Thickness optimisation of Au thin layer, b) Au / Ag bimetallic layer, c) composing alloy or Au composite, and d) Au thinlayer with nano or micro holes.
RESULTS: As the result we successfully 'move' the refractive index, ε of the AR platform (gold only) to ε = -0.948 + 3.455i, a higher sensitivity platform. This was done by composing Au-Ag2O composite with ratio = 1:1. The results were compared to the potential sensitivity improvement of the AR substrate using other that could be done by further tailoring the ε advanced method.
CONCLUSION: We suggested four strategies in order to realize this purpose. It is apparent that sensitivity has been improved through Au/Ag bimetallic layer or Au-Ag2O composite thin layer, This study is an important step towards fabrication of sensitive surface for detection of biomolecular interactions.
METHODS: Ten RDTs were evaluated: nine to detect clinical P. knowlesi infections from Malaysia, and nine assessing limit of detection (LoD) for P. knowlesi (PkA1-H.1) and P. falciparum (Pf3D7) cultures. Targets included Plasmodium-genus parasite lactate dehydrogenase (pan-pLDH) and P. vivax (Pv)-pLDH.
RESULTS: Samples were collected prior to antimalarial treatment from 127 patients with microscopy-positive PCR-confirmed P. knowlesi mono-infections. Median parasitaemia was 788/µL (IQR 247-5,565/µL). Pan-pLDH sensitivities ranged from 50.6% (95% CI 39.6-61.5) (SD BIOLINE) to 87.0% (95% CI 75.1-94.6) (First Response® and CareStart™ PAN) compared to reference PCR. Pv-pLDH RDTs detected P. knowlesi with up to 92.0% (95% CI 84.3-96.7%) sensitivity (Biocredit™). For parasite counts ≥200/µL, pan-pLDH (Standard Q) and Pv-pLDH RDTs exceeded 95% sensitivity. Specificity of RDTs against 26 PCR-confirmed negative controls was 100%. Sensitivity of six highest performing RDTs were not significantly different when comparing samples taken before and after (median 3 hours) antimalarial treatment. Parasite ring stages were present in 30% of pre-treatment samples, with ring stage proportions (mean 1.9%) demonstrating inverse correlation with test positivity of Biocredit™ and two CareStart™ RDTs.For cultured P. knowlesi, CareStart™ PAN demonstrated the lowest LoD at 25 parasites/µL; LoDs of other pan-pLDH ranged from 98 to >2000 parasites/µL. Pv-pLDH LoD for P. knowlesi was 49 parasites/µL. No false-positive results were observed in either P. falciparum-pLDH or histidine-rich-protein-2 channels.
CONCLUSION: Selected RDTs demonstrate sufficient performance for detection of major human malaria species including P. knowlesi in co-endemic areas where microscopy is not available, particularly for higher parasite counts, although cannot reliably differentiate among non-falciparum malaria.